Financial Services
It’s that time of year again – when people all over the U.S. take time away from life’s daily chores and embark upon that much-needed refresh: vacation! But just as fraud activity spikes during the holidays, there are also fraud trends suggesting spikes in fraudster activity during the summer. With consumers on vacation, identity theft becomes easier. Consumers are most likely to break their normal spending trends and break patterns established by fraud analytics; and consumers are less likely to be as attentive to elements that can help minimize fraud while out of town. There has been plenty of research to demonstrate that fraudsters perpetrate account takeover by changing the pin, address, or email address of an account. Now, fraudsters are more likely to add themselves as an authorized user to the account, which may not be considered a high-risk flag in transactional decisioning strategies. By identifying risky behaviors or patterns outside of a consumer’s normal behavior and an engaging in a knowledge based authentication session with the consumer, it is possible to help minimize the risk of fraud. Knowledge based authentication provides strong authentication and can be part of a risk-based approach to on-going account management, protecting both businesses and consumers from being burned, at least by fraudsters, while on vacation.
By: Kari Michel On March 18th 2011 the Federal Reserve Board approved a rule amending Regulation Z (Truth in Lending) to clarify portions of the final rules implementing the Credit CARD Act of 2009. Specific to ability to pay requirements, the new rule states that credit card applications generally cannot request a consumer\'s \"household income\" because that term is too vague to allow issuers to properly evaluate the consumer\'s ability to pay. Instead, issuers must consider the consumer\'s individual income or salary. The new ruling will be effective October 2011. Given the new direction outlined in the latest rules, we\'ve been hard at work on developing 2 income models to support these regulatory obligations and enhance the underwriting and risk assessment process - Income InsightSM and Income Insight W2SM. Both income models estimate an individual’s income based on an individual credit report and can be used in acquisition strategies, account management review and collection processes. Why two models? Income InsightSM estimates the consumer’s total income, including wages, investments, rentals and other income. Income Insight W2SM estimates wages only. Check them out - and let us know what you think! We want to hear from you.
By: Kennis Wong When we think about fraud prevention, naturally we think about mininizing fraud at application. We want to ensure that the identities used in the application truly belong to the person who applies for credit, and not identity theft. But the reality is that some fraudsters do successfully get through the defense at application. In fact, according to Javelin’s 2011 Identity Fraud Survey Report, 2.5 million accounts were opened fraudulently using stolen identities in 2010, costing lenders and consumers $17 billion. And these numbers do not even include other existing account fraud like account takeover and impersonation (limited misusing of account like credit/debit card and balance transfer, etc.). This type of existing account fraud affected 5.5 million accounts in 2010, costing another $20 billion. So although it may seem like a no brainer, it’s worth emphasizing that we need to have fraud account management system and continue to detect fraud for new and established accounts. Existing account fraud is unlikely to go away any time soon. Lending activities have changed significantly in the last couple of years. Origination rate in 2010 is still less than half of the volume in 2008, and booked accounts become riskier. In this type of environment, when regular consumers are having hard time getting new credits, fraudsters are also having hard time getting credit. So they will switch their focus to something more profitable like account takeover. In addition to application fraud, does your organization have appropriate tools and decisioning strategy to minimize fraud loss from existing account fraud?
The next time a consumer asks about his or her credit score, consider it an opportunity. Recent changes to the Risk-Based Pricing (RBP) rule may provide new opportunities to strengthen relationships by educating consumers about what their credit scores mean, how they’re used, and how they can be improved. For many lenders and other businesses, this could be the first time they’ve had a chance to speak directly and openly with customers about their credit scores. The RBP rule is intended to improve financial literacy As we’ve discussed, the Risk-Based Pricing Rule was instituted in response to policymaker concerns that consumers were not being sufficiently informed of the impact that credit reports can have on their annual percentage rate (APR). Now, when a lender makes a credit decision based on a consumer credit report and does not offer the best possible rate, or denies credit, the RBP Rule requires lenders to notify the customer about the decision – through either an explanation of the rate offered or disclosing a credit score. New requirements take effect on July 21 RBP compliance is changing following recent passage of the Dodd-Frank Wall Street Reform and Consumer Protection Act. Companies will now be required to provide all customers with a credit score within a Risk Based Pricing Notice, along with educational material. The new requirement is effective July 21, 2011. This is also the date when the new Bureau of Consumer Financial Protection (CFPB) is set to be fully operational. How to prepare for consumer questions about credit scores Experian offers a number of resources to help lenders answer consumer questions. Online resources, including the Ask Experian column and our extensive Credit Education section, provide fundamental information to help consumers better understand credit scores and credit reports. The Experian Credit Score Basics booklet, plus more than 20 other educational documents, are available electronically and formatted for easy printing and distribution. All documents, PowerPoint presentations, virtual seminars and education videos are available on a free mini-disk. Customized training and education is available The Experian Public Education team can also provide customized, live Internet-based training and education for our clients’ employees to help them effectively answer customer questions about credit reports and credit scores. For a free mini-disk or more information about training events, please contact Rod Griffin, Experian’s Director of Public Education, at 1 (972) 390-3528, or email clientcorner@experian.com. Take a moment to check out our Risk-Based Pricing microsite, too. Note: While Experian is happy to provide our observations related to the new Risk-Based Pricing Rule, please work with your own legal counsel to ensure that you comply with your obligations under the rule.
