Credit Lending
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.
Cell phone use on the rise A Wikipedia list of cell phone usage by country showed that as of December 2009, the U.S. had nearly 286 million cell phones in use. In parallel, a recent National Center for Health Statistics study found that one in every seven homes surveyed received all or almost all their calls on cell phones, even though they had a landline. Study results further indicated, one in four homes in the U.S. relied solely on cell phones. This statistic highlights these households had no land line at all during the last half of 2009. Since this time, the number of households that fall within this category have increased 1.8 percent. Implications for communications companies The increasing use of cell phones, coupled with the decreasing use of landlines, raises some very important concerns for communications companies: The physical address on file may not be accurate, since consumers can keep the same number as they jump providers. The increased use of pre-paid cell phones shines a new light on the growing issue that contact numbers are not a consistent means of reaching the consumer. These two issues make locating cell phone-only customers for purposes of cross-selling and/or collections an enormous challenge. It would certainly make everyone’s job easier if cell phone providers were willing to share their customer data with a directory assistance provider. The problem is, doing so, exposes them to attacks from their competition and since provider churn rate concerns are at an all-time high, can you really blame them? Identifying potentially risky customers, among cell phone-only consumers, becomes more difficult. Perfectly good customers may no longer use a landline. From a marketing point of view, calling cell phones for a sales pitch is not allowed, how then do you reach your prospects? What concerns you? Certainly, this list is by no means complete. The concerns above warrant further discussion in future blog posts. I want to know what concerns you most when it comes to the rise in cell phone-only consumers. This feedback will allow me to gear future posts to better address your concerns.
By: Staci Baker According to Wikipedia, mobile banking is defined as, “a term used for performing balance checks, account transactions, payments, credit applications, etc. via a mobile device such as a mobile phone or Personal Digital Assistant (PDA).” However, as several large lenders and phone carriers test mobile banking and mobile payments, there is still much to be deciphered. Will it help businesses compete? Is it safe for a consumer? Should a bank offer a mobile solution; and if so, what precautions will they need to take to ensure their customer’s information, i.e. fraud, consumer identity? Peter Garuccio, spokesman for the American Bankers Association in Washington D.C., noted that “various experts predict that some 20 million people may be banking via cell phone this year, and that number is projected to skyrocket to 50 million by 2013.” And, according to a mobile payment study by Juniper Research ,“Combined market for all types of mobile payments is expected to reach more than $630B globally by 2014.” For the purpose of this blog, I will focus on the mobile banking solution, and questions to consider before entering into the mobile banking arena. Mobile banking today is akin to online banking a few years ago. It’s new, getting a lot of press, late adopters want more information, while the early adopters are already participating and it appears to be on the verge of taking over more conventional banking and payments. Before entering into the world of mobile solutions, there are a few things to consider: How will new regulations, such as the Durbin Amendment to the Frank-Dodd Act (a new Interchange fee proposal), affect implementation and usage? The current average interchange fee is between $1 and $1.30, the new cap at $.12 will reduce the charges by up to 90%.While the interchange fee proposal will not be finalized until after February, it is not known how the new “swipe fee” legislation will affect mobile solutions. If the new amendment directly affects debit cards only, mobile solutions can become a new revenue stream for many lenders. As more information becomes available regarding the Durbin Amendment, I will relay additional details and implications. What fraud prevention solutions do you have in place? Fraud is an issue in all industries; therefore utilizing fraud best practices specific to your market, or identifying fraud trends is essential in keeping retailers, consumers and your company safe. As consumers replace the need for a wallet with a phone, identity theft can become an issue. This is especially true of phones with minimal security, or if their phone gets into the hands of a hacker. Therefore companies can initiate an identity theft prevention program to raise awareness in consumers and retailers. As well as implement new internal processes and requirements. As we delve further into an IT-led economy, businesses will continually need to adjust how they do business in order to meet consumer demand, as well as finding new revenue streams. I am curious, how many businesses have already begun to implement a mobile solution, and what issues or results have you already seen? If you have not already implemented a mobile solution, is this in your planning for the upcoming year?
