Tag: fraud

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.

Another consumer protection article in the news recently highlighted some fraud best practices for social networking sites. Click here to read the article. When I say fraud best practices, I mean best practices to minimize fraud and identity theft risk…not best practices for fraudsters. Although I wonder if by advising consumers about new fraud trends and methods, some fraudsters are picking up new tips and tricks? Anyway, many of the suggestions in the article are common sense items that have been making the rounds for some time now: don’t post vacation plans, things that might provide clues to your passwords or secret questions, etc. What I found surprising was that this list of “6 Things You Should Never Reveal on Facebook” still included birth date and place and home address. Are people overly trusting or just simply unaware of the risk of providing personal identifying information out in cyber space, unsecured? The US government has gone to a lot of trouble to protect consumers from identity theft through its issuance of the Red Flags rule and Red Flags guidelines for financial institutions of all types. I work with many clients that are going to large efforts to meet these important goals for fraud and compliance. Not just because the legislation requires it but because they know it is in the best interest of fostering long term and trust-based relationships with their customers. But just as much responsibility lies on us as consumers to protect ourselves. Each individual or family should have their own little identity theft prevention program that includes: guidelines for sharing information on social networking sites, shredding of paper documents with personal data, safe storage of passwords (i.e. not written down by your computer!), and up to date virus and malware protection on their computer.

Anyone keeping tabs on the legal scene would think data breaches are something new, given all of the legislation hitting the floor of Congress, when in reality they have been happening since businesses began saving data. The truth is the average consumer didn’t really think about it until they started to hear about data breaches and fraud trends when California blazed a trail with what is considered to be the “grandma” of data breach laws back in 2002. The California law (CA SB 1386) required entities to report data breaches if a California resident was a record in the breach that included personally identifiable information and met the state’s criteria for breach. One might say that law started it all: data breach reporting, the ability for watchdog tracking, and media coverage – before CA SB 1386 we only saw the tip of the iceberg. There are currently four bills worth watching in Congress right now that could have some significant impact to data breach notification requirements: Senate Bill 139, sponsored by California Sen. Diane Feinstein. The Data Breach Notification Act would cover any agency or business that uses or stores personal identifiable information and make it mandatory that if a breach occurred, the victims would be informed Senate Bill 3579, the Carper-Bennett legislation, entitled the Data Security Act of 2010 applies to financial institutions, retailers and government agencies, and would require these entities to safeguard sensitive information, investigate security breaches and notify consumers when there is a substantial risk of identity theft or account fraud. This bill is aimed to protect consumers and businesses from identity theft and account fraud. Senate Bill 3742, entitled The Data Security and Breach Notification Act of 2010, sponsored by Senators Mark Pryor and Jay Rockefeller would cross industries and requires special requirements for data brokers. It was referred this month to the Committee on Commerce, Science and Technology, which Rockefeller chairs. Senate Bill 1490, entitled the Personal Data Privacy and Security Act, designates as fraud unauthorized access of personally identifiable information and allows the act to lead to racketeering charges. Sponsored by Senate Judiciary Committee Chairman, Patrick Leahy, it would also prohibit concealment of security breaches involved in fraud and prohibit the dismissal of a Chapter 7 bankruptcy case if the debtor is an identity-theft victim. Many organizations already provide for data breach and the security of personally identifiable information as part of an Identity Theft Prevention Program or Red Flags Rule compliance. I’m happy to say that many rely on Experian tools (https://www.experian.com/data-breach/data-breach-resources.html) for data breach or Enterprise Risk Management solutions. However, any of these bills could change the game for many businesses not already regulated by the Gramm-Leach-Bliley Act (GLB), the Fair Credit Reporting Act (FCRA) or Fair and Accurate Credit Transactions Act (FACTA). In fact, two of the bills would essentially subject data brokers to the same kinds of legislation that financial institutions have under FCRA. The reasoning behind it is that fraud trends continue to show risk levels are the same to the consumer, regardless of where the information is stored. The financial industry and credit bureau data have been regulated for years so, in a sense, I think it’s just “more of the same” unless you happen to be in an industry not regulated as stringently. Still… it’s worth keeping those “tabs” and RSS feeds alive.

