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Updated November 17th Related Posts Link to automotive form, business form

Discover how token-based authentication works, its types, and why businesses trust it to secure sensitive data.

Discover how data and analytics can enhance deposit growth strategies, improve customer engagement, and drive financial wellness for banks and credit unions.

By: Andrew Gulledge I hate this question. There are several reasons why the concept of an “average fraud rate” is elusive at best, and meaningless or misleading at worst. Natural fraud rate versus strategy fraud rate The natural fraud rate is the number of fraudulent attempts divided by overall attempts in a given period. Many companies don’t know their natural fraud rate, simply because in order to measure it accurately, you need to let every single customer pass authentication regardless of fraud risk. And most folks aren’t willing to take that kind of fraud exposure for the sake of empirical purity. What most people do see, however, is their strategy fraud rate—that is, the fraud rate of approved customers after using some fraud prevention strategy. Obviously, if your fraud model offers any fraud detection at all, then your strategy fraud rate will be somewhat lower than your natural fraud rate. And since there are as many fraud prevention strategies as the day is long, the concept of an “average fraud rate” breaks down somewhat. How do you count frauds? You can count frauds in terms of dollar loss or raw units. A dollar-based approach might be more appropriate when estimating the ROI of your overall authentication strategy. A unit-based approach might be more appropriate when considering the impact on victimized consumers, and the subsequent impact on your brand. If using the unit-based approach, you can count frauds in terms of raw transactions or unique consumers. If one fraudster is able to get through your risk management strategy by coming through the system five times, then the consumer-based fraud rate might be more appropriate. In this example a transaction-based fraud rate would overrepresent this fraudster by a factor of five. Any fraud models based on solely transactional fraud tags would thus be biased towards the fraudsters that game the system through repeat usage. Clearly, however, different folks count frauds differently. Therefore, the concept of an “average fraud rate” breaks down further, simply based on what makes up the numerator and the denominator. Different industries. Different populations. Different uses. Our authentication tools are used by companies from various industries. Would you expect the fraud rate of a utility company to be comparable to that of a money transfer business?  What about online lending versus DDA account opening? Furthermore, different companies use different fraud prevention strategies with different risk buckets within their own portfolios. One company might put every customer at account opening through a knowledge based authentication session, while another might only bother asking the riskier customers a set of out of wallet questions. Some companies use authentication tools in the middle of the customer lifecycle, while others employ fraud detection strategies at account opening only. All of these permutations further complicate the notion of an “average fraud rate.” Different decisioning strategies Companies use an array of basic strategies governing their overall approach to fraud prevention. Some people hard decline while others refer to a manual review queue.  Some people use a behind-the-scenes fraud risk score; others use knowledge based authentication questions; plenty of people use both. Some people use decision overrides that will auto-fail a transaction when certain conditions are met. Some people use question weighting, use limits, and session timeout thresholds. Some people use all of the out of wallet questions; others use only a handful. There is a near infinite possibility of configuration settings even for the same authentication tools from the same vendors, which further muddies the waters in regards to an “average fraud rate.” My next post will beat this thing to death a bit more.

A recent article in the USA Today titled, “Jobs rebound will be slow”*, outlines state-by-state forecasts for the United States, as released by Moody’s Economy.com. Although the national forecasted increase, 0.9%, reflects the expectation that unemployment will remain an issue throughout 2011, the state-level detail possesses interesting variances that should be further considered by lenders in determining their marketing and acquisition strategies. What I find intriguing, is that Moody’s forecasts job growth for several states that since the beginning of the housing decline have been the hot-spots for mortgage default and high delinquency rates. Moody’s projects job growth for Florida (+2.5%), Nevada (+1.5%), and California (+0.5%) – the so called “sand states” – with comparable growth rates to states like Texas (+2.5%) and North Carolina (+1.3%), which have not experienced the same notoriety for increased risk levels and delinquency. Should this growth transpire, then these states that have been the center of credit risk in recent years will soon become centers of opportunity for lenders, as increased employment should result in decreasing delinquency rates, improved repayment habits, and a generally more creditworthy consumer population. This shift is important, since any economic recovery will start with jobs growth, leading to increased lending, which will drive housing and a broader economic growth. As I noted above, the Moody’s forecast implies that lenders who are looking to drive growth may find that profitable portfolio segments exist in some of what appear to be the unlikeliest places. __________________ *http://www.usatoday.com/money/economy/2009-02-06-new-jobs-growth-graphic_N.htm

By: Margarita Lim It’s the holiday season and a festive time of year. Colorful Christmas lights and decorations, holiday songs, all of these things contribute to the celebratory atmosphere which causes many people to let their guards down. Unfortunately, fraudsters and other criminals take advantage of the prevailing goodwill and can help make one of the busiest shopping times of the year, a miserable one for their victims. It’s not a surprise that articles and news stories are released advising shoppers on how to continue enjoying their holiday season by not being victims of identity theft or other known fraud activities. Consumers can get tips from the Federal Trade Commission and other websites to prevent or minimize exposure to identity theft but I think key ones include: • If using credit cards for purchases, write ‘Check Photo ID’ on the back of your credit card. • Be very protective about disclosing personal information, especially Social Security Numbers. Did you know that it only takes one piece of personal information about you for a thief to steal your identity? • If shopping online, only make purchases from recognizable online retailers and websites. Many fraudsters will create fake websites that offer goods for sale in order to collect personal and credit information that can then be used to make fraudulent purchases. If consumers need to be careful this holiday season, businesses should also be vigilant. Fraudsters cause businesses like banks, retailers and credit card companies to lose millions of dollars that ultimately get passed on to their customers. Companies need to make sure they have tools in place to minimize these fraud losses. I’ve mentioned this in a previous post but Experian supports Identity Theft Prevention Programs by offering highly accurate consumer identity verification services. Our consumer authentication and fraud prevention product, Precise ID, and our knowledge based authentication product, Knowledge IQ, are highly respected in the marketplace for their reliability, quality and accuracy. Implementing either of these products would go a long way in preventing fraud this holiday season.