By Revathi Subramanian
Learn how advances in know-how may help scale back financial institution fraud
Fraud prevention experts are grappling with ever-mounting amounts of knowledge, yet in modern-day risky advertisement atmosphere, taking note of that information is extra very important than ever. Bank Fraud presents a frank dialogue of the attitudes, options, and—most importantly—the know-how that experts might want to wrestle fraud.
Fraudulent job could have elevated through the years, yet so has the sector of knowledge technological know-how and the consequences that may be completed via making use of definitely the right ideas, an important device at the present time for monetary associations to guard themselves and their shoppers. This source is helping execs within the monetary companies utilize facts intelligence and uncovers the acceptable how to strengthening defenses opposed to fraudulent habit. This in-depth therapy of the subject starts with a short background of fraud detection in banking and definitions of key phrases, then discusses the advantages of know-how, information sharing, and research, besides different in-depth info, including:
- The demanding situations of fraud detection in a monetary companies environment
- The use of facts, together with powerful how one can degree losses in step with account and ROI by means of product/initiative
- The Ten Commandments for tackling fraud and how you can construct a good version for fraud management
Bank Fraud bargains a compelling narrative that finally urges safety and fraud prevention pros to utilize the information they've got so painstakingly collected. Such pros can not enable their most vital highbrow asset—data—go to waste. This e-book indicates you simply the way to leverage facts and the main up to date instruments, applied sciences, and strategies to thwart fraud at each turn.
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Extra resources for Bank fraud : using technology to combat losses
The Advent of Nonlinear Statistical Models Simple statistical models such as linear and logistic regression models are much better at understanding and generalizing fraud versus nonfraud behavior compared to expert-written rules. All of the variables 12 ▸ BANK FRAUD: THEN AND NOW that might have an impact on detecting fraud can be used as variables in the models. With respect to interactions between the different variables in the model, as long as the experts are able to figure out the interactions and feed them as variables into the model, the models are capable of understanding the behavior and its relationship to fraud.
When a customer used the card and made a purchase, the bill was sent to the bank. The bank acted as the intermediary, paid the merchant, and then got reimbursed by the cardholder. This card restricted the purchases to just local purchases. In 1951, New York’s Franklin National Bank issued a card for loan customers, and it could only be used by customers of the bank. This was followed by Diners Club cards. These were small cardboard cards and mainly used for travel and entertainment. Diners Club had 20,000 or so customers within a couple of years.
Third-party fraud is where the fraud is committed clearly by a third party, not the two parties involved in a transaction. In first-party fraud, the perpetrator of the fraud is the one who has the relationship with the bank. The fraudster in this case goes to great lengths to prevent the banks from knowing that fraud is happening. In this case, there is no reporting of the fraud by the customer. Until the bank figures out that fraud is going on, there is no data that can be collected. Also, fraud could go on for quite a while and some of it might never be known.
Bank fraud : using technology to combat losses by Revathi Subramanian