All posts by Guest Contributor
By: Staci Baker For the one-third of the U.S. population that rents, in the past, rental payment history has not been included in determining a credit score. With the acquisition of RentBureau by Experian, renters’ credit can now be affected by on-time payments or account delinquency, the same as an individual that owns a home. Why is it important to include rental payment history? Including rental payment history in credit score data strengthens the analytics used to compile credit scores by giving a more complete picture of an individual’s payment history. For consumers with no history on which to build a credit score, this allows them to create track record of continuous, on time, repayment. I believe the power this brings to multi-family owned units is the ability to quickly and easily determine who is either a low credit risk, or higher credit risk when leasing an apartment. As a property manager or resident screener, the risk that is taken on new tenants can be high. There are many unknown variables regarding a tenant’s credit worthiness, even once an application is completed – do they have a good history of making payments on time, did they fill out their application truthfully, will they be a good neighbor and many more. Now that the credit risk management of applicants includes rental payment history in the consumer credit file, it will identify better quality residents, reduce delinquency rates and lead to greater collections management.
US interest rates are at historically low levels, and while many Americans are taking advantage of the low interest rates and refinancing their mortgages, a great deal more are struggling to find jobs, and unable to take advantage of the rate- friendly lending environment. This market however, continues to be complex as lenders try to competitively price products while balancing dynamic consumer risk levels, multiple product options and minimize the cost of acquisition. Due to this, lenders need to implement advanced risk-based pricing strategies that will balance the uncertain risk profiles of consumers while closely monitoring long-term profitability as re-pricing may not be an option given recent regulatory guidelines. Risk-based pricing has been a hot topic recently with the Credit Card Act and Risk-Based Pricing Rule regulation and pending deadline. For lenders who have not performed a new applicant scorecard validation or detailed portfolio analysis in the last few years now is the time to review pricing strategies and portfolio mix. This analysis will aid in maintaining an acceptable risk level as the portfolio evolves with new consumers and risk tiers while ensuring short and long-term profitability and on-going regulatory compliance. At its core, risk-based pricing is a methodology that is used to determine the what interest rate should be charged to a consumer based on the inherent risk and profitability present within a defined pricing tier. By utilizing risk-based pricing, organizations can ensure the overall portfolio is profitable while providing competitive rates to each unique portfolio segment. Consistent review and strategy modification is crucial to success in today’s lending environment. Competition for the lowest risk consumers will continue to increase as qualified candidate pools shrink given the slow economic recovery. By reviewing your portfolio on a regular basis and monitoring portfolio pricing strategies closely an organization can achieve portfolio growth and revenue objectives while monitoring population stability, portfolio performance and future losses.
By: Kristan Frend Last week I came across a news article that said the NYPD arrested 26 people who allegedly took at least $5 million from stealing identities. What I found most disturbing was that criminals allegedly affected more than 200 soldiers, including many of whom were unaware of what was happening, since they were serving overseas. To help reduce the risk of identity theft and minimize fraud losses, all three major credit bureaus provide Active- Duty Alerts, which allow deployed soldiers to have their credit frozen while they are overseas. While these fraud alerts, coupled with financial institutions implementing identity theft programs, can help prevent identity theft losses, what is being done to reduce the risk of military personnel data being exposed and stolen? As social security numbers play a key role in identity theft, I was surprised and disturbed to learn that government issued military ID cards include the card holder’s social security number in full on the front. This creates an obvious security vulnerability to the card holder. Especially considering that the military ID card must be shown in a number of situations, such as getting on and off base, medical care, picking up prescriptions, entering a base shopping exchange, mess hall, etc. There are many situations where the service member encounters people in positions that were once filled by military personnel but are now filled by civilians, who may not have the same code of honor toward others in the military community. While it’s true that thieves are increasingly using computer hacking, phishing, malware, spyware and key stroke loggers to gather SSNs, thieves still resort to low-tech methods like dumpster diving, mail tampering, and purse and wallet theft to obtain privacy sensitive information. The need to show ID so often and the fact that it contains all of their pertinent data, puts service members at particular risk when they may be in harm’s way, focused more on missions than money missing from their bank account. The good news is that the Department of Defense launched a Social Security Number reduction initiative consisting of a phased removal of SSNs. Phase one, removal of dependent SSNs from ID cards is underway. Phase two, removal of printed SSNs from all cards has been placed on hold indefinitely, and phase three, removal of SSNs embedded in barcodes will begin in 2012. My point is not to be critical of the use of SSNs; I think we all can agree that the use of SSNs have become an integral part of our culture. However, we should look to see that organizations carefully balance the value of how SSNs are used with the vulnerabilities that its use creates. The old adage “an ounce of prevention is worth a pound of cure” could never be truer than with identity theft. The easiest way to minimize fraud is to avoid it by not giving criminals the opportunity to perpetrate identity theft against individuals.
