Film Comparative Analysis

Film Comparative Analysis The general solution following the screening was a distinct realization that nobody is above the law, and that the stereotypes associated with the cono nearly left Larranaga guilty as mis takenly named. (Syjuco, 2012) thither is no referee, when innocent men are in empower away this is the main subject that the deuce films carry in common. With this, permit us ask ourselves, Is on that point re every last(predicate)y something wrong with the Philippine and Texas referee system? Are we to sustain that it is a corrupt system that we have? These two films ordain bring out our eyes wide opened to the truth or if not, to the flaws and corruptions in the justice system, not only of our own country, but to a fault that of the new(prenominal)s. I. Background separate Up Tomorrow The text fileary film is intimately a Filipino-Spanish educatee named Paco Larranaga, who was sentenced to death in 2004 for the double murder and rape of Chiong sisters (Marijoy and Jacqueline) in 1997. This is the fabrication of what we now know as the Chiong Murder Case, a cebu scandal of the century. two Chiong sisters go missing on July 16, 1997. Larranaga was one, on with six other suspects who was pinpointed by the terra firma witness, David Rusia. David Rusia is a convicted felon and was sentenced to prison twice in the United States for other crimes. As claimed by Rusia, he was with Larranaga in Ayala Center, Cebu early in the level of July 16, that evening Larranaga says that he was at R&R Restaurant in Quezon City with his fri finishs such fact was proven by photographs and the testimonies of his friends.The defense presented xxxv witnesses, including Larranagas teachers and classmates at the Center for Culinary Arts (CCA) in Quezon City, who all testified under oath that Larranaga was in Quezon City, when the crime is said to have taken place in Cebu. The trial court considered these testimonies irrelevant, rejecting these as coming from friends of the accused, and were not admitted. The following are also evidences presented by the defense during trial a)Larranaga, at that time was at a party at the R&R Restaurant along Katipunan Avenue, Quezon City, and stayed there until early morning the following day. )After the party, the logbook of the aegis guard at Larranagas condominium indicates that Larranaga returned to his Quezon City condominium at 245 a. m. c)Rowena Bautista, an instructor and chef at the culinary center, said Larranaga was in school from 8 a. m. to 1130 a. m. and saw him again at about 630 p. m on July 16. d)The schools registrar, Carolean Calleja, said she proctored a two-hour exam where Larranaga was present from 130 p. m. Larranaga go to his second round of midterm exams on July 17 commencing at 8 a. m. Only then did Larranaga leave for Cebu in the late aft(prenominal)noon of July 17, 1997. )Airline and airport personnel also came to court with their flight records, indicating that L arranaga did not take any flight on July 16, 1997, nor was he on board any rent aircraft that landed in or departed from Cebu during the relevant dates, except the 5 p. m. PAL flight on July 17, 1997 from Manila to Cebu The aforementioned evidences did not preserve the assent of Larranaga along with his six co-accused. The trial court judge, after interpretation judgment against them, was prepare dead in a hotel in Cebu, and allegedly committed suicide.This unexpected event during the Chiong murder case was proven in the film to be part of the whole scheme of putting the institutionalise on Larranaga, and concealing the truth of the facts with regard to the murder and rape of the Chion sisters. Larranaga, along with the other co-accused were sentenced to death, and appealed later on, but all of them were denied. Considering the Filipino-Spanish nationality of Larranaga, his family asked for help from the Spanish government. In September 2009, the Department of Justice approve d Larranagas transfer to a Spanish prison.Thelma Chiong, the mother of the victims, expressed shock over the decision, saying that, despite Larranagas Spanish citizenship, If you committed a crime in the Philippines, you are jailed in the Philippines, despite the fact that this would constitute a breach of the treaty and thence of international law. Larranaga, escorted by two Spanish Interpol agents, left for Spain on October 6, 2009. His dependable behavior at the New Bilibid Prison was taken into consideration, and he go out serve the rest of his sentence at the Madrid Central punitive at Soto del Real. The Thin Blue LineThe film is an investigation into the 1976 murder of Dallas practice of law officer Robert Wood. Harris testified that Adams had shot and killed Wood after their car had been pulled over on their way home from a movie. Adams claimed to know nothing of the murder, insisting that Harris had dropped him at his home two hours before it occurred. Local authorities believed Harris, and witnesses corroborated his story, leading to Adams credit and a death sentence, (which was later on changed). Randall Adams recalls the events in detail after running out of gas, he had been picked up by Harris in a stolen car.The two had gone to a movie where they drank beer and smoked marijuana, and this was the extent of their relationship. David Harris, on the other hand, also recalls the events of the evening in detail, but creates a much different impression. Adams defense attorneys thought that Harris was the killer, pointing to his past lamentable record and other crimes committed the night of the murder. The film presents a serial publication of interviews about the investigation and reenactments of the shooting, based on the good word and recollections of Adams, Harris, and various witnesses and detectives. Two attorneys who epresented Adams at the trial where he was convicted of capital murder also come out of the closet they suggest that Adams was charged with the crime despite the better evidence against Harris because, as Harris was a new-fashioned, Adams alone of the two could be sentenced to death under Texas law. II. Similarities and Differences The two films both dealt on the fact that there is a corrupt justice system. That even an innocent man can be put into jail all for the sake of concealing the truth. This idea is very obvious in the films presented, that even a man of little knowledge with the law will doubt the guilt of both, Larranaga and Adams.The idea brought up by the filmmakers of both was a frame up or cover up which lead to the sentence of innocent people. The very controlling authorities in both were the law of nature officers, the judge, and other executive officers of the government and to add, the media, influencing the course of the trial and the impression of the great deal on the suspects. In both, natural law authorities were overwhelmed with the idea of having someone to put the blame fo r the murder of the victims. They were like heroes of the public for having solved the case and found a suspect. In which, it is very obvious that it was politically motivated.As one of the differences among the case of Larranaga and Adams, is that of having exhausted all administrative remedies. Larranaga, after being convicted in the trial court, appealed to the Supreme Court, but was not able to attain a favourable judgment. After such, taking into consideration of the dual citizenship of Larranaga, they asked for the help of Spanish government so that the death penalty be withdrawn and let him be transferred in Spain where he will serve his sentence. This however surface the way for the abolishment of death penalty by former Pres.Gloria Arroyo and the thanksgiving of Larranagas transfer. The cases of Larranaga and Adams both involved beneficials which were violated. As declared under the planetary Declaration of Human Rights (UDHR), the following are those evidently violate d in the course of the whole trial of the case, (a) member 11, par. 1, (b) Article 9 and (c) Article 10. Article 11, par. 1 Everyone charged with a penal offense has the right to be presumed innocent until proved guilty according to law in a public trial at which he has had all the guarantees demand for his defense.In light of this article which pertains to the right of an accused to be presumed innocent, Larranaga was outrightly charged as a criminal in the minds of the people, especially those of the Cebuanos, even before a trial was held. Aggravating this situation was the participation of the media from the start up to the end of the case, tagged as the trial of the decade. The impressions that were make by the police authorities and the media, contributed to the image of Larranaga as guilty of the crime charged.His identity was corroborated as a rich bad boy/gangster from a salient family, in which the people presumed that they will make use of their resources to pay for wit nesses and bullshit the whole case and avoid prosecution. As to the case of Adams, he was made fit to the image of a cop-killer as compared to Harris. The prosecution relied on the testimony of Harris that it was Adams who killed Wood, even before the start of the case, they knew already who to convict. The fact that Harris was a juvenile that time, made it more likely for Adams to commit the crime thus woful away from the presumption of his innocence. Article 9 No one shall be subjected to arbitrary arrest, detention or exile. The course of Larranagas arrest came spry and unexpected and appeared to him as kidnapping. The people who arrested him were all in civilian clothes, though they looked like policemen. They did not identify themselves when they arrested Larranaga, until they were asked by Larranagas sister. They unlawfully arrested Larranaga collectable to absence of warrant of arrest, in defense, they said that he committed a continuing crime.As to Adams case, he was tak en into the custody of the police few eld after the commission of the crime. He was forced to sign a document containing an admission that he was the one who murdered Wood. The policeman even peril him with a pistol if he will not sign it. There is no sufficient cause for his guilt. Article 10 Everyone is entitled in full equality to a fair and public hearing by an independent and impartial tribunal, in the determination of his rights and obligations and of any criminal charge against him.The right to a fair and speedy trial was not accorded to Larranaga, first, the media had participated a lot in drawing the image of Larranaga as the criminal. The judge also showed his impartiality which was really unexplainable. After having refused to accept the testimonies of witnesses of Larranaga, preventing him to take the witness impasse and rendered a judgment of double life imprisonment, the judge was found in a hotel dead. Through the series of events that had transpired, the fairness and impartiality of the trial cannot be said to be present.As in the case of Adams, it cannot be said to have been a fair trial for him because the prosecution presented fake witnesses, in which the conviction was based. There is a biased judgment and inconsideration on the merits of the case. Adams was not able to defend himself, such conviction of him was predicated on the failure of his defense lawyer to clearly establish his innocence albeit all the frame-ups that had transpired. References http//www. centerforsocialmedia. org/sites/default/files/documents/pages/interview_transciption_giveuptomorrow. pdf http//en. wikipedia. org/wiki/The_Thin_Blue_Line_(film)

The Death of Ivan Ilyich

The Death of Ivan Ilyich, by Tolstoy, is the account of a man who is faced with twinge and death in which no sensation seems to believe him. Hes a common man with common dreams. Hes non extraordinary in any way. Ivan Ilyich is a soundly literary protagonist. His guinea pig goes though ups and downs, is well rounded and relatable. Ivan married Praskovya Fedorovna. Ivan doesnt appear to be in love with her.She is attractive, has money, a good social standing and he really has no objection to her, the marriage gave him personal satisfaction, and at the like time it was considered the right thing by the most highly place of his associates (Lawall). This is a relatable piece of life. This may have held more truth punt in this era, but its not that far off nowadays either. Many people marry for reasons other than love. Ivan had a good muse and was very happy with it despite being passed over for a advance at one time.He was said to be a valet de chambre and was admired by his p eers. When things were good, they were good. And when they werent, well, they just werent. His wife, with discover any reason de gaiete de coeur as Ivan Ilych express it to himself began to disturb the pleasure and propriety of their life. She began to be jealous without any cause, judge him to devote his whole attention to her, found fault with everything, and made vernacular and ill-mannered scenes (Lawall). The ups and downs of his life are what make him a good literary protagonist.Perhaps this scene is one that men brush off be sympathetic towards more than women. Having a well-rounded character makes for a good literary protagonist. When the reader sees Ivan struggling with his own mortality this completes a circle of persuasion for the character. The reader has watched Ivan through good times and bad and has been able to unite on different levels. In the depth of his heart he knew he was dying, but not only was he not accustomed to the thought, he simply did not and could not arrest it (Lawall).Being able to grasp the finality of death especially your own, is something that people have thought around and struggled with throughout their lives. It reminds people they are real and not indestructible. A good literary protagonist is one that is relatable and well-rounded and people need to be able to see this character through their ups and downs and still come out with them as being on top in the end. The Death of Ivan Ilyich, by Tolstoy, is the story of a man who had a good life, a the right way wife and in the end he suffered and died. As the eader goes through the story of Ivan they are taken into his entire life. He is someone the reader can empathize with which allows connections between the character and reader. Everyone thinks about their mortality at one time or another, but to think about what others think of your own mentality is something entirely different. Besides considerations as to the executable transfers and promotions likely to result from Ivan Ilychs death, the mere fact of the death of a close acquaintance aroused, as usual, in all who heard of it the complacent feeling that, it is he who is dead and not I (Lawall).

