Fraud & Identity Management

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.

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.

The U.S. Senate passed legislation recently that would exempt certain businesses from complying with the Red Flags Rule.  Sponsored by Senator John Thune (R-SD), the bill (S. 3987) creates an exception to the Red Flags Rule for businesses that do not advance funds to a customer. The bill would, for example, redefine the term “creditor” as currently described under the Red Flags Rule guidelines, to apply only to those businesses who advance funds to, or on behalf of, a customer, and based upon an obligation to repay those advanced funds.  The legislation also still provides the Federal Trade Commission with authority to require certain organizations to comply with the Red Flags Rule. The legislation now moves to the U.S. House of Representatives, where the chamber must approve the bill before the end of the year in order for the bill to become law.  This may alleviate many businesses in industries such as law practices, healthcare providers (particularly solo practitioners), and perhaps some service providers in telecommunications and utilities.  However, it is likely that many businesses in the utilities space will still fall under Red Flags Rule enforcement given their accessing of consumer credit profiles in many of their application processing procedures.  Again, one has to wonder what the original intent of the Red Flags Rule was.  If it was to protect consumers from identity theft and other fraud schemes via a robust identity theft prevention program, then vastly narrowing the businesses under which potential enforcement applies seems counter-productive.  The advancement of funds or not doesn’t necessarily add to or reduce risk of fraud, as much as the actual obtainment of accounts and services with identity information…regardless of industry.  More to follow…

By: Margarita Lim Recently, the Social Security Administration (SSA) announced that it will change how Social Security numbers (SSN) will be issued, with a move toward a random method of assigning SSNs. Social Security numbers are historically 9 digits in length, and are comprised of a three-digit number that represents a geographic area, a two-digit number referred to as a Group number and a four digit serial number.You can go to http://www.ssa.gov/employer/randomization.html to learn more about this procedural change, but in summary, the random assignment of SSNs will affect: • The geographic significance of the first three digits of the SSN because it will no longer uniquely represent specific states • The correlation of the Group number (the fourth and fifth digits of the SSN) to an issuance date range. What does this mean? It means that if you’re a business or agency that uses any type of authentication product in order to minimize fraud losses, one of the components used to verify a consumer’s identity – Social Security number, will no longer be validated with respect to state and date.   However, one of the main advantages of utilizing a risk-based approach to authentication is the reduction in over-reliance on one identity element validation result.  Validation of SSN issuance date and state, while useful in determining certain levels of risk, is but one of many attributes and conditions utilized in detailed results, robust analytics, and risk-based decisioning.  It can also be argued that the randomization of SSN issuance, while somewhat impacting the intelligence we can glean from a specific number, may also prove to be beneficial to consumer protection and the overall confidence in the SSN issuance process.

As the December 31st deadline approaches for FTC enforcement of the Red Flags Rule, we still seem quite a ways off from getting out from under the cloud of confusion and debate related to the definition of ‘creditor’ under the statutory provisions. For example, the Thune-Begich amendment to “amend the Fair Credit Reporting Act with respect to the applicability of identity theft guidelines to creditors” looks to greatly narrow the definition of creditor under the Rule, and therefore narrow the universe of businesses and institutions covered by the Red Flags Rule. The question remains, and will remain far past the December 31 enforcement deadline, as to how narrow the ‘creditor’ universe gets. Will this amendment be effective in excluding those types of entities generally not in the business of extending credit (such as physicians, lawyers, and other service providers) even if they do provide service in advance of payment collection or billing? Will this amendment exclude more broadly, for example ‘buy-here, pay-here’ auto dealers who don’t extend credit or furnish data to a credit reporting agency? Finally, is this the tip of an iceberg in which more entities opt out of the requirement for robust and effective identity theft prevention programs? So one has to ask if the original Red Flags Rule intent to “require many businesses and organizations to implement a written Identity Theft Prevention Program designed to detect the warning signs – or “red flags” – of identity theft in their day-to-day operations, take steps to prevent the crime, and mitigate the damage it inflicts” still holds true? Or is the idea of protecting consumer identities only a good one when it is convenient? It doesn’t appear to be linked with fraud risk as healthcare fraud, for example, is of major concern to most practitioners and service providers in that particular industry. Lastly, from an efficiency perspective, this debate would likely have been better timed at the drafting of the Red Flags Rule, and prior to the implementation of Red Flags programs across industries that may be ultimately excluded.