By: Kennis Wong Several weeks ago, I attended and presented at Experian’s sold-out annual conference, Vision, in Phoenix, Arizona. One of the guest speakers was Malcolm Gladwell, best-selling author of The Tipping Point, Blink, Outliers and What the Dog Saw: And Other Adventures. Since I\'ve read three of his four books, I could be considered a fan. And yes, his hair did look as wild in person as it appears in the pictures on the insides of his book covers. But that was not why I was so impressed by his speech. The real reason was that his topic was so relevant to how Experian Decision Analytics delivers value to our clients. Gladwell spent the whole hour addressing the difference between “puzzle” and “mystery”, providing abundant examples for both. The puzzle-versus-mystery topic was from one of his articles in The New Yorker. To solve a puzzle, one or more pieces of information are needed. The source of the problem is that insufficient data is available to have a conclusive answer to the question. An example would be finding Osama Bin Laden’s whereabouts. We simply do not have enough information to locate him, and we need more intelligence. On the other hand, a mystery is not solved by simply gathering more information. It is a matter of making sense out of a massive amount of data available, using analysis and judgment. Enron’s creative accounting was an example of a mystery. All the information was out in the open. Pages and pages of SEC filings and annual reports were there for anyone who was willing and able to analyze them. All that was needed to solve the mystery was to make sense out of the data. In the Fraud and Identity Solutions team, we satisfy clients’ needs by providing solutions for both puzzles and mysteries to fend off fraudsters. Besides the core credit bureau data, we have demographic data, fraud consortium data, past application data, automotive data and much more. We also have strategic partnerships to deliver demand deposit account, cell phone, and device data. All these data sources ensure that our clients get the data they need to piece the puzzle together. Our consulting and analytics, on the other hand, help clients to solve mysteries. Looking at individual pieces of disparate data is inefficient and provides little or no value. That’s why our numerous scoring solutions combine the available data in a way that is most predictive of various fraud outcomes. For example, our Precise ID Score and Fraud Shield Score Plus predict first- and third-party fraud; our BustOut Score predicts the likelihood of bust outs; our Never Pay score predicts the likelihood of a consumer never making a payment. As more data are available, we incorporate them into existing or new models if it increases the effectiveness of the models. So we have both the puzzle and mystery grounds covered. A note to Malcolm Gladwell: Great job at Vision! If you write a book about this topic, I’ll definitely buy it.
By: Kari Michel Credit risk models are used by almost every lender, and there are many choices to choose from including custom or generic models. With so many choices how do you know what is best for your portfolio? Custom models provide the strongest risk prediction and are developed using an organization’s own data. For many organizations, custom models may not be an option due to the size of the portfolio (may be too small), lack of data including not enough bads, time constraints, and/or lack of resources. If a custom model is not an option for your organization, generic bureau scoring models are a very powerful alternative for predicting risk. But how can you understand if your current scoring model is the best option for you? You may be using a generic model today and you hear about a new generic model, for example VantageScore. How do you determine if the new model is more predictive than your current model for your portfolio? The best way to understand if the new model is more predictive is to do a head-to-head comparison – a validation. A validation requires a sample of accounts from your portfolio including performance flags. An archive is pulled from the credit reporting agency and both scores are calculated from the same time period and a performance chart is created to show the comparison. There are two key performance metrics that are used to determine the strength of the model. The KS (Komogorov-Smirnov) is a statistical term that measures the maximum difference between the bad and good cumulative score distribution. The KS range is from 0% to 100%, with the higher the KS the stronger the model. The second measurement uses the bad capture rate in the bottom 5%, 10% or 15% of the score range. A stronger model will provide better risk prediction and allow an organization to make better risk decisions. Overall, when stronger scoring models are used, organizations will be best prepared to decrease their bad rates and have a more profitable portfolio.