Baroque Oratorio

Oratorio, which literally means hall for prayer, strictly refers to the musical setting usually pertaining to religion having a storyline. Usually, the text or story is based on religious books such as legers. It is wish an opera minus the scenery, costumes and actions, but has a lot of recitative. In profit to this, at some time, the forms and styles that is present in the oratorio is almost evenhandedly accurate than that of the opera and focuses greatly on chorus (Boynick, 1996, February 1).Handels Hallelujah let out from his oratorio The Messiah features elements such as basso continuo, homophony, combined instrumental-vocal forms, and a pleasant harmony. Basso continuo refers to the sustaining of either the bass or and the keyboard instrument. This would give to the development of a continuous accompaniment. Furthermore, this is notated with a new music bank note system. Homophony refers to the use of one melodic voice while being come with by instruments. Handel used a musical technique called the text-painting.It is a technique wherein the melody mimics its lyrics. Melodic rhythm can be observed in Hallelujah Chorus. The rhythm kept changing wherein the word hallelujah was sung in so many different ways. The rhythm of the piece in macro- and microbeats is Bah- layabout Bum Bah Bah-Bah Bum Bah (Runfola and Taggart, 2005). Handels Hallelujah Chorus is still popular nowadays because it is practically heard in churches. In addition to this, Handels Hallelujah Chorus continues to budge or adapt with the generation.There atomic number 18 variations of this piece that becomes familiar to everybody, especially those who are really religious. The piece is also intriguing that it states a story from the bible in a way that excites the audience. References Boynick, M. (February 1, 1996, October 10, 2000). Musical Forms Oratorio. The Grove Concise lexicon of Music Retrieved February 3, 2008, from http//w3. rz-berlin. mpg. de/cmp/g_oratorio. html Runfol a, M. , & Taggart, C. C. (2005). The Development and Practical Application of Music accomplishment Theory. USA GIA Publications.

Performance and Value in Business in Relation to Religion Essay

Its commonly known that Christians wont the Bible as a slide by to salvation and to assist in having a stable loving family and home life. However, the Bible is far to a greater extent useful than many imagine. The Bible is also a resource for the workplace. The archetypal day on the job is often stressful however, the Bible provides blow with Psalm 23, The Lord is my shepherd (NIV) Besides comfort, the Bible is a guide to proper functioning in the workplace. A longsighted with performance is pry, and both argon important in military control.Managers should not increase a firms value or performance by treating employees harshly (Brealey et. al., p.14). They should act without unserviceable conceit or selfish ambition, but with humility (Phil. 23). The value of a company is increased by the performance of the manager(s), and this is accomplished by meeting business standards, complying with all laws, tax codes, and paying debts on beat (Rom. 131) (Mat. 2217) (Rom. 137). Manag ers that are successful have reinforced a trust with employees and other business partners which further enhance performance and increase a companys value by creating long term working relationships (Brealey et. al., p. 15).Teaching others that you can be trusted serves to pass on profits and trusting in the Lord is essential (Tit. 210) (Tit. 38). Ones own belief in Christianity and using its priceless lessons as a guide to life is great, but what if people began to combine it in business as a regular practice? This question was posed by Laura Nash in the article where she was interviewed. She is a senior question fellow at Harvard Business School (Lagace 2001).Understanding religion in todays business is critical because you may win contracts with Buddhistic and Muslims and feel the underlying ghostly current. Managers need to understand that a religious uprising in India can affect their plants operation there. Managing a business creates stress with others that can lead to poor interactions even hate and voracity may develop. A religion based on love much(prenominal) as Christianity to work as a spiritual anchor and train best business practices (Lagace 2001).

Professional and legal implications Essay

This naming countenance explore the nonrecreational soulfulness and wellnessy suggestions of a scenario which took place within a wellness apportion noniceting during the last year. health distribute is very(prenominal) complex and finishs ab step to the fore how services atomic number 18 provided tail assembly return a huge effect on peoples lives. on that pointfore it is dogmatic form that the aid called has the beaver chance of benefiting a coarse-suffering and non harming them. that, in the pastime scenario a finality do by a healthcargon original for the scoop out rice beers of their tolerant is challenged by the longanimouss niggle. To entertain confidentiality the real names of the individuals manifold set about been changed (NMC, 2008). Katie is a 24 year old woman who has been admitted to hospital with a severe chest infection. Katie suffers from recur chest infections over delinquent to her condition and also has noetic palsy, l earning disabilities and epilepsy. payable to these conditions Katie is unable to communicate, requires a Naso Gastric Tube for feeding, is doubly incontinent and has unitary to ane billing from a wellness Cargon Support proletarian for all her personal and clinical needs.Katie lives with her induce at home, who provides her maintenance during the night. The medical police squad discovered that her chest infection is Pneumonia and begin the relevant interference, hitherto believe that ascribable to Katies quality of action she should be non for Resuscitation (NFR) in the event of a cardiac fascinate. However, Katies induce argues that her girl should be resuscitated and the determination should be make by her, because she is her m opposite and that the health cargon team are neglecting her daughters reppair to animateness and are acting illegally by make much(prenominal) a ratiocination. Katies mum also believes that the health care team are basing their closi ng on Katies learning dis readiness preferably than her lift out interests. This testify volition encompass the honorable considerations that need to be sought when a finale much(prenominal)(prenominal)(prenominal) as NFR is made. Taking into score the legal and headmaster implications this has on the health care team involved. ahead reservation either decisiveness the health care captain give need to consider if the Katie has the noetic cater, what are in the her best interests and hold dear the her human correctlys. All these topics entrust be included in this evidence. This essay lead also explain why it is important for a health care superior to take into account the Bolam Test and percentage 4 of the genial readiness Act (2005), taking into consideration a tolerants best interest when they lack capacity, before they necessitate any determination. The medical examination Team mustiness act in accordance with the executethat is accepted at that eon a nd by a recognised passkey body (Dimond 2008). All these issues are relevant in this scenario. Making a decision much(prenominal) as NFR is taken very seriously due to the have sexn expiration in the event of a cardiac arrest.A Not For Resuscitation (NFR) decision indicates that a decision has been made non to advert the resuscitation team if in the future that diligent, much(prenominal) as Katie, suddenly dinero breathing or suffers cardiac arrest. Resuscitation decisions are very controversial and have been the subject of much media interest. Especially when that patient has a learning harm. There is evidence of this in the appendix at the back of this essay and it will be reasoned further on in the essay.A decision such as NFR is the responsibility of the most senior clinician for the particular proposition(prenominal) patient, according to a revised advocate of cardiopulmonary resuscitation (2007). Every health board should have a resuscitation policy. The Local He alth Boards policy involved in this scenario can be rear in the appendix of this essay. The policy, create in (2009) states that cardiopulmonary resuscitation ( cardiopulmonary resuscitation) should be obtaind unless the patient has refused cardiac resuscitation the patient is at the mitigatory stage of illness or the burdens of the treatment outweigh the benefit.The Health Care Team are needed, before they confide any decision to determine if Katie has mental capacity and if she is able to clear and contribute to the decisions of her treatment. If Katie had capacity and was non meditateed about the decision thusly the heath care schoolmaster could be seen as acting unlawfully and the decision kneadr would be legally and professionally responsible (B v An NHS curse 2002). The psychological Capacity Act (2005) describes capacity as an individuals ability to retrace a certain decision at a specific time and not on their ability to cook decisions generally. Legal ca pacity depends on the patients understanding kind of than their wisdom. They should be able to retain and understand the cultivation that they are given and then communicate their decision with the appropriate professional (Simpson, 2011). A patients competency to capacity should not be presumed.An assessment of capacity should be made before a person can be said to be incapacitated (NMC, 2008). Nurses have the ability to assess capacity, if they feel that it is needed. However, they do not have the authority to make a decision such as NFR (Hawley 2007). so, they mustrefer to a doctor or psychologist to assess the patients capacity and make such a decision (Hutchison, 2005). Katies mental capacity, following the Mental Health Act (2005), will need to be assessed by a doctor or a psychologist due to the significance of the decision. The Case of Re C (1994) helped produce the 3 stage test of capacity and this has prove to be a suitable test used in the assessing run of capacity. However, the introduction of the Mental Capacity Act resulted in a fourth Stage being added (Section 3 MCA).The test trys whether the individual is able to perceive and retain information, Believe information given and weigh it up, balance the risks and needs, make a choice. The fourth stage is to communicate the decision. In this particular scenario, afterwardwards an assessment of Katies Mental Capacity using this test, resolved that Katie did not have the Mental Capacity to make decisions due to her inability to understand the information and communicate the decision. This enables the team to make this decision for her as long as it is in her best interests. Katies mother believes that she should be the one to make this decision for her daughter because she is her next of kin and Katies causality of attorney. The Mental Capacity Act (2005) allows a person to legally set up a lasting power of attorney.The chosen person or persons have the power to make decisions on the ind ividuals financial and personal behalf. The act does not allow enduring power of attorneys to be set up however those already in existence can continue to be used. The lasting power of attorney has the power to give consent on behalf of a patient who is incapacitated if it is in their best interest (Thomson et al, 2006). However, the lasting power of attorney does not have the power to order a patient who is NFR or who is suitable NFR, as in this scenario, to be resuscitated if a health care professional has assessed that the outcome would not be in the best interest of the patient. There is no obligation to give treatment that is futile or burdensome as seen in the case of Re J (A Minor) (Wardship Medical Treatment 1990). As in the case of R (Burke v General Medical Council 2004) no person has a legal right to insist on specific treatments either for themselves or relatives.The health care professional is not oblige by law to resuscitate Katie irrelevant weather Katies mother is next of kin or has power of attorney. It was discovered afterwards that Katies mother was not her power of attorney because Katie had never had the capacity to nominate one. The health care professional will make their decision after assessing the patient and following the appropriate legal examples which are set to protect them and the patient and examining what decision would be in Katies best interests. Section 4 of the Mental Capacity Act (2005) sets out the legal framework for a best interest decision to be made, for people without mental capacity. This can be found in the appendix of the essay. The Act states that the health care professional making the decision must not make it simply on the basis of the patients age or appearance. The patients condition and aspects of behaviour must not assume the judgements of best interests and duty of care.The health care professional making the decision must consider all the relevant circumstances and consider the possibleness of the patient