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Fraud Detection & Prevention(a subtopic of Applications)
Good Places to StartMimicking fraudsters - If your card use has been queried, it's probably because more banks are now using artificial intelligence software to try to detect fraud. By Ken Young. The Guardian (September 9, 2004). "Credit card fraud losses in the UK fell for the first time in nearly a decade last year, by more than 5% to 402.4m [British pounds], according to research by the Association of Payment Clearing Services (Apacs). The fall has put a spotlight on the increasing use of neural networks that have the ability to detect fraudulent behaviour by analysing transactions and alerting staff to suspicious activity. As commercial applications of research into artificial intelligence, these systems give the impression of mimicking human abilities for recognising unusual activity. Karina Purang, a financial analyst at Datamonitor in London, says the use of neural networks is growing: 'These systems are very important to banks trying to reduce fraud, and are becoming standard across the card industry to detect unusual spending patterns.' She says Barclays reported that after installing Fair Isaac's Falcon Fraud Manager system in 1997, fraud was reduced by 30% by 2003. The bank attributed this mainly to the new system. ... Nick Sandall, head of retail banking at Deloitte, says that banks also use other technologies. 'The artificial intelligence community is constantly bringing us new solutions. ...'"
Computer programs help flag insurance fraud before payment. By Julie Appleby. USA Today (November 7, 2006). "Computer sleuths trying to stop health care fraud say they have a new weapon: computer programs that can flag potential fraud even before medical claims are paid. ... Insurer Aetna says its new computer software helped it stop $89 million in payments before they reached medical providers last year. That compares with the $15 million in fraud repayments it was able to collect after the fact. ... While the software systems may differ, their main effort is to spot medical providers who vary from the norm. 'Pattern recognition is a growing field in health fraud detection,' says Malcolm Sparrow, a professor at Harvard's John F. Kennedy School of Government and author of License to Steal: How Fraud Bleeds America's Health Care System." Electronic Brain Helps Cut Credit Card Fraud. By Wendy Kaufman. Radio broadcast of NPR's Morning Edition (July 18, 2005). Audio excerpt: "[Renee Montagne, host] On Mondays, our business report focuses on technology. Today, how an electronic brain is helping to cut credit card fraud. We have been hearing a lot about identity theft lately, so it's a bit surprising to learn that credit card fraud is actually declining. ... [W.K.] Nearly all transactions for Visa, MasterCard, American Express and others are scrutinized electronically before they're approved. David Robertson, publisher of the credit industry's Nilson Report, explains. [D.R.] While it's going through their system for authorization, it's also being checked against information about your previous spending. [W.K.] So if you use your card in Seattle in the morning and someone tries to use the same account an hour later in New York, the security system will send up a big red flag. Credit card companies use what is essentially an electronic brain, aided by a form of artificial intelligence known as neural networks. The brain keeps track of every purchase you make and sorts them into patterns and categories and compares your spending habits to others and to credit card activity linked to fraudsters. Then it makes predictions about whether a transaction is legitimate or not." E-Europe awards. The Guardian (November 23, 2005). "The eEurope awards, organised by the European Institute of Public Administration, recognise innovaton in e-government and healthcare in the EU and Efta countries. We pick out some of the 52 finalists. ... Fighting fraud (Italy): Italian customs officers are fighting fraud with an artificial intelligence system called Falstaff: a fully automated logical system against forgery and fraud."
Smart Tools - Companies in health care, finance, and retailing are using artificial-intelligence systems to filter huge amounts of data and identify suspicious transactions. By Otis Port, with Michael Arndt and John Carey. Business Week's 2003 edition of The BusinessWeek50. "Banks, brokerages, and insurance companies have been relying on various AI tools for two decades. One variety, called a neural network, has become the standard for detecting credit-card fraud. Since 1992, neural nets have slashed such incidents by 70% or more...." Future Route releases AI-based fraud detection product. finextra news (August 19, 2004). "UK-based Future Route is releasing a new card fraud detection system, iHex, based on artificial intelligence technology developed at Oxford University's computing laboratories for bio-informatics. The product has been designed for use by financial services firms, government agencies and corporations. IHex detects fraud using Inductive Logic Programming (ILP) techniques - an artificially intelligent method of identifying fraud patterns and anomalies. The vendor says unlike many other pattern detection products, the system automatically generates and continuously enhances underlying rules."