By: Wendy Greenawalt In my last blog, I discussed the Risk-Based Pricing Rule and provided an overview of the risk based pricing notice compliance option. In this blog, I will provide a re-cap of the compliance Risk-Based Pricing notice and talk about the Credit Score Disclosure exception compliance option in more detail. When the Risk-Based Pricing Rule went into effect in January 2010, the Federal Reserve Board and Federal Trade Commission outlined two distinct compliance options available to lenders. The first option is a risk based pricing notice, which must be provided to a specific segment of consumers who “receive terms that are materially less favorable than the terms available to a substantial portion of consumers”. The notice also provides consumers with general information about credit reports, how lenders use them to make lending decisions and how to obtain a copy of their credit report. The second compliance option is a credit score disclosure exception. This option requires lenders to provide a disclosure to all consumers associated with a new account and must be in a written format that can be retained by the consumer for reference. The credit score disclosure provides consumers with the credit score that was used in conjunction with the lending decision, the range of scores for the credit score used and a national score distribution that enables consumers to compare their score to the scores of other consumers. The disclosure also contains key factors that adversely affected the consumers’ credit score and information about how to obtain a copy of their credit report. Some lenders who want to streamline compliance or those who have a concerned with the messaging contained in the Risk-Based Pricing notice may prefer this option. Either way, both compliance options should be carefully evaluated by lenders to ensure an effective compliance program is implemented. Model forms have been provided for both compliance options, which will assist lenders in complying, but implementing the new forms into existing processes and systems will require time, effort and cost for most lenders.
By: Staci Baker With the increase in consumer behaviors such as ‘strategic default’, it has become increasingly difficult during the past few years for lenders to determine who the most creditworthy consumers are – defining consumers with the lowest credit risk. If you define risk as ‘the likelihood of [a consumer] becoming 90 days or more past due’, the findings are alarming. From June 2007 to June 2009, Super Prime consumers (those scoring 900 or higher) in the U.S. have gone from an average VantageScore* of 945 to 918, which increased their risk level from approx. 0.12% to 0.62% - an increase of 417% for this highly sought after population! Prime and near prime risk levels increased by 400% and 96% respectively. Whereas subprime consumers with few choices (stay subprime or improve their score), saw a slight decrease in risk, 8% - increasing their average VantageScore from 578 to 599. So how do lenders determine who to lend to, when the risk level for all credit tiers increases, or remain risky? In today’s dynamic economy, lenders need tools that will give them an edge, and allow them to identify consumer trends quickly. Incorporating analytic tools, like Premier Attributes, into lender’s origination models, will allow them to pinpoint specific consumer behavior, and provide segmentation through predefined attribute sets that are industry specific and target profitable accounts to improve acquisition strategies. As risk levels change, maintaining profitability becomes more difficult due to shrinking eligible consumer pools. By adding credit attributes, assessing credit risk both within an organization and for new accounts will be simplified and allow for more targeted prospects, thus maximizing prospecting strategies across the customer lifecycle and helping to increase profitability. * VantageScore®, LLC, May, 2010, “Finding Creditworthy Consumers in a Changing Economic Climate”
--By Wendy Greenawalt Recently the Federal Reserve Board and Federal Trade Commission issued a new rule requiring any lender who utilizes a credit report or score when making a credit decision to provide consumers with a risk-based pricing notice. The new regulation goes into effect on January 1, 2011, but lenders must begin the planning process now--as compliance will require potential changes to their current lending practices. The regulation is another evolution in an attempt to provide consumers with more visibility to their credit history and the impact a blemished record may have on their finances. The ruling is good for consumers, but will require lenders to modify existing lending processes and add another consumer disclosure, as well as additional costs to the lending process. The risk-based pricing rule provides lenders with two compliance options--the risk-based pricing notice or a credit score disclosure exception. In this