gaining capacity (MCA, 2005). However, if this is not possible then the health care professional must revise the past and present wishes of the patient, especially if an climb directive has been made. In relation to the scenario, it is crucial that this checklist is considered when making a decision such as NFR, due to Katies Learning disabilities. Mencap (2007) published a report called remainder by indifference which can be found in the appendix of this essay. The report examines cases where families believed that doctors used inappropriate use of Do Not Resuscitate Orders simply because the patient had a learning disability rather than assessing the best interest of the patient resulting in institutional discrimination. The Mental Capacity Act (2005) adds that the health care professional must consult anyone caring for the patient or who is concerned for their welfare and gain their views on the decision (Dimond, 2008).In this scenario Katies mother was addressed and i nformed of the decision and her views were taken into account, despite the disagreement of the boilersuit decision. Katies mums attitude and opinion towards the decision could be biased. She whitethorn genuinely not recognise that an NFR decision would be in the best interests of her daughter. Katies mother has her own values and beliefs that are likely to be factors that can twist her disapproval. The health care professional involved with Katies care will need to reassure Katies mum, show compassion and empathise with her situation. As stated earlier in the essay, the best interests of Katie can be determined via consideration of a checklist of circumstances within Section 4 of the MCA (2005). The benefits of treatmentand the probability of them arising are considered (Griffiths and Tengnah 2008). In this scenario the benefits of resuscitation would be measured. If it was concur that resuscitation would do to a greater extent harm than good then it would be considered that NFR would be in Katies best interests (Re A (mental patient sterilisation) 2001).Due to Katies quality of life, because of her cerebral palsy and epilepsy, it was considered by the health care professionals that it was in the best interest of Katie that she becomes NFR, as the outcome of resuscitation would not rectify her quality of life. It was also agreed that resuscitation would do more harm to Katie than good, due to the probability of resuscitation being unsuccessful. However, Katies mum believes that the health care professionals are depriving her daughter of a right to life as was in the case of Airedale NHS Trust v savourless 1993. The Human Rights Act (1998) is an Act of Parliament produced to protect the rights of individuals. The Act incorporates crowd rights and protocols and is comprised of several articles. Schedule 1 Article 2, the Right to Life is of particular relevance in this scenario. The Article legally entitles every persons individuals right to life to be prot ected by law. It states that an individuals life should not be deprived intentionally. Katies mum believes that the decision of NFR is infringing her daughters human rights.If this is proved to be the situation then the professional could face legal action (Dimond, 2008). In this scenario the health care professionals are acting in Katies best interests and will not face any legal proceedings as long as they can justify their decision. This was illustrated in the cases of subject Health Service Trust A V D and others 2000, NHS Trust A v M 2001 and NHS Trust B V H 2001 indicates that decisions such as NFR, which are found to allow the individual to die with gravitas and be in the best interests of the person, are not legally classed as infringing human rights. It could be implied that the decisions of NFR supports Katies human rights. If it is considered that Katies quality of life would remain poor or that resuscitation could potentially cause her harm and not be in Katies best in terests then it could be implied that resuscitation in the event of Katie experiencing a cardiac arrest could prove a contaminating treatment (Thompson et al, 2006).In this particular scenario Katies mother is accusing the health care professionals of being heedless. The case of (Bolam v Friern Hospital Management delegation 1957)initiated the Bolam test. The Bolam test is used to examine if a health care professional has been negligent. If the health care professional has acted in accordance with an accepted trust which is approved by a recognised professional body then they cannot be thought as negligent. However, it could be disputed that the health care professional could be assumed negligent if they resuscitated Katie since it is not in her best interests as the health care professionals have a legal duty of care to preclude acts or omissions which can potentially victimize the patient (Donogue v Stevenson 1932). If the health care professionals were to resuscitate Katie an d it resulted in her becoming harmed then the health care professionals could be accused of being negligent under the Bolam test. Once a decision such as NFR has been reassert and documented then if Katie was resuscitated in the event of a cardiac arrest then this treatment could been seen as battery and it is unlawful as in the case of (Airedale NHS Trust v Bland 1993).Such as in the case of Bland where the patients recovery was not going to happen due to him being in a ineradicable Vegetative State, then the courts can decide that treatment can be withdrawn and not infringe the human rights of the individual (NHS Trust v M 2001). In this scenario the health care team have decided, that due to Katies ongoing chest infections, the pain that she welcomes from her conditions and her poor quality of life, it would not be in Katies best interests for her to be resuscitated in the event of a cardiac arrest. Consequently health professionals are not infringing her right to life and con sequently not legally negligent. All health care professionals have a duty of care to their patients (Dimond, 2008). For this section of the essay the author will focus on how a decision such as NFR can have on a adjudge and discuss the legal implications that may occur. Registered keeps are governed by The Code Standards of conduct, performances and ethical motive for harbours and midwives (NMC, 2008). The formula is not a legal document however, it sets a framework of standards that a hold in must adhere to within their recitation and it enables them to act lawfully. Decisions such as NFR can cause professional issues for a entertain.The nurse is the frontline provider of their patients care (Dimond, 2008). They have the most contact with the patient and their relatives. They oftentimes develop a therapeutic kindred with both. This could cause the nurse to face a dilemma of being criticised by the family and friends of the patient if theydo not commence CPR or even face reproach from their colleges if they did proceed with CPR (Dimond, 2008). The nurse may feel duty-bound to commence CPR due to the relationship they have formed with the patient. However, the nurse must always act lawfully. Due to the nurses role as the care provider, they often have contact with the family members. This may provide difficulties for the nurse if the family, such as Katies mum, disagree with a decision that has been made. Therefore, the nurse may be confront with a possible confrontation from the family or friends of the patient due to their disapproval (Hughes and Baldwin, 2006).The nurse has a responsibility to their patients to provide a high standard of care (NMC, 2008). However, at times they may feel as though they are being prevented from providing this standard when a decision such as NFR is issued and could cause them professional implications. However, it could also be argued that the nurse is fulfilling their role in such a situation as the nurse has a dut y to alleviate the suffering of patients (Rumbold, 2002). The nurse would not be alleviating a patients suffering if they commenced CPR and it had been decided that it was not in the patients best interests. Nurses are accountable for their actions (NMC, 2008). The accountability of not providing CPR to a patient can present the nurse with a professional implication. Therefore, as the essay mentioned earlier, if the decision of NFR is legal then the nurse will not be held professionally accountable for not commencing CPR if their patient experiences a cardiac arrest.All Health care professionals are responsible for maintaining standards set in the code of professional conduct. The NMC (2008) governs nurses to Adhere to the laws of the nation in which you are practicing. This implies that nurses are needed to act lawfully. They are required to follow orders such as NFR regardless of their own values and beliefs. A decision such as NFR creates the question of who has the right to de cide what is in the best interests of a patient. Even though the person making the decision is professionally qualified to do so they may find it tangled in proving that it is in the best interests of a patient without capacity (Runciman et al, 2007). The professional has a duty to act lawfully and be able to protract this when making such an important decision. The attitudes of a nurse can offer professional implications for a decision such as NFR. Attitudes are governed by personal values and beliefs. If the nurse did not agree that it is in thebest interests of the patient to become NFR this could create some difficulties. The nurse may decide to vocalise what they consider is in the best interests of their patient and this could conflict with the NFR decision made by the health care professional resulting in an ethical dilemma (Thompson et al, 2006).According to Schlutz (1998), there is considerable evidence that many nurses experience the feeling of powerlessness when confron ted with an ethical dilemma and fear conflict with other professionals such as consultants and doctors. Due to this they may turn out by instructions regardless of it conflicting with their own professional values and beliefs. This could imply that the nurse involved with Katies care could follow an instruction as NFR despite it being against their own professional opinion. However, the nurse must be accountable for their actions and must indicate a satisfactory reason for their conduct (NMC, 2008) therefore potentially resulting in a professional implication. Rundell (1992) claims that the nursing of a palliative patient and providing them with a dignified closing, uncomplicated or uncompromised by CPR could prove to be more complex than simply intervening and commencing CPR. Therefore not intervening when a patient is suffering a cardiac arrest can result in a professional implication of the NFR decision.The nurse could find it very difficult to watch a patient suffer a cardia c arrest and not be allowed to step in because of an NFR decision made by a health care professional who may not even have had a therapeutic relationship with the patient or their family. Doctors and nurses are professionally responsible to perform beneficently, justifying and respecting the rights of others (Thompson et al, 2006). kindness can be defined as an action taken that will benefit others and prevent and remove harm. Examples of harm are suffering and death (Herbert, 1998). If a health care professional fails to act beneficently it violates social, moral and professional standards (Beauchamp and Childress, 1989). This principle implies that the health care professional would be acting unskilled by not commencing CPR. However, Casteldine (1993) implies that it is of greater beneficence for the health care professional to acknowledge end of life on certain occasions rather than using CPR, which could potentially cause harm, to prevent death. This implication is seen withi n the scenario.However it is imperative that the staff perform lawfully. Health care professionals are often faced with thedilemma as to whether a certified decision has been made morally and legally accepted. This could result in disputes due to differentiating values and beliefs (Herbert, 1998). The NMC (2008) states that a patient, who does not possess capacity, should be protected. This may cause conflict in role responsibility in an NFR decision, as a health care professional not commencing resuscitation in the event of a cardiac arrest could potentially cause the issue of passive non-voluntary euthanasia. This is a further professional implication that the nurse may experience when a decision such as NFR is initiated. Passive non-voluntary Euthanasia can be defined as when the individual who dies is unable to give their consent and the individuals competent requests concerning euthanasia are not known, such as Katies wishes are not know due to her not having the mental capacit y.In effect it involves not providing or discontinuing treatments that would be relatively successful in preventing the patients death because death is considered to be kind to the patient by the health care professional making the decision. Therefore, this type of euthanasia depends on other factors for its act in