By: Kristan Frend Small business owners appear to be lucrative targets for identity fraud perpetrators, alarming banking institutions, payment processors, and B2B service providers. According to Javelin’s 2011 Small Business Owners (SMBO) Identity Fraud report, the cost of fraud and identity theft “hit SMBO constituents particularly hard. Javelin research uncovered what was previously an undocumented cost to the industry of $5 billion as a direct result of this fraud. In addition, financial institutions (FIs) lost over $590 million in clients and revenue opportunities over a five‐year period.” Additionally, the report indicated that small business owners mean fraud amount is about 5% higher than that for all consumers ($4,851 vs. $4,607). Even more alarming was the fact that the SMBO’s mean victim cost is 150% higher than consumer costs ($1,574 vs. $631). So what does all of this mean? If you’re a small business lender or service provider, having a robust multi-layered SMBO fraud prevention program in place is essential for client retention and avoiding reputational risk. You can take control of the situation with more proactive fraud prevention strategies which will improve your relationships with SMBO customers and save them (and you) money in the long run.
By: Staci Baker It seems like every time I turn on the TV there is another natural disaster. Tsunami in Japan, tornadoes and flooding in the Mid-West United States, earthquakes and forest fires – everywhere; and these disasters are happening worldwide. They are not confined to one location. If a disaster were to happen near any of your offices, would you be prepared? Living in Southern California, this is something I think of often. Especially, since we are supposed to have had “the big one” for the past several years now. When developing a preparedness plan for a company, there are several things to take into consideration. Some are obvious, such as how to keep employees safe, developing steps for IT to take to ensure data is protected , including an identity theft prevention program, and establishing contingency business plans in case a disaster directly hits your business and doors need to remain closed for several days, weeks, or …. But, what about the non-obvious items that should be included in a disaster preparedness plan? When a natural disaster hits, there is an increase in fraud. So much so, that after Hurricane Katrina battered the Gulf, the Hurricane Katrina Fraud Task Force, now known as the National Center for Disaster Fraud, was created. In addition to the items listed above, I recommend including the following. Create a plan that will put fraud alerts in place to minimize fraud. Fraud alerts are not just to notify your clients when there is fraudulent activity on their accounts. Alerts should also be put in place to let you know when there is fraudulent activity within your own business as well. Depending on the type of disaster, delinquency rates may increase, since borrower funds may be diverted to other needs. Implement a disaster collections strategy, which may include modifying credit terms, managing credit risk, and loan loss provisioning. Although these are only a few things to be considered when developing a disaster preparedness plan, I hope it gets you thinking about what your company needs to do to be prepared. What are some things you have already done, or that are on your to do list to prepare your company for the next big event that may affect you?