blog, I will discuss the primary compliance option, the risk-based pricing notice. The risk-based pricing notice is a document that notifies consumers that the terms of their new credit account are materially less favorable than the most favorable terms. The notice will not be provided to all consumers, but rather just those that receive account terms that are worse than what is offered to the most credit worthy consumers. Determining who will receive the notice has been outlined in the rule, and lenders can use several options including the direct comparison, credit score proxy or tiered pricing method. For lenders that perform regular validation of their portfolio, determining which consumers to issue a notice to should not be difficult. However, for those lenders who do not perform regular scorecard performance monitoring, this is another reminder of the importance of on-going validations and monitoring. As the economy continues to recover and lenders begin to re-enter the market, it will be more important than ever to validate that scores are performing as expected to manage risk and revenue goals. In my next blog, I will discuss the credit score disclosure exception.
By: Kristan Frend I recently gave a presentation on small business fraud at the annual National Association of Credit Managers (NACM) Credit Congress. Following the session, several B2B credit professionals shared recent fraud issues The attendees confirmed what we’ve been hearing from our customers: fraudsters are shifting from consumer to business/commercial fraud and they’re stepping up their game. One of the schemes mentioned by an attendee included fraudsters obtaining parcel provider’s tracking numbers to reroute shipments meant for their B2B customer. The perpetrator calls the business’s call center, impersonates the legitimate business customer to place an order, obtains the tracking number, and then calls back with the tracking number to request that the shipment be rerouted. Often the new shipping location is a residential address where an individual has been recruited for a work-at-home employment opportunity. The individual is instructed to sign for deliveries and then reship merchandise to a freight company within the country or directly to destinations outside the United States. The fraud is uncovered once the legitimate B2B customer receives an invoice for goods which they never ordered or received. I encourage you to take a look at your business’s policies and procedures on handling change of address shipment requests. What tools do you employ to verify the individual making the request? Are you verifying who the new address belongs to? You may also want to ask your parcel provider about account setting options available for when your employees submit reroute requests. While a shipping reroute request isn’t always indicative of fraud, I recommend you assess your fraud risk and consider whether your fraud-related business processes need refining. Keep an eye out here for postings on these topics: known fraud, bust out fraud, and how best to minimize fraud loss.
By: Staci Baker As more people have become underwater on their mortgage, the decision to stay or not stay in their home has evolved to consider a number of influences that impact consumer credit decisions. Research is revealing that much of an individual’s decision to meet his credit obligations is based on his trust in the economy, moral obligation, and his attitude about delinquency and the effect it will have on his credit score. Recent findings suggest that moral obligation keeps the majority of homeowners from walking away from their homes. According to the 2009 Fannie Mae National Housing Survey (i) – “Nearly nine in ten Americans (88%), including seven in ten who are delinquent on their own mortgages, do not believe it is acceptable for people to stop making payments on an underwater mortgage, while 8% believe it is acceptable.” It appears that there is a sense of owning up to one’s responsibilities; having signed a contract and the presumed stigma of walking away from that obligation. Maintaining strong creditworthiness by continuing to make payments on an underwater mortgage is motivation to sustain mortgage payments. “Approximately 74% of homeowners believe it is very important to maintain good credit and this can be a factor in encouraging them not to walk away (ii).” Once a homeowner defaults on their mortgage, their credit score can drop 150 to 250 points (iii), and the cost of credit in the future becomes much higher via increased interest rates once credit scores trend down. Although consumers expect to keep investing in the housing market (70% said buying a home continues to be one of the safest investments available (iv)) they will surely continue optimizing decisions that consider both the moral and credit implications of their decisions. i December, 2009, Fannie Mae National Housing Survey ii 4/30/10, Financial Trust Index at 23% While Strategic Defaults Continue to Rise, The Chicago Booth/Kellogg School Financial Trust Index iii http://www.creditcards.com/credit-card-news/mortgage-default-credit-scores-1270.php iv December, 2009, Fannie Mae National Housing Survey