causing death, such as Katies underlying pneumonia which if go away untreated could kill her or promote her inability to breathe satisfactorily without oxygen or respiratory assistance. By withdrawing treatment or as in Katies case creating an NFR that would normally be done for a patient with this condition, with the objective of causing the patients death out of compassion could be regarded as passive euthanasia and be see as allowing the patient to die rather than killing them. Again when faced with such a situation the nurse must always abide by the NMC Code (2008) and act lawfully in their practice and they will not be accountable for breaching their professional duties. In conclusion, this essay has contained legion(predicate) reasons why legal implications could arise due to Katies mother disagreeing with the NFR decision.When a health care professional makes a decision such as NFR, it is taken very seriously and as this essay has explained the health care professional has a legal obligation to justify their decision. They are required to follow the appropriate assessments and procedures before making their decision. The health care professional has a duty of care to their patient and they must ensure that they are considering the overall outcome and quality of life if CPR was performed and if it would be in their patients best interests orpotentially cause harm. It is imperative that they discuss all decisions with the immediate family and reassure the family that they are acting in the best interest of the patient (Hawley, 2007). Decisions such as NFR need to be regularly reassessed because a patients condition may improve or they may r egain their capacity to make decisions. There are many legal and professional implications that the health care professional could adjoin due to such a decision. Therefore it is essential that they are certified of the law because they will be accountable for their actions.Ultimately they must be able to prove that they are acting in the best interests of the patient and be able to provide relevant evidence to support this. In this particular scenario, Katies mother was made fully aware of the NFR decision and what it meant if Katie was to have a cardiac arrest. She was involved in the decision making process and consulted regarding her daughters condition. Soon after the health care professional made the NFR decision Katies health deteriorated due to the Pneumonia and subsequently her quality of life was poorer than previously. It was at this point that Katies mum finally accepted the NFR decision and realised that it was in the best interests of her daughter that she should not be resuscitated.As the essay has shown, in the event that Katies mother pursued a clinical negligence claim against the Health Board, on the grounds that she believed the health care professionals in charge of Katies care were neglecting her daughters right to life, the likeliness of a ruling that Katie be for resuscitation in the event of a cardiac arrest would be unlikely due to Katies mental capacity, overall outcome, quality of life and the evidence supporting the health care professionals decision that it would be in Katies best interest.In conclusion, the essay draws on the fact that all health care professionals, when making a decision such as NFR are required by law to assess patients mental capacity, follow a code of practice and always act in the best interest of the patients regardless of the patients families views and a patients disability. In order for this to be achieved, the Bolam Test and Section 4 of the MCA (2005) should be considered. The health care professiona l in this scenario conducted their decision process accordingly, following the correct assessments and legal frameworks, basing their decision on Katies best interests due to her ill health rather than her learning disability. Word Count 4,268References* Airedale NHS Trust v Bland 1993 1 ALL ER 449* B v An NHS Trust 20022 ALL ER 449* Beauchamp TL and Childress JF, (1989), Principles of biomedical ethics, third edition, Oxford University argue * Bolam v Friern Hospital Management Committee 1957 1 WLR 582 * British Medical Association (2007) Resuscitation Council (UK) and the Royal College of Nursing, Decisions relating to cardiopulmonary resuscitation, BMA. * Campbell A, Grant G and Jones G, (2005) Medical ethical motive, fourth part Addition, Oxford publishers * Castledine G, (1993), The Nursing Way of Death, British Journal of Nursing, 16 138-146. * Degrazia D, (1999), Advanced Directives, alienation and the Someone else problem Journal of bioethics, 13 (5) 373. * Dimond B, (200 8) Legal aspects of Nursing, Fifth edition, Pearson discipline publishers. * Donogue v Stevenson 1932 AC 562 599* Grifiths R and Tengnah C, (2008), Mental Capacity Act ascertain best interest, British Journal of Community Nursing, 13 (7) 335-340 * Hawley G (2007) Ethics in clinical practice an interpersonal approach. Pearson Education. * Herbert C L, (1998), To be or not to be an ethical debate on the not for resuscitation experimental condition of a stoke patient, Journal of Clinical Nursing, 6 99-105 * Hughes JC and Baldwin C, (2006), Ethical issues in dementia care making difficult decisions, Jessica Kingley Publishers * Hutchinson C, (2005), Addressing issues related to the adult patient who lack the capacity to give consent, Nursing Standard, 19 (23) 47-53 * http//www.dailymail.co.uk/health/artcle-2101445/NHS* http//www.gmc-uk.org/guidance/ethical_guidance/writing_references.asp * http//www.mencap.org.uk/74deaths* http//www.legislation.gov.uk/ukpga/2005/9/contents* http//www .lawcf.org/CMS/uploads/611/documents/Case Note on Leslie Burke * National Health Service Trust A v D and others 2000 Lloyds rep med 411 * NHS Trust A v M 2001 1 ALL ER 801* NHS Trust B v H 2001 1 ALL ER 801* Nursing and Midwifery Council (2008) Code of Professional Conduct Standards for Conduct, performance and ethics, NMC * R (on the application of Burke) v General Medical Council and Disability rights commission and the ordained solicitor of the Supreme Court 2004 Lloyds Rep Med 451 * Re A (Mental unhurried Sterilisation) 2001) 1 FLR 594* Re C (Adult refusal of treatment) 1994 1 ALL ER 819* Re J (a Minor) (Wardship Medical treatment) (1991) Fam 33 1990 3 All ER 930 1991 2 WLR 140 Times, 03 October 1990 1992 1 FLR * Rumbold G, (2002) Ethics in nursing practice, Third edition, Bailere Tindall issue * Rundell s and Rundell L, The Nursing Contribution of the resuscitation debate, Journal of clinical nursing, 1 195-198 * Runicman B, snappy A and Walton M (2007), Safety and ethics i n healthcare a guide to getting it right, Ashgate publishers * Schluzt L, (1998), Not for Resuscitation two decades of challenge for nursing ethics and practice, nursing ethics, 4 (3) 227-240 * Thomson IE, Melia KM, Boyd KM and Horsburgh D, (2006) Nursing ethics, Fifth edition, Churchill Livingstone.

Real-Time Fraud Detection: How Stream Computing Can Help the Retail Banking Industry

Para os meus pais, porque o politesse das coisas nao esta no tempo que elas duram, mas na intensidade com que acontecem. Por isso existem momentos inesqueciveis, coisas inexplicaveis e pessoas incom mirror symmetryveis como voces Obrigado por tudo, Filipe Abstr wreak The sell Banking Industry has been severely affected by subterfuge over the past tense few years. Indeed, despite solely the enquiry and material bodyation of ruless functional, deceitsters ease up been sufficient to sidestep and deceive the commits and their clients. With this in mind, we narrow down to come before a novel and multi- goal engine room k instantern as flow rate Computing, as the basis for a duplicity sensing solution.Indeed, we believe that this calculator computer architecture leave behind stimulate research, and to a smashinger extent authorisedly makeups, to invest in Analytics and statistical dupery-Scoring to be utilize in join with the already in-place pr correcttive te chniques. Therefore, in this research we explore antithetical strategies to mastergress a Stream base fraud staining solution, victimisation advanced info exploit algorithmic programs and statistical digest, and show how they bear to increased accuracy in the contracting of fraud by at least 78% in our seed entropy primp. We excessively discuss how a combination of these strategies buns be infix in a Stream-based application to detect fraud in real time.From this perspective, our experiments lead to an average impact time of 111,702ms per trans execute, magic spell strategies to further improve the operation atomic number 18 discussed. Key oral communication cunning detection, Stream Computing, Real-Time Analysis, subterfuge, entropy tap, Retail Banking Industry, entropy Preprocessing, data Classi? cation, Behavior-based pecks, Supervised Analysis, Semi-supervised Analysis Sammanfattning Privatbankerna har drabbats hart av bedragerier de senaste ben. Bedragare har lyckats kringga forskning och tillgangliga administration och lura bankerna och deras kunder.Darfor vill vi infora en ny, polyvalent strommande datorteknik (Stream Computing) for att upptacka bedragerier. Vi tror att denna struktur kommer att stimulera forskningen, och framfor all(a)t fa organisati superstarrna att investera i analytisk och statistisk bedragerisparning som kan anvandas tillsammans med be? ntlig forebyggande teknik. Vi undersoker i var forskning olika strategier for att skapa en strommande losning som utnyttjar avancerade algoritmer for datautvinning och statistisk analys for att upptacka bedragerier, och visar att dessa okar traffsakerheten for att upptacka bedragerier med minst 78% i var referensbas.Vi diskuterar aven hur en kombination av dessa strategier kan baddas in i en strommande applikation for att upptacka bedragerier i realtid. Vara forsok ger en genomsnittlig bearbetningstid pa 111,702ms per transaktion, samtidigt som olika strategier for a tt fortsatta forbattra resultaten diskuteras. Acknow directgments soundless gratitude isnt much function to any superstar Gladys Bronwyn Stern When I wrote the ? rst countersigns in this report I think I had no idea what a Master Thesis is aboutI wadt hip-hop myself though since I never wrote one before, however if you ask me now to describe this experience I would say that its wish a road trip you set yourself a destination, you conduct a devoted crew that is always there for you, a roadmap, give birthers on the side and past the journey unhorses. Within the latter(prenominal), you show set suffers with the table service of new(prenominal)s, you share knowledge, you meet in the buff people and to the highest degree importantly you get to know them This journey would non start been assertable without the support, camaraderie and guidance of legion(predicate) friends, colleagues and my family.For all these reasons, I couldnt let the journey end without expressin g my gratitude to apiece and e very(prenominal)(prenominal)one of them. First and foremost, I would like to express my sincere gratitude to my supervisor, Philippe Spaas, who make it possible for me to fit in this acoustic projection under his supervision and in collaboration with IBM. It was a immunity to work alongside with him and a unique learning opportunity for me I am indebted for his precious guidance and for the time dedicated non just in helping me understand how a research report card should be formulated, but also in reviewing the latter.Thank you I am very conveyful as wellspring to Tybra Arthur, who graciously accepted me in her group and supported my internship, Jean de Canniere who accepted to be my Manager and without whom I wouldnt establish had this opportunity. In this line of thought, I am also pleasing to Hans cutting edge Mingroot who helped me secure this project in its negotiation phase. All third were key elements, and their support and guida nce without the research were important to me and very much appreciated.I would also like to express my gratitude to prof Mihhail Matskin at KTH the regal Institute of Technology for having accepted this Master Thesis and for beingness my examiner. His insights and help were invaluable to achieve to a greater extent sound end results and put in concert this ? nal report In addition, I would like to incubate my personalizedized give thanks to my Erasmus Coordinator, Anna Hellberg Gustafsson, for her support, kindness and dedication for the duration of the research which was key to the organization of the latter.She is, for me, the shell coordinator I have met and heard about I would probably non have crapn the appropriate steps to have this opportunity deep down IBM if it werent for the initial support and guidance of Karl De Backer, Anika Hallier, Anton Wilsens and last but non least Parmjeet Kaur Gurmeet. I truly value their follow-up both on the research and on my ex perience On a surplus measure I would like to thank Parmjeet for having been always a wide-cut learn to me and for her support and trust ever since the Extreme Blue internship.I want to thank each IBMer with whom I came in contact with in the Financial serve Sector De lotment for welcoming me into their working environment and for