As E-Government customer demand and opportunity increases, so too will regulatory requirements and associated guidance become more standardized and uniformly adopted.  Regardless of credentialing techniques and ongoing access management, all enrollment processes must continue to be founded in accurate and, most importantly, predictive risk-based authentication. Such authentication tools must be able to evolve as new technologies and data assets become available, as compliance requirements and guidance become more defined, and as specific fraud threats align with various access channels and unique customer segments. A risk-based fraud detection system allows institutions to make customer relationship and transactional decisions based not on a handful of rules or conditions in isolation, but on a holistic view of a customer’s identity and predicted likelihood of associated identity theft.  To implement efficient and appropriate risk-based authentication procedures, the incorporation of comprehensive and broadly categorized data assets must be combined with targeted analytics and consistent decisioning policies to achieve a measurably effective balance between fraud detection and positive identity proofing results. The inherent value of a risk-based approach to authentication lies in the ability to strike such a balance not only in a current environment, but as that environment shifts as do its underlying forces. The National Institute of Standards and Technology, in special publication 800-63, defines electronic authentication (E-authentication) as “the process of establishing confidence in user identities electronically presented to an information system”. Since, as stated in publication 800-63, “individuals are enrolled and undergo an identity proofing process in which their identity is bound to an authentication secret, called a token”, it is imperative that identity proofing is founded in an approach that generates confidence in the authentication process. Experian believes that a risk-based approach that can separate valid from invalid identities using a combination of data and proven quantitative techniques is best. As “individuals are remotely authenticated to systems and applications over an open network, using a token in an authentication protocol”, enrollment processes that drive ultimate provision of tokens must be implemented with an eye towards identity risk, and not simply a series of checks against one or more third party data assets. If the “keys to the kingdom” are housed in the ongoing use of tokens provided by Credentials Service Providers (CRA) and binding credentials to that token, trusted Registration Authorities (RA) must employ highly predictive identity proofing techniques designed to segment true, low-risk identities from identities that may have been manipulated, fabricated, or in true-form are subject to fraudulent use, abuse or victimization. Many compliance-oriented authentication requirements (ex. USA PATRIOT Act, FACTA Red Flags Rule) and resultant processes hinge upon identity element (ex. name, address, Social Security number, phone number) validation and verification checks. Without minimizing the importance of performing such checks, the purpose of a more risk-based approach to authentication is to leverage other data sources and quantitative techniques to further assess the probability of fraudulent behavior.

Experian recently contributed to a TSYS whitepaper focused on the various threats associated with first party fraud. I think the paper does a good job at summarizing the problem, and points out some very important strategies that can be employed to help both prevent first party fraud losses and detect those already in an institution’s active and collections account populations. I’d urge you to have a look at this paper as you begin asking the right questions within your own organization. Watch here The bad news is that first party fraud may currently account for up to 20 percent of credit charge-offs. The good news is that scoring models (using a combination of credit attributes and identity element analysis) targeted at various first party fraud schemes such as Bust Out, Never Pay, and even Synthetic Identity are quite effective in all phases of the customer lifecycle. Appropriate implementation of these models, usually involving coordinated decisioning strategies across both fraud and credit policies, can stem many losses either at account acquisition, or at least early enough in an account management stage, to substantially reduce average fraud balances. The key is to prevent these accounts from ending up in collections queues where they’ll never have any chance of actually being collected upon. A traditional customer information program and identity theft prevention program (associated, for example with the Red Flags Rule) will often fail to identify first party fraud, as these are founded in identity element verification and validation, checks that often ‘pass’ when applied to first party fraudsters.