Quite a scary new (although in some ways old) form of identity theft in the headlines recently. Here’s a link to the article, which talks about how children’s dormant Social Security numbers are being found and sold by companies online under the guise of CPN’s – aka credit profile numbers or credit protection numbers.  Using deceased, “found”, or otherwise illicitly obtained Social Security numbers is not something new.  Experian’s and any good identity verification tool is going to check against the Social Security Administration’s list of numbers listed as deceased as well as check to ensure the submitted number is in an SSA valid issue range.  But the two things I find most troubling here are: One, the sellers have found a way around the law by not calling them Social Security numbers and calling them CPN’s instead.  That seems ludicrous!  But, in fact, the article goes on to state that “Because the numbers exist in a legal gray area, federal investigators have not figured out a way to prosecute the people involved”. Two, because of the anonymity and the ability to quickly set up and abandon “shop”, the online marketplace is the perfect venue for both buyer and seller to connect with minimal risk of being caught. What can we as consumers and businesses take away from this?  As consumers, we’re reminded to be ever vigilant about the disclosure of not only OUR Social Security number but that of our family members as well.  For businesses, it’s a reminder to take advantage of additional identity verification and fraud prediction tools, such as Experian’s Precise ID, Knowledge IQ, and BizID, when making credit decisions or opening accounts rather than relying solely on consumer credit scores.

Working with clients in the financial sector means keeping an eye toward compliance and regulations like the Gramm-Leach-Bliley Act (GLB), the Fair Credit Reporting Act (FCRA) or Fair and Accurate Credit Transactions Act (FACTA). It doesn’t really matter what kind of product it is, if a client is a financial institution (FI) of some kind, one of these three pieces of legislation is probably going to apply. The good part is, these clients know it and typically have staff dedicated to these functions. In my experience, where most clients need help is in understanding which regulations apply or what might be allowed under each. The truth is, a product designed to minimize fraud, like knowledge based authentication, will function the same whether using FCRA regulated or non-FCRA regulated data. The differences will be in the fraud models used with the product, the decisioning strategies set-up, the questions asked and the data sources of those questions. Under GLB it is acceptable to use fraud analytics for detection purposes, as fraud detection is an approved GLB exception. However, under FCRA rules, fraud detection is not a recognized permissible purpose (for accessing a consumer’s data). Instead, written instructions (of the consumer) may be used as the permissible purpose, or another permissible purpose permitted under FCRA; such as legitimate business need due to risk of financial loss. Fraud best practices dictate engaging with clients, and their compliance teams, to ensure the correct product has been selected based on client fraud trends and client needs. A risk based authentication approach, using all available data and appropriately decisioning on that data, whether or not it includes out of wallet questions, provides the most efficient management of risk for clients and best experience for consumers.

By: Kristan Frend It seems as though desperate times call for desperate measures- with revenues down and business loans tougher than ever to get, “shelf” and “shell” companies appear to be on the rise. First let’s look at the difference between the two: Shelf companies are defined as corporations formed in a low-tax, low-regulation state in order to be sold off for its excellent credit rating. According to the Better Business Bureau, off-the-shelf structures were historically used to streamline a start-up, but selling them as a way to get around credit guidelines is new, making them unethical and possibly illegal. Shell companies are characterized as fictitious entities created for the sole purpose of committing fraud. They often provide a convenient method for money laundering because they are easy and inexpensive to form and operate. These companies typically do not have a physical presence, although some may set up a storefront. According to the U.S. Department of the Treasury’s Financial Crimes Enforcement Network, shell companies may even purchase corporate office “service packages” in order to appear to have established a more significant local presence. These packages often include a state business license, a local street address, an office that is staffed during business hours, a local telephone listing with a receptionist and 24-hour personalized voice mail. In one recent bust out fraud scenario, a shell company operated out of an office building and signed up for service with a voice over Internet protocol (VoIP) provider. While the VoIP provider typically conducts on-site visits to all new accounts, this step was skipped because the account was acquired through a channel partner. During months one and two, the account maintained normal usage patterns and invoices were paid promptly. In month three, the account’s international toll activity spiked, causing the provider to question the unusual account activity. The customer responded with a seemingly legitimate business explanation of activity and offered additional documentation. However, the following month the account contact and business disappeared, leaving the VoIP provider with a substantial five figure loss. A follow-up visit to the business showed a vacant office suite. While it’s unrealistic to think all shelf and shell companies can be identified, there are some tools that can help you verify businesses, identify repeat offenders, and minimize fraud losses. In the example mention above, post-loss account review through Experian’s BizID identified an obvious address discrepancy - 12 businesses all listed at the same address, suggesting that the perpetrator set up numerous businesses and victimized multiple organizations. The moral of the story? Avoid being the next victim and refine and revisit your fraud best practices today. Click here for more information on Experian's BizID