making my stand by very enjoyable. In addition to the aforesaid(prenominal) IBMers, among many others and in no speci? c order I would like to thank Daniel Pauwels, Patrick Taymans, Hedwige Meunier, Gauthier de Villenfagne, Michel Van Der Poorten, Kjell Fastre, Annie Magnus, Wouter Denayer, Patrick Antonis, Sara Ramakers, Marc Ledeganck, Joel Van Rossem and Stephane Masso increment. It was a real pleasure to share the open space and, to a greater extent(prenominal) importantly, to meet themDan Gutfreund at IBM Haifa was a key element in the victimization of this thesis. I am very appreciative for the discussions we had about Fraud detection and for his advice in the various phases that compose this research. In addition, I would like to extend my thanks to Jean-Luc Collet at IBM La Gaude for his valuable help in obtaining a stable virtual elevator car with InfoSphere Streams. I am thankful to Professor Gianluca Bontempi and Liran Lerman at Univer berth Libre de Bruxelles for ? nding the time to discuss about Fraud spying and info Mining techniques.Their insights were vital for the reading of the prototype and the general research. On the corresponding vein, I would like to thank Chris Howard at IBM capital of Ireland for his help in understanding Stream Computing and InfoSphere Streams. His guidance was authoritative for a timely comprehension of the ? long time without which I wouldnt have been able to develop the prototype. I want to thank Mike Koranda and s besidesl Thorson at IBM Rochester for their help in understanding the integration of entropy Mining and Stream Computing and how to achieve the latter in a more ef? cient manner.I really appreciated their help with the prototype, un cat valiumly when atypical errors occurred to more pronto detect the line of the problem. I am also thankful to IBM, as a lodge, for providing me the opportunity and necessary facilities to conduct my thesis project, as well as to KTH, as university, for having allowed me to teach on this experience. I want to become this opportunity to thank my friend, Thomas Heselmans, for having been there ever since the spot one of the research despite my busy agenda. His support and concern were vital in times of great stress and trouble, thank you for your friendshipThe same applies to Stephane Fernandes Medeiros, a great friend of mine who was always there for me and followed my work very closely. In addition, I am thankful to two of my greatest friends, Nicola Martins and Alberto Cecilio, for their friendship, for always load-bearing(a) me and always having my back. Margarida Cesar is a very important per son in my life, and I would like to express my gratitude for all the discussions and advice we shared, as well as for the support demonstrated ever since we met. I always take her advice very in earnest and she has helped me cope with dif? ulties in more than one occasion, namely during the thesis, and for that Im very thankful I am also very pleasant to my friend, Arminda Barata, for all the help she provided me in moving and adapting myself to capital of Sweden. Without her help and concern I wouldnt have felt at home so good, and I wouldnt have liked Stockholm from the very ? rst day. I would like to take advantage of this opportunity to thank all my colleagues and friends in Stockholm for making these two years of write up unforgettable, and for shaping the person I am today.Among so many others, I would like to thank in finicky Sanja Jankolovska, Boshko Zerajik, Pedram Mobedi, Adrien Dulac, Filipe Rebello De Andrade, Pavel Podkopajev, Cuneyt Caliskan, Sina Molazem, Arezoo Ghannadian and Hooman Peiro. I couldnt have made it by without all of them withstand but de? nitely not least, beca custom I didnt have the run into to formally thank my friends in my previous studies, I would like to take this opportunity to extend my thanks to them for all the good moments we spent unitedly throughout our bachelor degree as well as today.In particular I would like to thank Miruna Valcu, Rukiye Akgun, Vladimir Svoboda, Antonio Paolillo, Tony Dusenge, Olivier Sputael, Aurelien Gillet, Mathieu Duchene, Bruno Cats, Nicolas Degroot and Juraj Grivna. I reserve a special thank you note to Mathieu Stennier, for both his friendship and support throughout my schoolman life, and for having shared with me what were the best moments I had in Brussels composition at UniversityI would very much like to express myself in Lusitanian to my family so that they trick all more easily understand what I have to say, thank you for your understanding Nao podia deixar de agradecer a toda a minha familia o apoio que demonstraram ao longo deste percurso academico que conhece hoje um novo capitulo. Gostaria de agradecer a todos sem excepcao por acreditarem em mim e nunca duvidarem das minhas capacidades. Obrigado por estarem sempre presentes apesar da distancia, obrigado por se preocuparem comigo e por fazerem com que eu saiba que poderei sempre contar com vocesSou verdadeiramente um ser afortunado por poder escrever estas palavras Um obrigado especial a minha grande avo Olga por estar sempre disposta a sacri? car-se por nos e por telefonar quase diariamente a perguntar se estou bem e se preciso de alguma coisa. Agradeco-lhe do fundo do coracao esse amor que tem pelos illuminateos e que tanta forca transmite Queria agradecer tambem aos meus bests Rui e Hugo, que sao para mim como os irmaos que eu nunca tive, a forca que me transmitem para seguir em frente face as adversidades da vida. Ambos ensinaram-me imenso durante toda a vida e sao uma fonte de inspiracao constante para mimA admiracao que tenho por eles foi como um guia que me levou onde estou hoje Obrigado por acreditarem em mim para levar a bom porto este projecto e por terem estado sempre presentes a apoiar-me Gostaria de deixar uma mensagem de apreco ao David, que e mais do que um primo para mim, e um melhor amigo, que sempre esteve presente e sempre se preocupou comigo durante a tese. Foram momentos, frases e situacoes da vida que ? zeram com que o David se tornasse na pessoa importante que e para mim e ao longo da tese as suas mensagens de apoio foram sempre bem recebidas porque deram-me um alento enorme.Aproveito tambem para agradecer a minha querida tia Aida e ao meu estimado primo Xico pela preocupacao que tem sempre comigo e por serem uma fonte de inspiracao para mim. Desejo tambem aproveitar esta oportunidade para agradecer a Nandinha e Jorginho todo o apoio que me deram nao so durante estes 6 longos meses mas desde os meus primeiros passos. Sao como uns segundos pais para mim cujo apoio ao longo deste curso e capitulo da minha vida foi primordial. Agradeco, do fundo do coracao, o facto de me tratarem como se fosse um ? lho, por me guiarem e sempre ajudarem Tenho ainda um lugar especial reservado para o meu tio Antonio.Um tio que admiro muito, que sempre me quis bem e cujo dom da palavra move montanhas O seu conselho e para mim uma maisvalia, e agradeco todo o seu apoio e ajuda durante esta investigacao e sobretudo por me guiar quando nao ha estrelas no ceu. Aproveito para vos deixar a todos um pedido de desculpa por nao estar presente como gostaria, e agradeco o facto de que apesar de tudo voces estejam todos de pe ? rme atras de mim Sem o vosso apoio nunca teria feito metade do que ? z Costuma-se guardar o melhor para o ? m, e por isso nao podia deixar de agradecer aos meus pais tudo o que ? eram e fazem por mim A lingua de Camoes e escassa para que eu consiga descrever o quao grato estou Dedico-vos esta tese, por sempre me terem render todo o amo r, carinho, e ajuda necessaria para ter uma vida feliz e de sucesso. Deixo aqui um grande e sentido obrigado por terem estado sempre presentes quando mais precisava, por me terem sempre apoiado a alcancar os meus objectivos, por me terem ensinado a viver, a amar, a partilhar e a ser a pessoa que sou hoje. Obrigado Em particular gostaria de agradecer ao meu pai a compreensao que teve comigo durante este periodo mais ocupado.Agradecer-lhe a ajuda em conseguir por um meio termo as coisas e a olhar para elas de outro prisma. Agradeco tambem a calma que me transmitiu e transmite, e o apaziguamento que me ensinou a ter face as adversidades da vida. Sem estas licoes de vida, que guardarei sempre comigo, sinto que a tese nao teria sido bem sucedida e eu nunca teria alcancado tudo o que alcancei A minha mae, agradeco por onde hei-de comecar? Pela ajuda diaria durante a tese para que os meus esforcos se concentrassem no trabalho? Pela inspiracao diaria de um espirito lutador que nao desmorona face as di? culdades e injusticas da vida?Agradeco por tudo isto e muito mais pois sem a sua ajuda diaria nao teria conseguido acabar a tese. A admiracao que tenho pela sua forca e coragem ? zeram com que eu tentasse seguir os mesmos passos e levaram-me a alcancar patamares que considerava inalcancaveis A paciencia que teve durante todo o projecto, mas sobretudo no ? m, e de louvar, e sem o seu ombro amigo teria sido tudo muito mais complicado. Obrigado a todos por tudo Thank you all for all(prenominal)thing Filipe Miguel Goncalves de Almeida set back of Contents 1 Introduction Part I setting the Scene 2 Retail Banking and The State of the Art in Detection and cake of Fraud 2. The Retail Banking Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. 1. 1 A terse Walk Down Memory Lane . . . . . . . . . . . . . . . . . . . . 2. 1. 2 The Retail Banking IT Systems architecture . . . . . . . . . . . . . . 2. 2 Fraud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. 2. 1 meshwork and E-Commerce Fraud . . . . . . . . . . . . . . . . . . . . . 2. 2. 2 early(a) Consumer Fraud . . . . . . . . . . . . . . . . . . . . . . . . . . 2. 3 Current radicals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. 3. 1 Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. 3. 2 Analytics and Statistical Fraud-Scoring . . . . . . . . . . . . . . . . . 3 Problem De? nition 3. 1 Weak Links in presently Available Solutions . 3. 1. 1 Bank Card and Pin Code . . . . . . . . . 3. 1. 2 One-Time-Password or Card Reader . . 3. 1. 3 Biometrics . . . . . . . . . . . . . . . . . 3. 1. 4 Analytics and Statistical Fraud-Scoring 3. 2 Facts and views . . . . . . . . . . . . . . . . . 3. 2. 1 France . . . . . . . . . . . . . . . . . . . 3. 2. 2 United Kingdom . . . . . . . . . . . . . 3. 3 E-Commerce and Internet Banking . . . . . . . 3. 4 unsettled Banking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2 3 3 3 4 6 6 12 12 13 14 15 15 16 17 18 18 19 19 19 20 21 22 22 23 23 23 24 24 25 25 28 28 29 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 31 31 31 32 32 33 34 Research Methodology 4. 1 object of the Research . . . . . . . . . . . . . . . 4. 2 selective randomness Collection . . . . . . . . . . . . . . . . . . . . 4. 2. 1 FICOs E-Commerce proceedings Dataset . 4. 2. 2 Personal Retail Bank Transactions . . . . . 4. 3 Data Analysis Plan . . . . . . . . . . . . . . . . . . 4. 3. 1 Partitioning of the Data . . . . . . . . . . . 4. 4 Instruments and implementation Strategy . . . . . 4. 4. 1 InfoSphere Streams . . . . . . . . . . . . . . 4. 4. 2 SPSS modeler . . . . . . . . . . . . . . . . . 4. 4. 3 MySQL Database . . . . . . . . . . . . . . . Part II Behind the Curtains 5 Phase 0 Data Preprocessing 5. Getting to have sex the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 1. 1 specifys and their Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 1. 2 Attributes in the Retail Banking Industry and in FICOs Dataset . . . . . . 5. 1. 3 Statistical Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 2 Data lessening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 2. 1 Dimensionality Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 2. 2 Supervised Merge and Transformation of nominal and Categorical Data . 5. 3 5. 4 5. 5 5. 6 . 7 5. 8 Cleaning Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 3. 1 Missing Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 3. 2 Noisy Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Data Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 4. 1 Transformation of generation and Dates . . . . . . . . . . . . . . . . . 5. 4. 2 Transformation by Normalization . . . . . . . . . . . . . . . . . . consume Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 5. 1 lot utilize K-Means algorithm . . . . . . . . . . . . . . . 5. 5. 2 Under-Sampling Based on Clustering . . . . . . . . . . . . . . . . Preprocessing Data with Stream Computing . . . . . . . . . . . . . . . . 5. 6. 1 Receiving and Sending Streams of Transactions . . . . . . . . . . 5. 6. 2 Retrieving and Storing Data to a Database . . . . . . . . . . . . . 5. 6. 3 Data Preprocessing using SPSS Solution Publisher . . . . . . . . . 5. 6. 4 Data Preprocessing using a Non-Generic C++ raw(a) Operator Rule-Based engine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 7. 1 Streams with a melody Rules Management System . . . . . . . . Final Thoughts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 36 36 37 37 37 39 40 41 42 42 43 45 45 46 48 49 50 51 51 52 53 53 54 55 56 57 57 58 60 60 61 62 62 63 63 66 71 71 73 76 77 6 Phase I Data Classi? cation 6. 1 Supervised Learning . . . . . . . . . . . . . . . . . . . 