Credit Card Companies Turn To Artificial Intelligence. By Margaret Webb Pressler. The Washington Post / available from the Tampa Tribune (September 29, 2002). "With billions of dollars at stake, and more clever crooks, credit card companies have become very smart about protecting themselves with astonishingly sophisticated network computers and software programs. 'We're at a level whereby we can understand with artificial intelligence ... the potentially fraudulent transactions,' said Raf Sorrentino, vice president of risk management for First Data Corp., one of the biggest providers of credit card processing and payment services. Credit card fraud costs the industry about a billion dollars a year, or 7 cents out of every $100 spent on plastic. But that is down significantly from its peak about a decade ago, Sorrentino says, in large part because of powerful technology that can recognize unusual spending patterns." AI Approaches to Fraud Detection and Risk Management. By Tom Fawcett, Ira Haimowitz, Foster Provost, and Salvatore Stolfo. AI Magazine 19(2): Summer 1998, 107-108. "The 1997 AAAI Workshop on AI Approaches to Fraud Detection and Risk Management brought together over 50 researchers and practitioners to discuss problems of fraud detection, computer intrusion detection, and risk scoring. This article presents highlights, including discussions of problematic issues that are common to these application domains, and proposed solutions that apply a variety of AI techniques." Computers try to outthink terrorists. By Bruce V. Bigelow. The San Diego Union-Tribune (January 13, 2002). Also available from UC San Diego. "Neural networking techniques begin by analyzing a database, and using systematic methods to identify characteristic features, trends and patterns within the data. Such features can then be used to analyze fresh data and to predict whether or not it 'fits' the model. In cases of credit card fraud, for example, Gutschow said a stolen credit card often is used to make a self-service purchase at a gas station (to determine if the card is still active) immediately before it's used to buy jewelry or for some other major purchase. Such illicit transaction patterns really stand out when the system has been 'trained' to recognize the legitimate cardholder's usage pattern. An irregular transaction prompts an alert, which is transmitted instantly to the sales clerk handling the purchase." Virtual lies face foolproof software. By Fiona Harvey. Financial Times (January 21, 2002). "SAS Institute, which makes fraud-detection systems for banks and phone companies, will on Monday announce a product that can sift through e-mails and other electronic text to catch elusive nuances such as tone. 'The patterns in people's language change when they are uncertain or lying,' says Peter Dorrington, business solutions manager at SAS. 'We can compare basic patterns in words and grammatical structures versus benchmarks to detect likely lies.' ... Another software company, SER Solutions, claims it has used its software to prove that Shakespeare was indeed the author of one of his disputed plays, Henry VIII. SER uses neural network algorithms, which mimic the working of the human brain, to make connections between words."
Smart Methods to Spot Fraud. By Michelle Finley. WIRED News (April 3, 2000). "Engineers are presently developing hybrid intelligent systems that incorporate all of the tools developed during the first wave of AI technology. ... The London Stock Exchange uses MonITARS (Monitoring Insider Trading and Regulatory Surveillance), developed by Searchspace. ... Searchspace calls its hybrid technology iTM, or intelligent transaction monitoring. ITM differs from the standard monitoring tools, Tellick said, because it can learn. It can understand business practices based on its analysis of transaction activity, using more flexible reasoning logic than the traditional on-off, yes-no type of processing." Computers Are Learning The Business - Advances in computer processing power open the way for wider use of so-called artificial intelligence, at the same time that the self-serve aspect of online processes has increased the need for systems that "think." By John Hackett. Bank Technology News. (April 2001). "If AI did nothing else, the fraud detection alone makes it a worthwhile investment for credit card companies, insurance providers, and financial lenders." Phone Friend. Software agents can use your pattern of mobile phone use to foil thieves. By Duncan Graham-Rowe. New Scientist Magazine (January 31, 2001). "The way you use your mobile phone could help to foil potential thieves. So say software engineers who have developed a fraud detection system that uses artificial intelligence to monitor your phone usage, making sure you're the rightful owner. ... The system uses pattern recognition software built into intelligent agents - called sentinels - that assemble behaviour profiles of subscribers on a network." (A related article appears in New Scientist's special section about AI.)