The overarching ‘business driver’ in adopting a risk-based authentication strategy, particularly one that is founded in analytics and proven scores, is the predictive ‘lift’ associated with using scoring in place of a more binary rule set. While basic identity element verification checks, such as name, address, Social Security number, date-of-birth, and phone number are important identity proofing treatments, when viewed in isolation, they are not nearly as effective in predicting actual fraud risk. In other words, the presence of positive verification across multiple identity elements does not, alone, provide sufficient predictive value in determining fraud risk. Positive verification of identity elements may be achieved in customer access requests that are, in fact, fraudulent. Conversely, negative identity element verification results may be associated with both ‘true’ or ‘good’ customers as well as fraudulent ones. In other words, these false positive and false negative conditions lead to a lack of predictive value and confidence as well as inefficient and unnecessary referral and out-sort volumes. The most predictive authentication and fraud models are those that incorporate multiple data assets spanning traditionally used customer information categories such as public records and demographic data, but also utilize, when possible, credit history attributes, and historic application and inquiry records. 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, application fraud, or other fraud risk. 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.

By: Kristan Frend As if business owners need one more thing to worry about — according to the Javelin Strategy & Research’s 2010 Identity Fraud Survey Report, respondents who defined themselves as “self-employed” or “small business owners” were one-and-a-half times more likely to be victims of identity theft. Intuitively this makes sense- business owners exposure would be higher than the average consumer as their information is viewed more often due to the broad array of business service needs. Also consider the fact that until recently, multiple states had public records containing proprietors social security numbers as tax identification numbers readily accessible on-line. What a perfect storm this has all created! Javelin’s report also explained that while the average fraud incidence for business owners was lower than the average consumers, small business owner’s consumer costs were higher.  In other words the small business owner suffered more out of pocket costs for identity theft losses than the average consumer. Experts believe this is due to the fact that commercial accounts often do not receive the same fraud guarantee protections that consumer accounts are afforded. While compliance regulations such as Red Flags Rules will enhance consumer safety, institutions must further develop their prevention and protection methods beyond what is legally required to sufficiently protect their small business customers from future fraud attacks. Small business owner fraud and the challenges organizations face in identifying and mitigating these losses are frequently overlooked and overshadowed by consumer fraud. Simply put, fraud is prevented because fraud is detected- verifying that the business owners is who they say they are using multiple data sources is critical to identifying applicant irregularities and protecting small business owners. A well-executed fraud strategy is more than just good business – it helps reduce small business customer acquisition costs and ultimately allows you to make better business decisions, creating a mutually beneficial relationship between your organization and the small business owner.  

There are a number of people within the industry heralding the death of knowledge based authentication. To those people I would say, “In my humble opinion you are as wrong as those recent tweets proclaiming the death of Bill Cosby.” Before anyone’s head spins around, let me explain. When I talk about knowledge based authentication and out of wallet questions, I mean it in the truest sense, a la dynamic questions presented as a pop quiz and not the secret questions you answered when you set-up an account. Dynamic knowledge based authentication presents questions are generated from information known about the consumer, concerning things the true consumer would know and a fraudster wouldn’t. The key to success, and the key to good questions, is the data, which I have said many, many times before. The truth is every tool will let some fraud through; otherwise, you’re keeping too many good customers away. But if knowledge based authentication truly fails, there are two places to look: Data: There are knowledge based authentication providers who rely solely on public record data for their KBA solutions. In my opinion, that data is a higher data risk segment for compromise. Experian’s knowledge based authentication practice is disciplined and includes a mix of data. Our research has shown us that a question set should, ideally, include questions that are proprietary, non-credit, credit and innovative. Yes, it may make sense to include some public record data in a question set, but should it be the basis for the entire question set? Providers who can rely on their own data, or a strategic combination of data sources, rather than purchasing it from one of the large data aggregators are, in my opinion, at an advantage because fraudsters would need to compromise multiple sources in order to “game the system.” Actual KBA use: Knowledge based authentication works best as part of a risk management strategy where risk based authentication is a component within the framework and not the single, determining factor for passing a consumer. Our research has shown that clients who combine fraud analytics and a score with knowledge based authentication can increase authentication performance from 20% - 30% or more, depending on the portfolio and type of fraud (ID Fraud vs. First Party, etc.)… and adding a score has the obvious benefit of increasing fraud detection, but it also allows organizations to prioritize review rates efficiently while protecting the consumer experience. So before we write the obituary of KBA, let’s challenge those who tinker with out of wallet products, building lists of meaningless questions that a 5th grader could answer. Embrace optimized decisions with risk based authentication and employ fraud best practices in your use of KBA.