6. 1. 1 Ensemble-Based Classi? er . . . . . . . . . . . . 6. 2 Classi? cation Algorithms . . . . . . . . . . . . . . . . 6. 2. 1 Support Vector Machines . . . . . . . . . . . . 6. 2. 2 Bayesian Networks . . . . . . . . . . . . . . . . 6. 2. 3 K-Nearest Neighbors (KNN) . . . . . . . . . . 6. 2. 4 C5. 0 Decision head . . . . . . . . . . . . . . . . 6. 3 Classi? cation using the Data Mining Toolkit . . . . 6. 3. 1 Weaknesses of the Approach . . . . . . . . . . 6. 4 Classi? cation using SPSS role modeler Solution Publisher 6. 4. 1 Implementation Details . . . . . . . . . . . . . 6. 5 Model Retraining co mputer architecture High Level Overview 6. 6 Final Thoughts . . . . . . . . . . . . . . . . . . . . . . 7 Phase II unusual person Detection and Stream Analysis 7. 1 Data Aggregation . . . . . . . . . . . . . . . . . . . . 7. 2 Bank Customers Aggregation Strategy . . . . . . . . 7. 3 Anomaly Detection . . . . . . . . . . . . . . . . . . . 7. 3. 1 Techniques for Anomaly Detection . . . . . . 7. 3. 2 Mahalanobis blank space . . . . . . . . . . . . 7. 4 Stream Analysis . . . . . . . . . . . . . . . . . . . . . 7. 4. 1 Window-Based Operators . . . . . . . . . . . 7. 4. 2 Window-Based Anomaly Detection Strategy 7. 5 Final Thoughts . . . . . . . . . . . . . . . . . . . . . Part III Critical brushup 8 boilers suit Evaluation 8. 1 Performance Measurement Techniques . . . . . . . . . 8. 1. 1 Performance prosody . . . . . . . . . . . . . . . 8. 1. 2 truth Levels . . . . . . . . . . . . . . . . . 8. 2 Data Preprocessing and moving in Rules Analysis . . . 8. 3 Data Classi? cation . . . . . . . . . . . . . . . . . . . . 8. 3. 1 Un-preprocessed Classi? er Analysis . . . . . . 8. . 2 Preprocessed Un-Sampled Classi? er Analysis 8. 3. 3 Preprocessed Sampled Classi? er Analysis . . . 8. 3. 4 Ensemble-Based Classi? er Analysis . . . . . . 8. 4 Anomaly Detection . . . . . . . . . . . . . . . . . . . . 8. 5 Overall ideal . . . . . . . . . . . . . . . . . . . . . . 8. 6 Future Work . . . . . . . . . . . . . . . . . . . . . . . . 8. 6. 1 Extend Services . . . . . . . . . . . . . . . . . . 8. 6. 2 eXtreme Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 78 78 79 80 80 81 83 84 87 88 89 90 91 92 i 8. 7 8. 6. 3 architecture and Data Mining Algorithms . . . . . . . . . . . . . . . . . . . . . . . Final Thoughts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 94 95 i vi 9 Conclusion tot upix A Supporing conventions Glossary hear of bets embark 1. 1 body-build 2. 1 go out 2. 2 omen 2. 3 guess 2. 4 range 2. 5 run a target 2. 6 enroll 2. 7 experience 2. 8 practice 2. 9 manakin 3. 1 Figure 3. 2 Figure 3. 3 Figure 3. 4 Figure 3. 5 Figure 3. 6 Figure 3. 7 Figure 3. 8 Figure 4. 1 Figure 4. 2 Figure 4. 3 Figure 4. 4 Figure 4. 5 Figure 4. 6 Figure 4. 7 Figure 5. 1 Figure 5. 2 Figure 5. 3 Figure 5. 4 Figure 5. 5 Figure 5. 6 Figure 5. 7 Figure 5. 8 Figure 5. 9 Figure 5. 10 Figure 5. 11 Figure 5. 12 Figure 5. 13 Figure 5. 14 Figure 5. 15 Figure 6. Figure 6. 2 Figure 6. 3 Figure 6. 4 Figure 6. 5 Lost in Translation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . As-Is Banking IT architecture . . . . . . . . . . Hype Cycle for lotion Architecture, 2009 To-Be Banking IT write Architecture . . . . MitB Operation . . . . . . . . . . . . . . . . . . Possible Paypal nettsite (1) . . . . . . . . . . . Possible Paypal website (2) . . . . . . . . . . . Keyboard State circuit board mode . . . . . . . . . . Windows Keyboard pussyfoot method . . . . . . . Kernel-Based Keyboard Filter Driver method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 5 5 5 8 10 10 11 11 11 16 16 17 20 20 20 21 21 24 25 26 26 27 28 29 30 32 32 33 34 35 35 36 37 40 40 42 45 46 48 50 51 52 53 54 Components of the Chip and Pin pom-pom . . . . . . . . . . . . Attack to Card Illustrated . . . . . . . . . . . . . . . . . . . . One-Time-Password Hacking Material and Architecture . Number of European Internet Users and Online Purchasers Forecast US Onl ine Retail Forecast, 2010 to 2015 . . . . . . . meshwork Growth has Outpaced Non-Web Growth for Years . . . US Mobile Bankers, 2008-2015 . . . . . . . . . . . . . . . . . US Mobile Banking Adoption . . . . . . . . . . . . . . . . . . CRoss-Industry Standard Process for Data Mining . . . . . . . . . Streams Programming Model . . . . . . . . . . . . . . . . . . . . . Straight-through processing of messages with optional storage. Backup and Fail-Over System for Streams . . . . . . . . . . . . . . Multiple-Machines Architecture . . . . . . . . . . . . . . . . . . Analytical and Business Intelligent Platforms Compared . . . . . Global Flow of Events Stream-Based Fraud Detection Solution . Overall SPSS Modeler Stream for the Of? ine Data Preprocessing Phase Frequency of Transactions per hr . . . . . . . . . . . . . . . . . . . . Amount Transferred per Transaction . . . . . . . . . . . . . . . . . . . . Data Feature Selection in SPSS . . . . . . . . . . . . . . . . . . . . . . . Data Pre paration Preprocessing Phase in SPSS . . . . . . . . . . . . . . SPSS Stream CHAID tree Model . . . . . . . . . . . . . . . . . . . . . . CHAID Tree for Data Reduction . . . . . . . . . . . . . . . . . . . . . Filtering Null Values with SPSS . . . . . . . . . . . . . . . . . . . . . . . Cyclic Values of Attribute hour1 . . . . . . . . . . . . . . . . . . . . . . K-Means Modeling in SPSS . . . . . . . . . . . . . . . . . . . . . . . . . Clustering with K-Means in SPSS Modeler . . . . . . . . . . . . . . . . Stream-based Application Data Preprocessing and Rule-Based Engine Stream-based Application Data Preprocessing . . . . . . . . . . . . . . Stream-based Application Rule-Based Engine . . . . . . . . . . . . . . Interaction amongst a BRMS and a Stream-based Application . . . . . Classi? cation in Stream-Based Application .Ensemble-Based Classi? er . . . . . . . . . . . Classi? cation in SPSS . . . . . . . . . . . . . . Support Vector Machines (SVMs) Illustrated Example of a Bayesia n Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i Figure 6. 6 Figure 6. 7 Figure 6. 8 Figure 7. 1 Figure 7. 2 Figure 7. 3 Figure 7. 4 Figure 7. 5 Figure 7. 6 Figure 7. 7 Figure 7. 8 Figure 7. 9 Figure 7. 10 Figure 7. 11 Figure 7. 12 Figure 7. 13 Figure 8. 1 Figure 8. 2 Figure 8. 3 Figure 8. 4 Figure 8. 5 Figure 8. 6 Figure 8. 7 Figure 8. 8 Figure 8. Figure A. 1 Figure A. 2 Figure A. 3 Figure A. 4 Figure A. 5 Figure A. 6 K-Nearest Neighbors Illustrated . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Section of C5. 0 Decision Tree . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . SPSS C&DS Classi? er Retraining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anomaly Detection Stream-based Application . . . . . . . . . . . . Aggregate Bank Customers . . . . . . . . . . . . . . . . . . . . . . . Learning a classi? er model for the normal class of proceedings . . Transaction not be to a cluster . . . . . . . . . . . . . . . . .Transactions far from the clusters center . . . . . . . . . . . . . . . Mahalanobis Distance Illustrated . . . . . . . . . . . . . . . . . . . . Mahalanobis Distance Stream-based Application . . . . . . . . . . Window Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tumbling Windows . . . . . . . . . . . . . . . . . . . . . . . . . . . Sliding Windows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Partitioned Keyword . . . . . . . . . . . . . . . . . . . . . . . . . . . Account average expenses and frequency of proceeding in 3 days Window-Based Analysis Stream-based Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 55 60 61 63 6 4 65 65 66 67 71 71 72 73 73 74 78 79 84 86 88 89 92 92 94 ii iii iii iv iv v Benchmarking Stream-based Application Concept for Each Processing Step . . disorderliness Matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Comparison amid Un-Preprocessed and Preprocessed Data Accuracy Levels Comparison between Sampled Datasets Accuracy Levels (TP/FP) . . . . . . . Stream Analysis Debited Account . . . . . . . . . . . . . . . . . . . . . . . . . . . Overall View of the Solution Accuracy Levels (TP/FP/FN) . . . . . . . . . . . . Overall Structure of the Financial Services Toolkit . . . . . . . . . . . . . . . . . . In-Memory Database with InfoSphere Streams . . . . . . . . . . . . . . . . . . . . Stream-Based Application a Flexible and Multifaceted Architecture . . . . . . . Stream-based Application Overview . . . . . . . . . . . . . . . . . . . . . . . . . . Time per Transaction for each of the Data Preprocessing Approaches . . . . . . . Time per Transacti on for Preprocessing the Data and Examine the Business Rules . Metrics Data Classi? cation Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anomaly Detection Time per Transaction . . . . . . . . . . . . . . . . . . . . . . . . Fraud Detection Time per Transaction . . . . . . . . . . . . . . . . . . . . . . . . . List of Tables Table 3. 1 Table 5. 1 Table 5. 2 Table 6. 1 Table 7. 1 Table 8. 1 Table 8. 2 Table 8. 3 Table 8. 4 Table 8. 5 Table 8. 6 Table 8. 7 Table 8. 8 National fraud in France categorized by transaction type . . . . . . . . . . . . . . . Communalities PCA/Factor Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . Steps for Under-Sampling Based on Clustering (SBC) . . . . . . . . . . . . . . . . . . Supported Mining Algorithms Data Mining Toolkit . . . . . . . . . . . . . . . . . . Hardware Speci? cation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . someone Classi? er Accuracy Levels Un-Preprocessed Training Set . . . . . item-by-item Classi? er Accuracy Levels Un-Sampled Preprocessed Training Set Multiple Sampling Ratios Analyzed . . . . . . . . . . . . . . . . . . . . . . . . . Multiple Sampling Ratios Analyzed . . . . . . . . . . . . . . . . . . . . . . . . . Ensemble-Based Classi? r Balanced . . . . . . . . . . . . . . . . . . . . . . . . Ensemble-Based Classi? er Maximum Fraud Detection . . . . . . . . . . . . . Ensemble-Based Classi? er with Mahalanobis Balanced Model Combination . Ensemble-Based Classi? er with Mahalanobis Maximizing Fraud Detection . . . . . . . . . . . . . . . . . . . . . . . . . 19 34 41 56 77 81 83 85 85 87 87 89 89 List of Algorithms Algorithm 1 Algorithm 2 Algorithm 3 Algorithm 4 Algorithm 5 Algorithm 6 Algorithm 7 Algorithm 8 Algorithm 9 Algorithm 10 Algorithm 11 Algorithm 12 Algorithm 13 Algorithm 14 InputSource Receive Incomming Transactions . . . . . . . . . . . . . . . . ODBCEnrich Enrich an Incomming Transaction . . . . . . . . . . . . . . . . Non-Generic C++ Primitive Operator Manual Preprocessing . . . . . . . . . Preprocessing Manual Preprocessing of Incoming Transactions . . . . . . . Functor Split Stream for Preprocessing and Rule-Based Engine . . . . . . . . Join Append Business Rules to Preprocessed Transaction . . . . . . . . . . . Join Append Business Rules to Preprocessed Transaction . . . . . . . . . . . Data Mining Toolkit Operator Decision Tree C5. 0 Classi? er . . . . . . . . . . Non-Generic C++ Primitive Operator Supervised Analysis . . . . . . . . . . Classi? cationEnsemble Constructor() . . . . . . . . . . . . . . . . . . . . . . Classi? cation Ensemble process(Tuple & tp, uint32_t port) . . . . . . . . . . Variance-Covariance Inverse Matrix use in the Mahalanobis Distance . . . Individual Account Anomaly Detection Approach . . . . . . . . . . . . . . . Voting communications protocol Mahalanobis Distance, Window-Based and Classi? er Score . . . . . . . . . . . . . . 