By: Kari Michel Lending institutions are more challenged today than ever before when assessing credit risk to find creditworthy consumers. Since 2006, the start of the housing bust and recession, consumer’s overall creditworthiness has deteriorated, especially those consumers who once had a high score (low risk). “For example, a study earlier this year by VantageScore found that the probability of serious delinquency, defined as nonpayment for 90 days or more, had increased by 417 percent among “super prime” borrowers between June 2007 and June 2009. Default risk during the same period rose by 406 percent for the second-highest rated category of “prime” consumers, and nearly doubled for those at the “near prime” scoring level.”* VantageScore is one example of a credit risk model that was recently redeveloped to capture the changing consumer behavior of repayment. The development data set included 45 million consumer credit profiles for the time period of 2006 to 2009. VantageScore 2.0 will be released for lenders use January 2011. *Source: The Washington Post, “Walk-aways leading to big changes for all borrower’s credit score, November 5, 2010 Link for article: http://www.washingtonpost.com/wp-dyn/content/article/2010/11/05/AR2010110502133.html
By: Kristan Frend According to the 2011 Identity Theft Assistance Center Outlook (ITAC), new forms of small business identity theft are emerging. This shouldn’t be a surprise that criminals view small business accounts as a lucrative funding source. What is surprising is that the ‘new’ form of small business identity theft consists of the U.S. Postal Inspection Service reporting a surge in criminal rings using small business information from stolen mail, check writing software and other tactics to counterfeit checks. That’s the new wave of small business identity theft??? I consider this one of the least sophisticated types of fraud that can easily be eliminated by small business owners not leaving mail unattended. Reading this report makes me realize that we have a long way to go in identifying and reporting the more sophisticated types of small business fraud. As I’ve mentioned before, the industry has come a long way in advancing consumer fraud solutions. Yet, as fraud has migrated into business accounts, we as an industry still have a ways to go in reporting the latest business fraud trends and tracking statistics. I’m adding this to my wish list for 2011… What’s on your wish list? On a side note, I’ve noticed nearly all of the articles posted in our blog include no reader comments. I’d like to think that this means our readers are too busy to add comments and/or our articles are so well-written that they answer all of your questions. One can dream right? Seriously though, as we approach 2011 and plan our topics, we’d love to hear from you- if you can think of any topic you’d like us to cover more in depth, please let us know.
By: Kristan Frend As my colleague Margarita Lim discussed in her December 3rd article, the SSA announced that it will change how social security numbers (SSNs) will be issued, with a move toward a random method of assigning SSNs. For organizations that currently incorporate the validation of an applicant’s SSN issue date and state as a part of their risk-based decisioning, they will lose this piece of applicant authentication post-randomization. But there is some good news - first, this validation piece won’t be entirely terminated on day one of the SSN randomization for organizations. All the change means is that the newly issued SSNs will be randomized. In other words, the only SSNs that the issue data and state won’t be validated on day one are the SSNs that have just been issued to the recently born or immigrants. Given that its likely newborns won’t be applying for credit for another 18 years, the bulk of the newly issued SSNs that organizations will see for a while are those belonging to adults who were recently issued a SSN…A growing number of applicants, but not the majority of applicants. The other bit of good news is this may actually be a good thing for all of us in the long run. While we’ll end up losing the ability to validate an applicant’s SSN issue data and state, the criminals will be at an even greater disadvantage. Consider this- Last year researchers* were able to “identify all nine digits for 8.5 percent of people born after 1988 in fewer than 1,000 attempts. For people born recently in smaller states, researchers sometimes needed just 10 or fewer attempts to predict all nine digits.” I don’t expect this change to drastically reduce third party fraud rates but over time it should eliminate one component of identity theft and ultimately benefit an organization’s Customer Information Program. *The National Science Foundation, the U.S. Army Research Office, Carnegie Melon Cylab, and the Berkman Faculty Development Fund provided support for the research. To view the entire study, please visit http://www.pnas.org/content/106/27/10975.full.pdf+html.