A few days ago I saw an article about hackers working from Russia, while committing check fraud in the United States. In what those investigating are calling a brilliant operation, the fraudsters compromised companies that archive and store records of check images or checks themselves. They then downloaded those check images and all available information. By printing new checks and using an old Internet “money mule” scheme, the fraudsters were able to send the bogus checks to ”the mule”, often as a payment, and have the check cashed at the mule’s bank to get the balance of the funds wired to an off-shore bank account. That article made me think about new breakthroughs in technology. What if those fraudsters had been a little savvier? What if they had the most recent smart phone application installed and didn’t need a mule to wire the money? They could have simply written checks and uploaded them for deposit to an account to which they had gained access with the hottest application du jour – deposit via photo image uploaded from a smart phone. That application would have allowed the fraudsters to cash the bogus check, gain access to the funds and move them to the next account at will. Or would it? Given the move toward mobile banking, it isn’t really a stretch to see this kind of thing happening. Probably not, but if organizations offering this kind of service use a risk based authentication approach it is more likely they use fraud models and decisioning strategies to minimize fraud and protect consumers while pushing out the latest technology. For those reasons, risk management solutions and enterprise fraud vendors need to not only keep pace with technology but also stay ahead of the curve in order to provide optimized decisions and the most relevant fraud analytics. Considering recent fraud trends and my love affair with mobile everything, I know I want the organizations I do business with to do everything they can to prevent fraud…and I’m positive I want my smart phone to be as smart as possible.

I often provide fraud analyses to clients, whereby they identify fraudsters that have somehow gotten through the system.  We then go in and see what kinds of conditions exist in the fraudulent population that exist to a much lesser degree in the overall population.  We typically do this with indicators, flags, match codes, and other conditions that we have available on the Experian end of things. But that is not to say there aren't things on your side of the fence that could be effective indicators of fraud risk as well! One simple example could be geography.  If 50% of your known frauds are coming from a state that only sees 5% of your overall population, then that state sounds like a great indicator of fraud risk!  What action you take based on this knowledge is up to you (and, I suppose, government regulation).  One option would be to route the risky customers through a more onerous authentication procedure.  For example, they might have to come into a branch in person to validate their identity. Geography is certainly not the only potential indicator of fraud risk.  Be creative!  There might be previously untapped indicators of fraud risk lurking in your customer databases.   Do not limit yourself to intuition either.  Oftentimes the best indicators of fraud risk that I find are counterintuitive.  Just compare the percentage of time a condition occurs in your fraud population to the percentage of time it occurs in the overall population.  It might be that you have a fraud ring that is leaving some telltale fingerprint on their behavior--one that is actionable in ways that will jumpstart your fraud prevention practices and minimize fraud losses!

I have already commented on “secret questions” as the root of all evil when considering tools to reduce identity theft and minimize fraud losses.  No, I’m not quite ready to jump off  that soapbox….not just yet, not when we’re deep into the season of holiday deals, steals and fraud.  The answers to secret questions are easily guessed, easily researched, or easily forgotten.  Is this the kind of security you want standing between your account and a fraudster during the busiest shopping time of the year? There is plenty of research demonstrating that fraud rates spike during the holiday season.  There is also plenty of research to demonstrate that fraudsters perpetrate account takeover by changing the pin, address, or e-mail address of an account – activities that could be considered risky behavior in decisioning strategies.  So, what is the best approach to identity theft red flags and fraud account management?  A risk based authentication approach, of course! Knowledge Based Authentication (KBA) provides strong authentication and can be a part of a multifactor authentication environment without a negative impact on the consumer experience, if the purpose is explained to the consumer.  Let’s say a fraudster is trying to change the pin or e-mail address of an account.  When one of these risky behaviors is initiated, a Knowledge Based Authentication session begins. To help minimize fraud, the action is prevented if the KBA session is failed.  Using this same logic, it is possible to apply a risk based authentication approach to overall account management at many points of the lifecycle: • Account funding • Account information change (pin, e-mail, address, etc.) • Transfers or wires • Requests for line/limit increase • Payments • Unusual account activity • Authentication before engaging with a fraud alert representative Depending on the risk management strategy, additional methods may be combined with KBA; such as IVR or out-of-band authentication, and follow-up contact via e-mail, telephone or postal mail.  Of course, all of this ties in with what we would consider to be a comprehensive Red Flag Rules program. Risk based authentication, as part of a fraud account management strategy, is one of the best ways we know to ensure that customers aren’t left singing, “On the first day of Christmas, the fraudster stole from me…”  