Last week I attended the Merchant Risk Council’s 2011 MRC Annual e-Commerce Payments & Risk Conference. I presented a session titled “Efficiency and Empowerment in Risk-based Authentication” with a client who has been able to use knowledge based authentication as a sales enabler - Home Shopping Network. You might be wondering what I mean by this. It is actually pretty simple: Home Shopping Network already has a fraud prevention program in place and utilizes risk based authentication to send a percentage of orders to an outsort queue. By using knowledge based authentication to further verify the true consumer, Home Shopping Network has been able to release an increased portion of those orders for shipping, increasing both revenue and the customer experience. The paradigm shift was thinking of knowledge based authentication as a sale enabler, rather than just a fraud tool. It was a great experience, to help share the story of this client’s success. If you are interested in the Merchant Risk Council: The Merchant Risk Council (MRC) is a merchant-led trade association focused on electronic commerce risk and payments. They lead industry networking, education, benchmarking and advocacy programs to make electronic commerce more efficient, safe and profitable. For more information on the Home Shopping Network, visit: http://www.hsn.com
Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:\"Table Normal\"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:\"\"; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:\"Calibri\",\"sans-serif\"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:\"Times New Roman\"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:\"Table Normal\"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:\"\"; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:\"Calibri\",\"sans-serif\"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:\"Times New Roman\"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} By: Kristan Frend I was recently pleased to see that the state I reside in, Minnesota finished in the bottom third of a state ranking. Luckily the rankings weren’t about overall health (#6), high school graduation (#3), or SAT scores (#2); instead it was the Federal Trade Commission’s state identity theft complaint ranks. Minnesota has just 49.2 complaints per 100,000 population, whereas the highest ranked state, Florida, as 114.8 complaints per 100,000 population. The top three states leading identity theft consumer complaints (per 100,000 population) included Florida, Arizona, and California. Besides warm sunshine and top-tier golf courses, what do these three states have in common? According to the February 2011 RealtyTrac U.S. Foreclosure Market Report™, all three rank in the top 5 states for foreclosure, and two of the three (Florida and California) rank #49 and #50 in unemployment rates, according to a March 2011 report released by the Bureau of Labor Statistics. On a national level unemployment rates and identity fraud incidence rates both improved from 2009 to 2010. From 2009 to 2010, unemployment rates went from 10.0% to 9.4% while according to Javelin’s 2010 Annual Identity Fraud Survey Report, identity fraud incidence rates fell from 4.8% to 3.5%. While it may be inaccurate to state that economic distress causes higher rates of identity fraud, there does seem to be a natural correlation between economic downswings and fraudulent activity. As we move further into 2011, it will be interesting to see if identity fraud incidence rates will continue to decrease as unemployment and economic outlook is on the upward swing. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:\"Table Normal\"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:\"\"; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:\"Calibri\",\"sans-serif\"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:\"Times New Roman\"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;}
Well, actually, it isn’t. The better question to ask is when to use knowledge based authentication (KBA). I know I have written before about using it as part of a risk based authentication approach to fraud account management, but I am often asked what I mean by that statement. So, I thought it might be a good idea to provide a few more details and give some examples. Basically, what I mean is this: risk segmentation based on binary verification is unwise. Binary verification can occur based on identity elements, or it can occur based on pass/fail performance from out of wallet questions, but the fact remains that the primary decisioning strategy is relying on a condition with two outcomes – verified or not verified, pass or fail – and that is unwise. When we recommend a risk based authentication approach, the view is more broadly based. We advocate using analytics and weighting many factors, including those identity elements and knowledge based authentication performance as part of an overall decision, rather than an as end-all decision. If you take this kind of approach, when might you want to use this kind of approach? The answer to that is just about any time a transaction contains a level of risk, understanding that each organization will have a unique definition and tolerance for “risk”. It could be an origination or account opening scenario, when you do not yet have a relationship with a consumer. It could be in an account management setting, when you have a relationship with the consumer and know their expected behavior (and therefore anything outside of expected behavior is risk). It could be in transactional settings where there is an exchange of money or information belonging to the consumer. All of these are appropriate uses for KBA as part of a risk based approach.
Application risk management processes for deposits has remained relatively unchanged for decades. Typically, it involves credit bureau data and a secondary check of “debit bureau” data. A “debit bureau” typically gathers information regarding known fraud and compiles a fraud database of perpetrators. Every applicant who passes the credit risk strategies is checked against this database. The challenge is that this process can be very expensive. Among a new class of fraud best practices is the idea of applying fraud models/fraud analytics as a filter upstream from the debit bureau’s fraud database. This practice enables deposit institutions to still identify known fraud and minimize fraud losses on those applicants that carry the highest risk. At the same time, costs are reduced by removing low risk accounts from the debit bureau check. In addition to reducing costs, these revised acquisition strategies help reduce fraud referral rates while ensuring that application fraud does not increase. As deposit institutions look for ways to significantly reduce costs without suffering additional application fraud, look for the continued emergence of fraud analytics among 2011’s fraud best practices.
By: Kari Michel In January, Experian announced the inclusion of positive rental data from its RentBureau division into the traditional credit file. This is great news for an estimated 50 million underbanked consumers - everyone from college students and recent graduates to immigrants - to build credit with continuous on-time rental payments. With approximately 1/3 of Americans renting, lenders who are using VantageScore will benefit from the inclusion of RentBureau data into the score calculation. VantageScore from Experian is able to both enhance its predictive ability for those that can already be scored as well as provide scores for those that previously could not be scored. With the inclusion of RentBureau data, 34% of thin file consumers increased their score from an ‘F’ (VantageScore 501 – 599) to a ‘D’ (VantageScore 600 – 699). For those consumers that did not have a prior credit history, 70% of them were able to be scored after the inclusion of RentBureau data into the credit repository. As a result, fewer consumers will get a “no hit” returned to lenders during a credit inquiry. Lenders will now have a comprehensive understanding of a consumer’s total monthly obligations to assist with offering credit to emerging consumers.