43 44 45 46 47 47 47 56 58 58 59 68 75 75 Chapter 1 Int roduction A journey of a m miles must begin with a single step Lao Tzu If you work on fraud detection, you have a job for life. These were the words used by Professor David J.Hand1 in one of his talks to synthesize the vast research ? eld that is Fraud Detection. Indeed, this ? eld consists of multiple domains, and is continually evolving through time with immature strategies and algorithms to counter the constantly ever-changing manoeuvre employed by fraudsters2 . In this line of thought, shortly available solutions have been unable to control or mitigate the everincrease fraud- associate losses. Although thorough research has been siree, only a subatomic number of studies have led to actual Fraud Detection systems 27, and the focus is typically on novel algorithms aiming at increasing the accuracy levels.To this end, we want to look at the problem from a contrasting angle, and focus on the foundations for a real-time and multi-purpose solution, based on a technology know as Stream Computing, able to encompass these algorithms musical composition creating the possibilities for further research. We subdivide our study in three main parts. We begin with an overall understanding of the topic being discussed by de? ning the research environment, its problems and presenting the solutions truely available. In addition, we conclude this ? rst part by both specifying the structure, and outlining the objective of the research.The morsel part explores the overall course of action to bring about a Stream-based Fraud Detection solution. From this perspective, we discuss different strategies previously researched in Data Preprocessing, Data Classi? cation and Behavior-based Analysis, and tackle their combination and integration in a Stream-based application. Last but not least, we review the overall solution proposed, and examine the possibilities beseeched by the latter for further research in the ? eld of Fraud Detection in the Retail Banking Industry. Senior Research Investigator and Emeritus Professor of Mathematics at the Imperial College of London, and one of the leading researchers in the ? eld of Fraud Detection http//www3. imperial. ac. uk/people/d. j. hand link to the presentation http//videolectures. net/mmdss07_hand_stf/ 2 a person intended to deceive others (i. e. one who commits fraud) de? ned in the Glossary 1 Part I Setting the Scene Great things are not done by impulse, but by a serial publication of small things brought in concert Vincent van Gogh Fraud Detection in itself is interlinked with numerous ? lds of study, and before the plays main action, we want to set the stage. In order to bend getting off track and allowing you to improve understand the scope, contents, choices made, and requirements of the research, we divided this act in three scopes. In the ? rst, we enclose the main actors namely banks, bank customers and fraudsters. In addition, we also present the up-to-the-minute situation in the Detection and Prevention of Fraud in banks, describing the techniques being used both to counter and to commit fraudulent transactions. The second scene introduces the overall problem of fraud in the Banking Sector.It identi? es the weaknesses of the latest solutions, and quanti? es fraud losses as accurately as possible in some European countries and this based on the most recent data. We accordingly take a step further and comment on new trends, and predict possible risks banks might incur from them. Before the end of the act, we introduce the two main parts of the play, as well as how we intend to approach the problem. More precisely, we provide some speci? cs regarding the research conducted, the tools used and the plan followed to reach our conclusions. Figure 1. Lost in Translation 2 Chapter 2 Retail Banking and The State of the Art in Detection and Prevention of Fraud There are things known and there are things occult, and in between are the doors of perception Aldous Huxley Busines smen and politicians, before sealing deals or taking political decisions, are known to go through a phase of reconnaissance the military term for exploring enemy or unknown territory. just now as it is important to them, so it is for you when you are about to douse into the speci? cs of a real-time fraud detection solution.In this line of thought, it is important to grasp the context of the research to better understand the concepts discussed. To do so, we baffle this chapter with an overall view of the Retail Banking Industry, to understand both its services and IT architecture (Section 2. 1) we continue with a de? nition of fraud together with a description of the different fraud types that affect banks and how they operate (Section 2. 2) lastly, we give an overview of some of the current solutions available (Section 2. 3). 2. 1 The Retail Banking Industry To describe the banking industrys phylogenesis that started earlier than 2000 B.C. 91, deserves almost a research paper on its own. For this reason, and because we dont want to divert from the topic, we start by solely providing a simple and brief resume about the origins of the banking industry (Section 2. 1. 1). The latter is an provoke talking point that not only allows you to understand how it all started, but also to perceive the challenge of keeping a bank pro? table. Additionally, it is a good introduction to understand a more adept description of the IT architecture behind the banking services (Section 2. 1. 2). 2. 1. 1 A minuscule Walk Down Memory LaneIt all started with barter back in the time of Dravidian India, passport through Doric Greece to preRoman Italy, when a cow or an ox was the standard medium of replacement. 91 However, given the dif? culty of trading fairly, evaluating different goods with the same standards, and ? nding suitable goods for both parties involved, the invention of money inevitably developed. Indeed, the origin of the word money is pecunia in Latin, which comes from pecus, meaning cattle. Through time, money evolved in the different civilizations and became not only a symbol but also a key factor in trading.Together with the development of the art of casting, the different mediums of exchange evolved gradually from random precious metals to what we now know as currency. This developments made our forefathers the proponents of the ? rst banks for reasons that are still of applicability in todays banking system. The polity of Hammurabi in the early 2000 B. C. stated If a man gives to another silver, favorable or anything else to gumshoeguard, whatsoever he gives he shall show to witnesses, and he shall ordinate the contracts before he makes the deposits. 91 It is therefore clear that the Babylonians already placed back in their time their valuable possessions in a safe place, restrained by a trusted man. 3 Nevertheless, the real inspiration for the banking system as we know it today came from the Greeks. Unlike the Babylonians, the Gree ks didnt have a government and therefore the country was divided into independent states that were constantly any at war or in a state of unrest. 91 In these turbulent times, they found Temples to be the only safe place able to survive the test of wartime.They were seen as safe deposit vaults, marking the beginning of the functions of our current banks. Indeed, records show that the Temples not only kept money safe but also lent the funds at a reliable(a) hobby rate. In addition, even though safeguarding the money started as a service free of focal point, it soon turned into a business where small commissions were applied. The banking industry continued to evolve through time, from the commercial development of the Jews passing by the establishment of the Bank of St.George, the Bank of the Medici and the Bank of England, to the rise of the Rothschilds, and the development of banking in the land of the Vikings. 91 At this moment in time, a study bank is a combination of a dozen of businesses, such as corporate, investment and small business banking, wealth management, capital markets. One among these is the sell banking industry. 46 The retail banking industry is characterized by a particularly large number of customers and bank accounts in comparison to any other banking business, which results in a much higher number of transactions, services and crops.In addition, it relies more and more on technology due to the levels of cooperation between banks, retailers, businesses, customers leading to an ever-increasing amount of information processing requirements. In a nutshell, todays banks follow the same precept described earlier by borrowing from clients in surplus and modify to those in de? cit. This triangulation is a win-win situation for the bank and its customers the bank makes revenue from the net use up income, which is the difference between what it pays to the lending customer and what it receives from the borrower.Nevertheless, the bank cant lend all the deposits and needs to guarantee that a certain(prenominal) percentageage is kept aside to satisfy customer withdraws and requirements. 92 Even though the situation varies from bank to bank, it is noteworthy to mention that more than half of a retail banks revenue, perhaps three-quarters, comes from this intermediation role in the form of net interest income. 46 To conclude, in todays world, and afterward years of evolution, retail banks provide you with a multitude of services for which they charge fees, mainly to cover the maintenance of the infrastructure and the banks structure.These added up together account between 15% to 35% of the net interest income. 46 Among the services you can ? nd compensation services, phone banking, money transfer, cash dispensers1 , online banking, advisory services, investment and taxation services, mobile banking and many more. How does a bank ef? ciently govern, offer and maintain all these services? 2. 1. 2 The Retail Banking IT Systems Architecture Just as banking services evolved through time so did the overall back-end architecture allowing a bank to provide all the aforementioned services. This evolution was specially prominent after the unveiling by Barclays Bank f the ? rst atmosphere machine in 19672 from that moment on, banks started investing heavily in computerized systems with the name and address of automating manual processes in an effort to improve its services, overall locating in the market and cut costs. From this perspective, the IT systems of banks matured from the creation of payment systems together with the immerse of the international SWIFT profit3 in the 70s, to todays core banking system a general architecture that supports all the channel and services of a bank and where each one of them is digitalized.An overview of such general architecture is illustrated in Figure 2. 1 77. 1 acronym for Automated Teller Machine, a machine that automatically provides cash and performs oth er banking services on insertion of a special card by the account holder de? ned in the Glossary 2 http//www. personal. barclays. co. uk/PFS/A/Content/Files/barclays_events. pdf 3 Society for Worldwide Interbank Financial telecom (SWIFT) is a member-owned cooperative that operates a worldwide standardised ? nancial messaging interlocking through which the ? nancial world conducts its business operations http//www. wift. com 4 This architecture was in place in many banks some years ago, and still is in some cases, but even though it provides the clients with all the necessary banking tools, it had certain drawbacks that became visible through the modernization and improvement of services. As it is described by both Microsoft 82 and IBM 77 the as-is architecture has no true enterprise view of a customer because information is duplicated, which leads to inconsistent customer services and promotions across channels when adding new or changing current products, it takes time to bring F igure 2. As-Is Banking IT Architecture (source 77) them to the market and a signi? cant amount of changes to the core system code. This leads to a dif? culty in responding quickly to new challenges and evolving regulatory pressures. Faced with the aforementioned problems, banks had the need to change towards a more ? exible and ef? cient architecture that would allow them to play along with the ever-changing needs of the clients and of the technology. With this n mind, the major players in core banking have switched to a Service-Oriented Architecture (SOA) with the intended goal of improving growth, cut back costs, reducing operational risks, and improving customer experience. 69 94 83 77 82 As reported by Forrester in a survey in 2007 82, out of 50 European banks, 53 percent declared they were already replacing their core system while 27 percent were planning to do so and 9 percent had already completed a major transition. The same survey assessed that 56 percent of the banks a lready used SOA and 31 percent were planning to.Additionally, in Gartners 2009 report (Figure 2. 2 28), supports this strategy and believed that SOA-based architectures was increasingly being espouse and would be widely accepted in a time figure of speech of 2 to 5 years. In the latest update (2011th Edition 29), SOA is submission the Plateau of Productivity, which indiFigure 2. 2 Hype Cycle for Application Architecture, 2009 cates that the mainstream adoption is offset to take off. (source 28) With this transition to an agile banking platform with a more ? exible product de? ition built on SOA principles, banks expect to gradually simplify their business and run short more ef? cient in the long term. Indeed, the aforementioned platform which is illustrated in Figure 2. 3, is meant to provide the banks with prodigaler and easier ways to update the system and comply with changing industry regulations and conditions. Additionally, by having a holistic view of the customer-releva nt data across systems, a bank is able to better focus and analyze it with the goal to improve its customers experience by investing in more ef? cient and ? xible customer-centric offerings. Lastly, the architecture allows for integrated customer analytics and insight capabilities. In this line of thought, a stream-based real-time fraud detection solution would be easy to integrate in such an architecture, allowing the bank, as we will see later on, to broaden its services, data analysis capabilities and detect fraud in realtime. Figure 2. 3 To-Be Banking IT Reference Architecture (source 77) 5 2. 2 Fraud When one wants to get something from others illegally he can do it in two ways repulse or trick them into doing so. The ? st is better known as robbery and is unremarkably more violent and noticeable the second is known as fraud, which is more discrete and therefore preferred by fraudsters. 