A recent article in the USA Today titled, “Jobs rebound will be slow”*, outlines state-by-state forecasts for the United States, as released by Moody\'s Economy.com. Although the national forecasted increase, 0.9%, reflects the expectation that unemployment will remain an issue throughout 2011, the state-level detail possesses interesting variances that should be further considered by lenders in determining their marketing and acquisition strategies. What I find intriguing, is that Moody’s forecasts job growth for several states that since the beginning of the housing decline have been the hot-spots for mortgage default and high delinquency rates. Moody’s projects job growth for Florida (+2.5%), Nevada (+1.5%), and California (+0.5%) – the so called “sand states” – with comparable growth rates to states like Texas (+2.5%) and North Carolina (+1.3%), which have not experienced the same notoriety for increased risk levels and delinquency. Should this growth transpire, then these states that have been the center of credit risk in recent years will soon become centers of opportunity for lenders, as increased employment should result in decreasing delinquency rates, improved repayment habits, and a generally more creditworthy consumer population. This shift is important, since any economic recovery will start with jobs growth, leading to increased lending, which will drive housing and a broader economic growth. As I noted above, the Moody’s forecast implies that lenders who are looking to drive growth may find that profitable portfolio segments exist in some of what appear to be the unlikeliest places. __________________ *http://www.usatoday.com/money/economy/2009-02-06-new-jobs-growth-graphic_N.htm
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.
By: Staci Baker As we approach the end of the year, and the beginning of holiday spending, consumers are looking at their budgets to determine what level of spending they can do this holiday season, or if they will need additional credit for those much wanted gifts. With that in mind, it is a great time for lenders to evaluate their portfolios to determine which consumers are the best credit risks. According to the National Retail Federation, consumer spending will be up 2.1% for the 2010 holiday season. Although still at pre-recession levels, consumer confidence is starting to re-bound. But, with an increase in consumer confidence, how will lenders meet the demand for credit, and determine the credit worthiness of potential applicants? Since the beginning of the recession there has been a demand for tools that will assist lenders in managing credit risk. One such tool is the tri-bureau VantageScore, a scoring model that is highly accurate, offers greater predictiveness, and is able to score more people. Scoring models allow lenders to predict the likelihood a consumer will default on a loan. Determining who is a qualified candidate through scoring models is only part of the equation. Each lender needs to determine what level of risk to take, and what is the cost of the credit per applicant. By assessing credit risk, having a good plan in place and knowing who the target customer is, lenders will be more prepared for the holiday season. ___________________ National Retail Federation, http://www.nrf.com/modules.php?name=News&op=viewlive&sp_id=1016
By: Wendy Greenawalt Large financial institutions have acknowledged for some time that taking a more consumer-centric versus product-centric approach can be a successful strategy for an organization. However, implementing such a strategy can be difficult, because inherently organizations want to promote a specific product for one reason or another. With the current economic unrest, organizations are looking for ways to improve customer loyalty with their most profitable and lowest risk customers. They are also looking for ways to improve offers to consumers to provide segment of one decisioning, while satisfying organizational goals. Customer management, and specifically cross-sell or up-sell strategies, are a great example of where organizations can implement what I call “segment of one decisioning”. In essence, this refers to identifying the best possible decision or outcome for a specific consumer when given multiple offers, scenarios and objectives. Marketers strive to identify the best strategies to maximize decision-making, while minimizing costs. For many, this takes the form of models and complex strategy trees or spreadsheets to identify the ideal offering for a segment of consumers. While this approach is effective, algorithm-based decisioning processes exist that can help organizations identify the optimal decisioning strategies, while considering all possible options at a consumers level. By leveraging an optimization tool, organizations can expand the decision process by considering all variables and all alternatives to find the most cost effective, most-likely-to-be-successful strategies. By optimizing decisions, marketers can determine the ideal offer, while quantifying the ROI and adhering to budgetary or other campaign constraints. Many organizations are once again focusing on account growth and building strategies to implement in the near future. With the limited pool of qualified candidates and increased competition, it is more important than ever that each consumer offer be the best to increase response rates, achieve portfolio growth goals and build a profitable portfolio.