By: Kennis Wong In the last entry, I mentioned that consumers’ participation in protecting their own identity information is an important aspect of an identity theft prevention program to minimize fraud loss.  Large financial institutions are starting to take charge in educating their customers, but others are having a hard time investing in such initiatives. I do understand that it is difficult to establish a direct linkage of revenue and positive return on investment for this type of activities. Business may view customer education of identity protection as a public service but not a necessity. After all, if my customer loses his identity information, it doesn’t necessarily mean that identity fraud will happen to my very own organization. But educating customers about identity protection and fraud trends can be a marketing tool and can increase customer loyalty, in additions to actual fraud prevention. Although consumers may not be aware of all the precautions they can take to protect their identity, undoubtedly identity theft is a hot topic in the media today. If there are two banks providing about the same service, but one of them goes an extra mile to provide me education on preventing identity theft, I would go with that bank. Also, as a financial institution, if my customers understand identity protection more, they would understand why I am putting some procedure in place and would be glad to comply with them. For example, they would be more patient when spending another minute in answering knowledge-based authentication questions, so that for their own protection, the bank can assure they are the true identity owners. Consumers can also actively monitor their credit report, whether through the bank or through other third party vendors. When consumers receive fraud alert from activities that could be a result of identity theft, they can actively contact the financial institutions about the situation. The sooner the identity fraud is discovered, the better off for both the consumers and the businesses.

By: Kennis Wong As a fraud management professional, naturally I am surrounded by fraud prevention topics and other professionals in the field all the time.  Financial, ecommerce, retail, telecommunication, government and other organizations are used to talking about performance, scoring models, ROI, false-positives, operational efficiency, customer satisfaction trade-off, loss provisioning, decisioning strategy or any other sophisticated measures when it comes to fraud management.  But when I bring up the topic of fraud outside of this circle, I am always surprised to see how little educated the general public is about an issue that is so critical to their financial health. I met a woman in an event several weeks ago. After learning about my occupation, she told me her story about someone from XYZ credit card company calling her and asking for her Social Security number, date of birth and other personal identifying information. Only days after she gave out the information that she realized things didn’t seem right. She called the credit card company and got her credit card re-issued. But at the time I talked to her, she still didn’t know enough to realize that the fraudster could now use her identity to start any new financial relationship under her name. As long as consumers are ignorant about protecting their identity information, businesses’ identity theft prevention program will not be complete and identity fraud will occur as a result of this weak link. To address this vulnerability and minimize fraud, consumers need to be educated.

-- by, Andrew Gulledge One of the quickest and easiest ways to reduce fraud in your portfolio is to incorporate question weighting into your out of wallet question strategy. To continue the use of knowledge based authentication without question weighting is to assign a point value of 100 points to each question. This is somewhat arbitrary (and a bit sloppy) when we know that certain questions consistently perform better than others. So if a fraudster gets 3 easier questions right, and 1 harder question wrong they will have an easier time passing your authentication process without question weighting. If, on the other hand, you adopt question weighting as part of your overall risk based authentication approach, that same fraudster would score much worse on the same KBA session. The 1 question that they got wrong would have cost them a lot of points, and the 3 easier questions they got right wouldn’t have given them as many points. Question weighting based on known fraud trends is more punitive for the fraudsters. Let’s say the easier questions were worth 50 points each, and the harder question was worth 150 points. Without question weighting, the fraudster would have scored 75% (300 out of 400 points). With question weighting, the fraudster would have scored 50% (150 out of 300 points correct). Your decisioning strategy might well have failed him with a score of 50, but passed him with a score of 75. Question weighting will often kick the fraudsters into the fail regions of your decisioning strategy, which is exactly what risk based authentication is all about. Consult with your fraud account management representative to see if you are making the most out of your KBA experience with the intelligent use of question weighting. It is a no-brainer way to improve your overall fraud prevention, even if you keep your overall pass rate the same. Question weighting is an easy way to squeeze more value of your knowledge based authentication tool.  