Readings OnlineMonitoring NASDAQ for Potential Insider Trading and Fraud. AAAI Press Release (July 30, 2003). "NASD has developed an intelligent surveillance application -- the Securities Observation, News Analysis and Regulation (SONAR) system -- that automatically monitors the NASDAQ, OTC, and futures markets for suspicious patterns. ... SONAR includes several AI techniques, such as data mining, natural language processing for text mining, intelligent software agents, rule-based inference, and knowledge-based data representation." The NASD Regulation Advanced-Detection System (ADS). By J. Dale Kirkland, Ted E. Senator, James J. Hayden, Tomasz Dybala, Henry G. Goldberg, and Ping Shyr. AI Magazine 20(1): Spring 1999, 55-67. "ADS makes use of a variety of AI techniques, including visualization, pattern recognition, and data mining, in support of the activities of regulatory analysis, alert and pattern detection, and knowledge discovery." Inspired by immunity - By developing programs that mimic some of the functions of the immune system, computer scientists are tackling problems from fighting fraud to controlling robots. By Erica Klarreich. Nature 415, 468 - 470 (January 31, 2002). NASD Regulation's Advanced Detection System Wins Awards From Smithsonian, Data Warehousing Institute, and Artificial Intelligence Association. Press release from the National Association of Securities Dealers, Inc. (NASD¨). September 15, 1998. "ASD Regulation, Inc. announced today that its Advanced Detection System (ADS) has recently won three prestigious awards in recognition of its superior technology and ability to help deter fraud and guard marketplace integrity. ... ADS is a market surveillance, data mining, and fraud/violative behavior detection software package that monitors Nasdaq¨ for potential late-trade reporting, market integrity, and best execution violations. The system combines data visualization, time sequence pattern matching, rule-pattern matching, and data mining in a single application that looks for patterns or practices of potentially violative behavior." The Hidden Truth - Data analysis can be a strategic weapon in your company's management and control of fraud. By Girish Keshav Palshikar. Intelligent Enterprise Magazine (May 28, 2002). "I've already remarked that fraud management is a knowledge-intensive activity. Therefore, applications of knowledge-based techniques from AI are a natural idea. Important AI techniques used for fraud management include: Data mining ... Expert systems ... Pattern recognition ... Machine learning ... Neural networks ... Other techniques such as Bayesian networks, decision theory, and sequence matching are also used for fraud detection." Signs of Fraud Go Beyond Signature - Credit Card Companies Use Artificial Intelligence to Thwart Thieves. By Margaret Webb Pressler. The Washington Post (July 21, 2002; Page H05). "As it turns out, however, credit card companies no longer rely on retail clerks to catch the crooks. ... 'We're at a level whereby we can understand with artificial intelligence . . . the potentially fraudulent transactions,' said Raf Sorrentino, vice president of risk management for First Data Corp., one of the country's biggest providers of credit card processing and payment services. Credit card fraud costs the industry about a billion dollars a year, or 7 cents out of every $100 dollars spent on plastic. But that is down significantly from its peak about a decade ago, Sorrentino says, in large part because of the powerful technology that can recognize unusual spending patterns." The Financial Crimes Enforcement Network AI System (FAIS). Identifying Potential Money Laundering from Reports of Large Cash Transactions. By Ted E. Senator, Henry G. Goldberg, Jerry Wooton, Matthew A. Cottini, A. F. Umar Khan, Christina D. Klinger, Winston M. Llamas, Michael P. Marrone, and Raphael W. H. Wong. AI Magazine 16(4): Winter 1995, 21-39. "The Financial Crimes Enforcement Network (FIN-CEN) AI system (FAIS) links and evaluates reports of large cash transactions to identify potential money laundering. The objective of FAIS is to discover previously unknown, potentially high-value leads for possible investigation. FAIS integrates intelligent human and software agents in a cooperative discovery task on a very large data space. It is a complex system incorporating several aspects of AI technology, including rule-based reasoning and a blackboard. FAIS consists of an underlying database (that functions as a black-board), a graphic user interface, and several preprocessing and analysis modules. FAIS has been in operation at FINCEN since March 1993; a dedicated group of analysts process approximately 200,000 transactions a week, during which time over 400 investigative support reports corresponding to over $1 billion in potential laundered funds were developed." AI Technologies to Defeat Identity Theft Vulnerabilities. By Latanya Sweeney, The Laboratory for International Data Privacy (also known as the "Data Privacy Lab") at Carnegie Mellon University. AAAI Spring Symposium, AI Technologies for Homeland Security, 2005. VISA EU Launches New Advanced Fraud Detection Tool. System to deliver significant increase in fraud detection rates. VISA EU press release (December 29, 2003). "Visa Intelligent Scoring of Risk (VISOR) is an advanced neural network system that scrutinises card transactions to deliver a highly accurate risk score by analysing the spending behaviour of each cardholder along with the profile of each merchant."
Related Web SitesArtificial Intelligence and Fraud Detection. A very informative site maintained by Jorn Dinkla. Fraud Detection Solutions from KD Nuggets. An exciting collection of intelligent products that are available to combat fraud. Related Pages
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