I love a good analogy, and living in Southern California, lately I’ve been thinking a lot about earthquakes, and how lenders might want to start thinking like seismologists when considering the risk levels in their portfolios. Currently, scientists that study earthquakes review mountains of data around fault movement, tidal forces, even animal behavior, all in an attempt to find a concrete predictor of ‘the big one’. Small tremors are inputs, but the focus is on predicting and preparing for the large shock and impact of large earthquakes. Credit risk modeling, conversely, seems to focus on predicting the tremors, (risk scores that predict the risk of individual default) and less so the large-shock risk to the portfolio. So what are lenders doing to forecast ‘the big one’? Lenders are building sophisticated models that contemplate the likelihood of the big event – developing risk models and econometric models that look at loan repayment, house prices, unemployment rates – all in an attempt to be ahead of the credit version of ‘the big one’. This type of model and perspective is at a nascent stage for many lenders, but like the issues facing the people of Southern California, preparing for the big-one is an essential part of every lender’s planning in today’s economy.
Exciting research leveraging Experian’s fraud analytics and credit risk modeling are now enabling deposit institutions to understand the impacts of first party fraud and identity theft on their portfolios. Historically, deposit institutions have not considered application fraud to be a major concern and legislation regarding overdraft fees and the opt-in provision for overdraft services will reduce a deposit customer’s ability to spend the bank’s money; however, a determined thief can still: kite checks to commit first party fraud perpetrate an account takeover/identity theft The result is that deposit institutions will continue to face losses that can be prevented using fraud best practices. The challenge for the institution is knowing whether it is facing first party fraud or identity theft. Increasingly, deposit institutions are turning to Experian to analyze customers that create losses early in the account life cycle in order to make the right modifications to their acquisitions strategies. Using a combination of fraud analytics built to target specific types of fraud trends, deposit institutions can get a clear picture of the type of behavior that is generating their losses. This type of analysis is quickly climbing the list of fraud best-practices. Armed with the right diagnosis, deposit institutions can respond by prioritizing the right set of fraud alerts.
By: Kristan Frend Imagine you’re on the #1 ranked relay swim team at the World Championships and you’re leading off. You finish your leg of the race with the team in first place. As your third teammate approaches the wall, your team is in first by a full body length. You’re on pace to set a new world record. Yet the anchor of your team is nowhere to be found, ultimately resulting in your team being disqualified. If only your fourth teammate would have made it to the blocks in time…. When you take a step back and look at your fraud risk management solutions, do you ever feel like you have all of the tools and processes available yet feel like the anchor is missing? Perhaps it’s time to reexamine your internal resources. You may have an assembly of sophisticated and robust online fraud detection tools from vendors, but you may be missing a critical piece if you’re not also effectively leveraging internal data. Through our work with clients, we’re found that it is not uncommon for organizations to manage the customer relationship through different departments or silos within the organization. All too often there is less than optimal coordination between these functional areas in taking advantage of their own internal negative data to combat application fraud. Additionally some organizations may have negative internal data but do not incorporate the check within their verification or risk based authentication tool, creating multiple steps and operational inefficiencies. One of the ways to overcome some of these issues is by incorporating internal negative data within an automated front-end check. Once loss data is loaded into a historical database, the next time that name, phone, address, driver’s license or SSN reappears on a new application, the data element is immediately identified as one associated with a previous loss. The negative data is securely stored for only your organization’s use and is not shared with users outside of your organization.
Let’s face it – not all knowledge based authentication (KBA) is created equal. I, too, have read horror stories of consumers forced to answer questions about a deceased relative or ex-spouse, or KBA sessions that went on far too long for anyone’s benefit. I have to attribute this to vendor inexperience and a lack of consulting with clients. An experienced vendor will use a fraud best practice such as a fraud analytics model to determine that some consumers do not even need questions and then a “Progressive Question” feature, which uses consumer performance on an initial question set to determine if it is necessary for the consumer to answer additional questions. This way, the true consumer completes the process quickly, improving the customer experience. The product of choice should also use a question mix that balances three factors: · how easily the true consumer can answer the question; · the fraud separation of the question (effectively the measured delta over time between how well true consumers answer the question vs. how well fraudsters do); · how many consumers overall the question can be generated. A list of hundreds of possible questions doesn’t mean much if the questions can only be generated for one quarter of one percent of the population, as is the case for something like airplane ownership or pilot’s license. Ultimately, out of wallet questions should be generated for a large part of the population, easily answered by the true consumer but difficult for a fraudster; and not offensive or what a consumer would consider “creepy” (such as their child’s birthday or name). Well designed questions will be personal but not intrusive and mindful of personal relationships that may have changed. The purpose of a knowledge based authentication session is risk management and/or consumer authentication for fraud prevention and compliance purposes – not to cause the loss of business because the fraud tool crossed the line in the mind of your customer.
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