-- by, Andrew GulledgeThe intelligent use of question weighting in KBA should be a no-brainer for anyone using out of wallet questions. Here’s the deal: some authentication questions consistently give fraudsters a harder time than other questions. Why not capitalize on that knowledge?Question weighting is where each question type has a certain number of points associated with it. So a question that fraudsters have an easier time with might be worth only 50 points, while a question that fraudsters often struggle with might be worth 150 points. So the KBA score ends up being the total points correct divided by the total possible points. The point is to make the entire KBA session more punitive for the bad guys.Fraud analytics are absolutely essential to the use of intelligent question weighting. While fraud prevention vendors should have recommended question weights as part of their fraud best practices, if you can provide us with as many examples as possible of known fraud that went through the out of wallet questions, we can refine the best practice question weighting model to work better for your specific population.Even if we keep your pass rate the same, we can lower your fraud rate. On the other hand, we can up your pass rate while keeping the fraud rate consistent.  So whether your aim it to reduce your false positive rate (i.e., pass more of the good consumers) or to reduce your fraud rate (i.e., fail more of the fraudsters), or some combination of the two, question weighting will help you get there.

By: Margarita Lim You may be surprised to learn that identity theft isn’t just a crime committed by an individual or individuals. There are identity theft rings that are organized and operated like corporations. A recent Justice Department press release described such an operation in New Jersey that involved 53 individuals who took part in a known fraud activity called Bust Out Fraud. Basically, the fraud ring purchased valid social security cards and then sold the social security cards to customers who then obtained driver’s licenses and other proof of identity-type cards. The fraud ring then built up the credit scores of these customers by adding them to existing credit card accounts. Once the customers with the fraudulent identities achieved good credit scores, then they opened their own fraudulent bank accounts, credit cards, lines of credit, etc.  The credit cards were used to make fraudulent purchases or rack up charges with vendors in co-hoots with the fraud ring and the fraudulent bank accounts were used to pay off the charge accounts or the charges went unpaid. Fraud trends like these cost banks, credit card companies and many others millions of dollars – costs that ultimately get passed on to you and me, the consumers. Fortunately, Experian has Fraud Products that can help companies minimize fraud losses from Bust Out Fraud as well as other types of fraud. Our BustOut Score helps decrease bust out losses by predicting and detecting bust out frauds one to three months in advance of the event happening. In addition, we have Fraud Shield Indicators or fraud alerts available on credit reports that flag when there is a recent or new authorized user added to an established credit account. Experian supports Identity Theft Prevention Programs by offering highly accurate consumer identity verification services. We’re not reliant solely on credit bureau data and are able to use multi-sourced data to confirm different components of a consumer’s identity – name, address, date of birth, etc. 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.  

By: Margarita Lim Consumer data has increasingly become commoditized over the years. There’s a lot of it and it’s arguably more easily obtainable. Social Security number and date of birth information was once considered confidential information. Today, those data elements in addition to traditional consumer data such as name, address and phone number are more publicly available (either legitimately or illegitimately). The advent and popularity of social network Internet sites have also made considerable information about a person’s life – both professional and personal, available for anyone’s viewing pleasure. So the question is…how much is too much information? If you’re a consumer who is particular about privacy, then you’ll have a lower threshold. On the other hand, if you’re a business trying to minimize fraud losses, then you’re at the other end of the spectrum - you can never have enough information to help prevent fraud – especially when you’re trying to keep up with fraud trends. Data is a key element in fraud prevention. Experian has access to many data assets and has a reputation for providing high quality fraud products in the marketplace. The data we use in our fraud products comes from multiple sources and sets us apart from our competitors because corroborated data is more reliable than data from a single source.  Having access to multiple data sources is especially beneficial in our Knowledge Based Authentication product where the different sources provide data that is critical to generating out of wallet questions. Since companies rely on our fraud products to comply with the government’s Red Flag Rules and support Identity Theft Prevention Programs, it is extremely important that we have as much data as possible in our arsenal to thwart fraudsters’ activities and prevent consumers from being victimized by criminals. Keep in mind that these programs are only as good as the data used to confirm a person’s identity. Although information can be a double-edged sword, I don’t think one can have too much information especially when the goal is to minimize fraud.  