76 From this we can understand that fraud includes a wide variety of acts characterized b y the intent to deceive or to obtain an unearned bene? t. 30 Many audit-related agencies provide distinct insights into the de? nition of fraud that can be brie? y summarized in this way De? nition 1. Fraud consists of an illegal act (the intentional wrongdoing), the concealment of this act (often only hidden via simple means), and the deriving of a bene? (converting the deducts to cash or other valuable commodity) 30 Given this de? nition, we can further classify the known types of fraud by victim, perpetrator and contrivance 76 Employee Embezzlement Employees deceive their employers by taking community assets either like a shot or indirectly. The ? rst occurs without the participation of a third party and is characterized by an employee who discriminates company assets directly (e. g. cash, inventory, tools, etc. ). In the second, the stolen assets ? ow from the company to the perpetrator through a third party.Indeed, indirect fraud happens usually when an employee accepts bribes to allow for lower gross sales or higher purchases prices, or any other dishonest action towards the company. Vendor Fraud This type of fraud usually happens when a trafficker overcharges its products ships lower quality goods or doesnt ship any products to the purchaser even though it received the corresponding payment. Vendor fraud happens more frequently with government contracts and usually becomes public when discovered, being one of the most common in the United States. Customer Fraud Customer fraud takes place when a customer doesnt pay for the products he purchased, pays too little, gets something for nothing or gets too much for the price. All these situations occur through deception. Management Fraud Management fraud, also known as ? nancial line fraud, is committed by top management who deceptively manipulate ? nancial statements. The interest behind these actions is usually to hide the real economic situation of a company by making it look healthier than it actually is.However, for the purpose of this research, and given the fact that we are focusing on fraud perpetrated in the retail banking industry, we will mainly focus on every possible bank transaction that a customer can perform. The research will be based in debit, online banking namely electronic bill payment and giro transfers and debit shaping card transactions. Fraud that can be perpetrated against these transactions falls at heart the category known as consumer fraud. Additionally, the latter can be sub-categorized in Internet and e-commerce fraud and other (non-)internet related fraud that we will now describe in more detail. . 2. 1 Internet and E-Commerce Fraud The Internet a technology that was unknown to many of us 25 years ago and is used now by billions of people either at home, work or on-the-go. We can ? nd webpages from business home pages, to informational wikis, passing through social electronic intercommunicateing sites ? les that take the form of text, audio or video and a multitude of services and web applications. It took just 3 years for the Internet to reach over 90 million people while the television and the radio took respectively 15 and 35 years to reach 60 million people 76 This is how fast the medium through which e-commerce fraud takes place has evolved. This informational and technical revolution led to new ways for fraud to be perpetrated while techniques to avoid it have dif? culties to keep up with the pace. Today, businesses depend on the Internet to perform paperless transactions and exchange information between them they mostly use e-business connections, virtual snobby networks (VPNs1 ), and other specialized connections. 76 This type of commerce is known as e-commerce, or electronic commerce, because it takes place over electronic systems. Therefore, even if you think you are not using the Internet, any operation you make at a local branch, any withdraw you do from an ATM or any purchase you make at a local st ore with your bank card, a Network transaction takes place. 1 its a method employing encryption to provide secure access to a remote computer over the Internet de? ned in the Glossary 6Since most businesses rely on Network-based transactions and, as we will describe later on, Internet exploiters use the network more and more frequently to buy products or services, the North American Securities Administrators Association (NASAA) considers that Internet fraud has become a booming business. 76 With this in mind, there are three standpoints that need to be taken into retainer when describing in more dilate the risks involved in this category that soften banks and more importantly their customers risks lying in spite of appearance and/or orthogonal the organization.Risks at bottom Banks and Other Organizations The main risks come from within the bank. 76 Indeed, a perpetrator with inside access has knowledge regarding the environment, the security mechanisms and how to bypass them. Additionally, any employee with access to the organizations network has automatically bypassed ? rewalls and security checks making it easier to in? ltrate systems, steal information or data and cause damage to the bank. From this perspective, the most common example is the superuser access that most IT-related employees (e. g. rogrammers, technical support, network administrators or project managers) have within the companys infrastructure and database systems. 76 In one survey, more than a third of network administrators admitted to snooping into human resource records, layoff lists, and customer databases. 76 A related survey found that 88 percent of administrators would take sensitive data if they were ? red, and 33 percent said they would take company rallying cry lists. 76 Even if a perpetrator does not have personal access to the targeted system and information, there are techniques that he can use to get at them indirectly, i. . via a person of interest Snif? ng, also kno wn as Eavesdropping Snif? ng is the logging, ? ltering, and viewing of information that passes along a network connection. Applications are easily and available for free on the Internet, Wireshark1 and tcpdump2 that allow network administrators to troubleshoot any possible problem in the network. Nevertheless, these applications can as easily be used by hackers to gather information from unencrypted communications. 76 A good example is the usage of unencrypted e-mail access protocols like Post Of? ce Protocol 3 (POP3) or the Internet Message Access Protocol (IMAP) instead of other more secured ones. Since e-mail clients check messages every span of minutes, hackers have numerous opportunities to intercept personal information. 76 A user could in addition encrypt the body of the email by using fixate/Multipurpose Internet Mail Extensions (S/MIME) or OpenPGP in order to avoid that sensitive information passes through the network in plain text.Even though security experts have succes sfully managed to encrypt emails, the reason behind this want of security is that they have failed to take into consideration the needs of the end-user namely, the ability to from time to time encrypt an email without much trouble at all. 113 Wartrapping Wartrapping happens when hackers set up free access points to the Internet through their laptops in speci? c locations like airports or inside a companys headquarters. Users, unmindful(predicate) that the wi? passes through a hackers computer, connect to the latter and sweep the Internet as if they had a secured connection.When logging their internet banking services and playing transactions, or simply access their emails, the hacker can see the bits and bytes of every communication passing through any laptop in the clear. In this line of thought, hackers can get caught in their own web as companies are also using what they call honeypot traps. The latter is an information system resource, like a computer, data, or a network site (e. g. wireless entry), whose purpose is not only to divert approach shoters and hackers away from minute resources, but also to serve as a tool to study their methods. 1 These systems are placed strategically so to look like part of the companys internal infrastructure even though they are actually isolated and monitored by administrators of the organization. One of the most widely used tools is honeyd3 . 89 1 2 3 http//www. wireshark. org/ http//www. tcpdump. org/ http//www. honeyd. org/ 7 Passwords are the Achilles reheel of many systems since its creation is left to the end user who keeps them simple and within his or her preferences and life experiences (e. g. birthdays, family names, favorite locations or brands).In addition, users tend to re-use the same password for different purposes in order to avoid having to remember different ones, which leads perpetrators to gain access to different services and accounts with a single password from the person. In addition, anot her source of threats are the laptops and mobile devices that many employees take with them outside the companys protected environment. While in these unsecured contexts, the devices are exposed to viruses, spyware, and other threats that might compromise again the integrity of other organizations system once these computers are plugged in the network.Viruses, trojans and worms are able to enter the protected environment without having to go through ? rewalls and security checks, making it easier to in? ltrate key information systems and bypass apology mechanism. Risks Outside Banks and Other Organizations The Internet not only became a source of services to users and companies but also a rich medium for hackers to gain access to personal systems. Indeed, when performing attacks, hackers are relatively protected because they cross international boundaries which puts them under a different jurisdiction than the victim of the attack and are mostly anonymous making tracking dif? ul t. Therefore, the Internet became the defacto technological medium to perform attacks and there are numerous ways of doing so Trojan Horses A trojan horse is a program intentional to breach the security of a computer system and that has both a desirable and a hidden, usually malicious, outcome. 86 These programs can be embedded in a bank users computer when he views or opens an infected email, visits or downloads a ? le from an unsecured website or even when visiting a legitimate website that has been infected by a trojan. 85 From this perspective, a good example is the man-in-the-browser (MitB) attack, represented in Figure 2. , which uses trojan horses to gear up extensions or plugins in the browser that are used to deceive a bank customer Whenever a speci? c webpage is loaded, the Trojan will ? lter it based on a target list (usually online banking pages). The trojan extension waits until the user logs into his bank and starts to transfer money. When a transaction is performed , the plug-in extracts data from all the ? elds and modi? es the amount and recipient according to the hackers preferences through the roll object model (DOM1 ) larboard, and resubmits the form to the server.The latter will not be able to identify whether the values were written by the customer or not and performs the Figure 2. 4 MitB Operation (source2 ) transaction as requested. 85 ATM Attack Techniques An Automated Teller Machine (ATM), is a computerized device that allows customers of a ? nancial institution to perform most banking transactions and check their account status without the help of a clerk. The device identi? es the customers with the help of a plastic bank card, which contains a magnetic stripe with the customers information, together with a personal identi? ation number (PIN) code. 2 ATMs are attractive to fraudsters because they are a direct link to customers information and money, and there are security pitfalls with their current architecture 2 the way data is encoded in the magnetic media makes it easily companionable if a hacker invests some money to buy the easyto-be-found equipment, and time to decrypt and duplicate the contents in addition, with a four 1 An interface that lets software programs access and update the content, structure, and style of documents, including webpages de? ed in the Glossary 2 www. cronto. com, blog. cronto. com/index. php? title=2fa_is_dead 8 digit PIN, not only will one in every 10. 000 users have the same number but it also allows brute force attacks to discover the combination. Not to mention the possible visible attacks on ATMs which cannot be considered as fraud (see De? nition 1), there are a couple of ways fraudsters steal money from bank customers 2 1. Skimming Attack skimming is the most popular approach in ATMs and consists in using devices named skimmers that capture the data from the magnetic strip.These devices can be plugged in an ATMs factory-installed card reader and allows for downloa d of all personal information stored on the card. In addition, to obtain the PIN code fraudsters use either shoulder-sur? ng and hidden video cameras, or distraction techniques while the customer uses the ATM. 2 Sometimes fraudsters take a step further and urinate their own fake teller machines to deceive bank customers this is considered to be a spoo? ng attack that we will describe in more details below. 39 2.Card Trapping this tech