Many compliance regulations such the Red Flags Rule, USA Patriot Act, and ESIGN require specific identity elements to be verified and specific high risk conditions to be detected. However, there is still much variance in how individual institutions reconcile referrals generated from the detection of high risk conditions and/or the absence of identity element verification. With this in mind, risk-based authentication, (defined in this context as the “holistic assessment of a consumer and transaction with the end goal of applying the right authentication and decisioning treatment at the right time") offers institutions a viable strategy for balancing the following competing forces and pressures: • Compliance – the need to ensure each transaction is approved only when compliance requirements are met; • Approval rates – the need to meet business goals in the booking of new accounts and the facilitation of existing account transactions; • Risk mitigation – the need to minimize fraud exposure at the account and transaction level. A flexibly-designed risk-based authentication strategy incorporates a robust breadth of data assets, detailed results, granular information, targeted analytics and automated decisioning. This allows an institution to strike a harmonious balance (or at least something close to that) between the needs to remain compliant, while approving the vast majority of applications or customer transactions and, oh yeah, minimizing fraud and credit risk exposure and credit risk modeling. Sole reliance on binary assessment of the presence or absence of high risk conditions and identity element verifications will, more often than not, create an operational process that is overburdened by manual referral queues. There is also an unnecessary proportion of viable consumers unable to be serviced by your business. Use of analytically sound risk assessments and objective and consistent decisioning strategies will provide opportunities to calibrate your process to meet today’s pressures and adjust to tomorrow’s as well.  

On Friday, October 30th, the FTC again delayed enforcement of the “Red Flags” Rule – this time until June 1, 2010 – for financial institutions and creditors subject to the FTC’s enforcement.   Here’s the official release: http://www.ftc.gov/opa/2009/10/redflags.shtm. But this doesn’t mean, until then, businesses get a free pass.  The extension doesn’t apply to other federal agencies that have enforcement responsibilities for institutions under their jurisdiction.  And the extension also doesn’t alleviate an institution’s need to detect and respond to address discrepancies on credit reports. Red Flag compliance Implementing best practices to address the identity theft under the Red Flags Rule is not just the law, it’s good business.  The damage to reputations and consumer confidence from a problem gone unchecked or worse yet – unidentified – can be catastrophic.  I encourage all businesses – if they haven’t already done so – to use this extension as an opportunity to proactively secure a Red Flags Rule to ensure Red Flag compliance.  It’s an investment in protecting their most important asset – the customer.  

By: Kennis Wong In Part 1 of Generic fraud score, we emphasized the importance of a risk-based approach when it comes to fraud detection. Here are some further questions you may want to consider. What is the performance window? When a model is built, it has a defined performance window. That means the score is predicting a certain outcome within that time period. For example, a traditional risk score may be predicting accounts that are decreasing in twenty-four months. That score may not perform well if your population typically worsens in two months. This question is particularly important when it relates to scoring your population. For example, if a bust-out score has a performance window of three months, and you score your accounts at the time of acquisition, it would only catch accounts that are busting-out within the next three months. As a result, you should score your accounts during periodic account reviews in addition to the time of acquisition to ensure you catch all bust-outs.  Therefore, bust out fraud is an important indicator. Which accounts should I score? While it’s typical for creditors to use a fraud score on every applicant at the time of acquisition, they may not score all their accounts during review. For example, they may exclude inactive accounts or older accounts assuming those with a long history means less likelihood of fraud. This mistake may be expensive. For instance, the typical bust-out behavior is for fraudsters to apply for cards way before they intend to bust out. This may be forty-eight months or more. So when you think they are good and profitable customers, they can strike and leave you with seriously injury. Make sure that your fraud database is updated and accurate.  As a result, the recommended approach is to score your entire portfolio during account review. How often do I validate the score? The answer is very often -- this may be monthly or quarterly. You want to understand whether the score is working for you – do your actual results match the volume and risk projections? Shifts of your score distribution will almost certainly occur over time. To meet your objectives over the long run, continue to monitor and adjust cutoffs.  Keep your fraud database updated at all times.