By: Kenneth Pruett I really thought I was going to be on easy street after receiving two emails in less than a week. The first email was telling me about some long lost relative in the UK who passed away over 10 years ago. His riches, which were over $20million dollars, would be forfeited to the government if an heir to the fortune did not claim the money. I was impressed how they figured out that I was the long lost “heir” to this millionaire just by looking at my email address. They also identified me specifically by calling me by name, “Dear Sir”.  The other email was a bit more intriguing. It involved a suitcase full of money. This was sent to me by a woman, who was in an abusive relationship but somehow had a chest full of money in America. For a certain % of the money, she was willing to pay me for my efforts to help her gain access to the suitcase and its contents. I am still surprised at just how many people fall victim to these types of email scams. They have been going on for quite some time, commonly known as the Nigerian 419 scam. I have noticed that the emails have changed a bit and seem to have become more convincing. The scammers also seem to be a bit more patient and work harder to gain the victims confidence in the legitimacy of the transaction. Individuals who give their information to these scammers will soon find out what a big mistake they have made. The goal of these groups is to gain access to a consumer’s money. They also will attempt to gather personal and banking information. Some victims of these scams may end up having their identity stolen. If they do attempt to use the identity information, they will typically make multiple attempts in a short period of time to establish credit. One way to help fight this type of organized fraud ring activity is to use velocity checks to track data elements. For example, a bank may want to know if a Social Security number has been used more than once within a certain period of time. Fraud analytic studies have also found that tracking data elements across multiple customers can also be very predictive in preventing fraud tied to identity theft rings. Elements often tracked are things like addresses, Social Security numbers and phone numbers. If these scammers attempt to take over consumers current bank accounts, they may attempt to change the address and possibly the phone number on the account. This is to prevent the true consumer from getting a phone call or mail relating to their account changes. Before making these changes, many entities often send out letters or make calls to the prior information before officially making these changes in their systems.  One other way to protect against account take over is to run the address and/or phone number against database of known frauds. A National Fraud Database can be helpful in identifying addresses that have been used in previous fraud activity. The Nigerian 419 scams will continue to be a problem. The need for money is just too great for some people to resist. For Banks, Card issuers, and Credit Unions, it is wise to put tools in place to help fight identity theft. This scam only represents a sample of the various fraudulent groups out there who make their living by ripping off these types of businesses. As I often say to my customers… I have done about everything in the fraud space, except commit it, which is the most profitable area. Good luck in your efforts to help us fight this ongoing problem.

In my last entry I mentioned how we’re working with more and more clients that are ramping up their fraud and compliance processes to ensure Red Flag compliance. But it’s not just the FACT Act Identity Theft Program requirements that are garnering all the attention.  As every financial institution is painfully aware, numerous compliance requirements exist around the USA PATRIOT Act and Know Your Customer, Anti-Money Laundering, e-Signature and more. Legislation for banks, lenders, and other financial services organizations are only likely to increase with President Obama’s appointment of Elizabeth Warren to the new Bureau of Consumer Financial Protection. Typically FI’s must perform due diligence across more than one of these requirements, all the while balancing the competing pressures of revenue growth, customer experience, fraud referral rates, and risk management. Here’s a case where we were able to offer a solution to one client’s complex needs.  Recently, we were approached by a bank’s sales channel that needed to automate their Customer Information Program (CIP). The bank’s risk and compliance department had provided guidelines based on their interpretation of due diligence appropriate for CIP and now the Sales group had to find a tool that could facilitate these guidelines and decision appropriately. The challenge was doing so without a costly custom solution, not sacrificing their current customer service SLA’s, and being able to define the criteria in the CIP decisioning rather than a stock interpretation. The solution was to invest in a customer authentication product that offered flexible, adaptable “off the shelf” decisioning along with knowledge based authentication, aka out of wallet questions. The fact that the logic was hosted reduced costly and time consuming software and hardware implementations while at the same time allowing easy modification should their CIP criteria change or pass and review rates need to be tweaked. The net result? Consistent customer treatment and objective application of the CIP guidelines, more cross selling confidence, and the ability to refer only those applicants with fraud alerts or who did not meet the name, address, SSN, and DOB check for further authentication.