By: Kari Michel How are your generic or custom models performing? As a result of the volatile economy, consumer behavior has changed significantly over the last several years and may have impacted the predictiveness of your models. Credit models need to monitored regularly and updated periodically in order to remain predictive. Let’s take a look at VantageScore, it was recently redeveloped using consumer behavioral data reflecting the volatile economic environment of the last few years. The development sample was compiled using two performance timeframes: 2006 – 2008, and 2007 – 2009, with each contributing 50% of the development sample. This is a unique approach and is unlike traditional score development methodology, which typically uses a single, two year time window. Developing models with data over an extended window reduces algorithm sensitivity to highly volatile behavior in a single timeframe. Additionally, the model is more stable as the development is built on a broader range of consumer behaviors. The validation results show VantageScore 2.0 outperforms VantageScore 1.0 by 3% for new accounts and 2% for existing accounts overall. To illustrate the differences that were seen in consumer behavior, the following chart and table show the consumer characteristics that contribute to a consumer’s score and compare the characteristic contributions of VantageScore 2.0 vs VantageScore 1.0. Payment History Utilization Balances Length of Credit Recent Credit Available Credit Vantage Score 2.0 28% 23% 9% 8% 30% 1% Vantage Score 1.0 32% 23% 15% 13% 10% 7% As we expect ‘payment history’ is a large portion driving the score, 28% for VantageScore 2.0 and 32% for VantageScore 1.0. What is interesting to see is the ‘recent credit’ contribution has increased significantly to 30% from 10%. There also is a shift with lower emphases on balances, 9% versus 15% as well as ‘length of credit’, 8% versus 13%. As you can see, consumer behavior changes over time and it is imperative to monitor and validate your scorecards in order to assess if they are producing the results you expect. If they are not, you may need to redevelop or switch to a newer version of a generic model.
By: Staci Baker As the economy has been hit by the hardest recession since the Great Depression, many people wonder how and when it will recover. And, once we start to see recovery, will consumer credit return to what it once was? In a recent Experian-Oliver Wyman Market Intelligence Report quarterly webinar, 70% of the respondents in a survey said they believe consumer debt will return to pre-2008 levels. Clearly, many believe that consumer spending and borrowing will return, despite the fact that consumer credit card borrowing recently declined for the 24th straight month*. Assuming that this optimism is valid, what can credit card lenders do to evaluate the risk levels of potential customers as they attempt to grow their portfolios? For lenders, determining who needs credit, as well as whom to lend to in this economic environment, can be quite challenging. However, there are many tools available to assist lenders in assessing credit risk and growing their portfolio. Many lenders look at a consumer’s credit score, such as the tri-bureau VantageScore, to evaluate their credit worthiness. By utilizing an individual’s VantageScore, a lender is able to determine potential customer risk levels. Another way to evaluate a consumer’s credit worthiness is to evaluate a population using credit attributes. Based on the attributes a lender is looking for in their portfolio, they can see improvement in evaluating risk prediction in their portfolio using pre-determined attributes, especially those specifically designed for the credit card industry. There are also models that can help lenders predict when a consumer is likely to be in the market for a new loan or account. Experian’s In the Market Models provide lenders with product-specific segmentation tools that can be combined with risk scores to enhance the efficiency and effectiveness of their offers. To identify the optimal cross-sell and line management decisions based on an individual customer’s risk score and potential value, a lender can also utilize optimization tools. Optimization, combined with a viable risk management strategy, can assist a lender to achieve a healthy portfolio growth in a highly constrained environment. Although lenders will need to determine the best method to meet their objectives, these are just a few of the many tools available that will assist them in correctly growing their lending portfolios. ____________________ * http://www.usatoday.com/money/economy/2010-10-07-consumer-credit_N.htm
With the issue of delayed bank foreclosures at the top of the evening news, I wanted to provide a different perspective on the issue and highlight what I think are some very important, yet often underestimated risks hidden within this issue. For many homeowners, the process of becoming delinquent and eventually going into default is actually a cash-flow positive experience. The process offers these borrowers temporary “free rent,” whereby a major previous monthly commitment is no longer a monthly obligation, freeing up cash for other purposes, including paying other bills. For those consumers who are managing cash flow issues each month, the lack of a mortgage commitment immediately allows them to meet other commitments more easily - making payments on credit cards and car loans that may have previously also become delinquent. From the perspective of a credit card or auto lender, the extended foreclosure process is a short-term positive – it allows a borrower who had previously struggled to remain current to now pay on time and in the short-run, contributes to portfolio health. Although these lenders will experience an improvement in delinquency rates, the reality is that the credit risk is simply dormant. At some point, the consumer’s mortgage will go into foreclosure, and which point the consumer will again be under pressure to continue meeting their obligations. The hidden and significant risk management issue is the misinterpretation of improved delinquency rates. Halting foreclosures means that an accumulating number of consumers are going to enter into this delayed stage of ‘free rent’, without any immediate prospect of having to make a rent or mortgage payment in the near future. In fact, according to Bank of America, “the average foreclosed borrower has not made a payment in 18 months”. This extended period of foreclosure delay will naturally result in a larger number of consumers being able to meet their non-mortgage obligations – but only while their free-rent status exists. A lender who has an interest in the “free rent” consumer is actually sitting on a time-bomb. When foreclosures stop or slow to a rate that is less than consumers entering it, that group will continue to grow in size - until foreclosures start again – at which point thousands of consumers will be processed and will have to start managing rent/housing payments again. Almost immediately, thousands of consumers who have had no problems meeting their obligations will have to start making decisions about which to pay and which not to pay. So, this buildup of rent-free mortgage holders presents a serious risk management issue to non-mortgage lenders that must be addressed. Lenders who have a relationship with a consumer who is delinquent on their mortgage may be easily fooled into thinking that they are not exposed to the same credit risk as mortgage lenders, but I think that these lenders will quickly find that consumers who have lived rent-free for over a year will have a very difficult time managing this transition, and if not diligent, credit card issuers and automotive lenders may find themselves in trouble. _____________________ http://cnews.canoe.ca/CNEWS/World/2010/10/08/15629836.html
By: Wendy Greenawalt In a recent poll conducted by Experian, 82 percent of the respondents indicated they were undecided or currently assessing options for complying with the Risk-Based Pricing Rule. If your organization is also considering which compliance option is right based on your unique circumstances, I would encourage you to act soon, as the deadline is quickly approaching. Some organizations have decided that they will be utilizing the Credit Score Disclosure Notice as their preferred compliance option, as it is supplied to all consumers and requires minimal procedural changes and maintenance. While at first glance this option may seem to be the most streamlined approach, it does come with its own considerations. The Disclosure Notice form letter is straightforward and includes minimal inputs such as the consumers credit score, score source, range of the score and a corresponding score distribution. The downside is that the Disclosure Notice must be provided individually to all consumers, even those that reside at the same address, and must be given in a format in which the consumer can keep/reference. This means there will be an inherently higher cost to mail or electronically provide the form to each applicant and obtain the required eSign confirmation (where applicable). The score distributions must be updated on a regular basis and lenders must be prepared to answer consumer questions related to scores and how they are derived. Conversely, the Risk Based Pricing Notice, which is the primary compliance option outlined in the rule, is provided to a specific segment of consumers and can be provided verbally, electronically or in writing. A model form is supplied in the ruling and requires a lender to provide the credit reporting agency used to obtain the consumers credit data and contact information for the agency. Some lenders feel the notice has awkward language; however I tend to think most consumers have a basic understanding of their credit and the language in the form will not provide a negative consumer experience. The language tells the consumer “the terms offered to you may be less favorable than the terms offered to consumers who have better credit histories”. The disadvantage of this notice is that a lender must determine which consumers must receive the notice, and this policy must be updated periodically. Fortunately, the ruling states that a lender must only review the policy every two years. For most lenders this will not be a problem as they perform more frequent reviews and validations of their portfolios and determining which consumers receive a notice can be performed at the same time with minimal resources. Lenders should carefully consider their compliance obligations in relation to the ruling and determine which notice is best for their organization given resource, maintenance and cost requirements. The January 1, 2011 deadline is looming and there is no indication that the effective date will be extended. I suspect the regulatory requirements will continue to evolve over the next few years with the creation of the Consumer Financial Protection Agency, which has the authority to set and enforce rules under 12 federal laws and the implications will continue to put a strain on lending institutions.
By: Kari Michel Credit bureau data has been used for many years to develop credit risk models, bankruptcy scores, profitability models, and response models to name a few. For the utility industry (water and power companies), a new score is available to help them administer more efficiently their internal low-income assistance programs. One challenge that utility companies face is to identify those consumers who clearly qualify for low-income assistance in a more automated process in order to reduce the number of applications that require manual intervention. Utility companies are starting to use scoring models to help them determine the likelihood that a customer will qualify for low-income assistance from their local utility. In a recent Experian case study, a medium-sized municipal utility company in California conducted a test using Experian’s Financial Assistance Checker to understand the benefit of using this score in their recertification process. The test showed a reduction of manual review of about 40% of the test file and they expect a 40-50% reduction in manual review in the future. The inclusion of the score in the recertification process will reduce costs and make their low income assistance program more efficient and provide an excellent example of the utility’s efforts to make a positive impact on the community.
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