By: Kari Michel The Federal Reserve’s decision to permit card issuers to use income estimation models to meet the Accountability, Responsibility, and Disclosure (CARD) Act requirements to assess a borrower’s ability to repay a loan makes good sense. But are income estimation models useful for anything other than supporting compliance with this new regulation? Yes; in fact these types of models offer many advantages and uses for the financial industry. They provide a range of benefits including better fraud mitigation, stronger risk management, and responsible provision of credit. Using income estimation models to understand your customers’ complete financial picture is valuable in all phases of the customer lifecycle, including: • Loan Origination – use as a best practice for determining income capacity • Prospecting – target customers within a specific income range • Acquisitions – set line assignments for approved customers • Account Management – assess repayment ability before approving line increases • Collections – optimize valuation and recovery efforts One of the key benefits of income estimation models is they validate consumer income in real time and can be easily integrated into current processes to reduce expensive manual verification procedures and increase your ROI. But not all scoring models are created equal. When considering an income estimation model, it’s important to consider the source of the income data upon which the model was developed. The best models rely on verified income data and cover all income sources, including wages, rent, alimony, and Social Security. To lean more about how income estimation models can help with risk management strategies, please join the following webinar: Ability to pay: Going beyond the Credit CARD on June 8, 2010. http://www.bulldogsolutions.net/ExperianConsumerInfo/EXC1001/frmRegistration.aspx?bdls=24143
By: Kari Michel Credit quality deteriorated across the credit spectrum during the recession that began in December, 2007. As the recession winds down, lenders must start strategically assessing credit risk and target creditworthy consumer segments for lending opportunities, while avoiding those segments where consumer credit quality could continue to slip. Studies and analyses by VantageScore Solutions, LLC demonstrate that there are more than 60 million creditworthy borrowers in the United States - 7 million of whom cannot be identified using standard scoring models. Leveraging methods using VantageScore® in conjunction with consumer credit behaviors can effectively identify profitable opportunities and segments that require increased risk mitigation thus optimizing decisions. VantageScore Solutions examined how consumers credit scores changed over a 12 month period. The study focused on three areas of consumer behavior: Stable: consumers that stay within the same credit tier for one year Improving: consumers that move to a higher credit tier in any quarter and remain at a high credit tier for the remainder of the timeframe Deteriorating: consumers that move to a lower credit tier in any quarter and remain at a lower credit tier for the remainder of the timeframe Through a segmentation approach, using the three credit behaviors above and credit quality tiers, emerges a clearer picture into profitable segments for acquisitions and existing account management strategies. Download the white paper, “Finding creditworthy consumers in a changing economic climate”, for more information on finding creditworthy consumers from VantageScore Solutions. Lenders can use a similar segmentation analysis on their own population to identify pockets of opportunity to move beyond recession-based management strategies and intelligently re-enter into the world of originations and maximize portfolio profitability.
By: Wendy Greenawalt The auto industry has been hit hard by this Great Recession. Recently, some good news has emerged from the captive lenders, and the industry is beginning to rebound from the business challenges they have faced in the last few years. As such, many lenders are looking for ways to improve risk management and strategically grow their portfolio as the US economy begins to recover. Due to the economic decline, the pool of qualified consumers has shrunk, and competition for the best consumers has significantly increased. As a result, approval terms at the consumer level need to be more robust to increase loan origination and booking rates of new consumers. Leveraging optimized decisions is a way lenders can address regional pricing pressure to improve conversion rates within specific geographies. Specifically, lenders can perform a deep analysis of specific competitors such as captives, credit unions and banks to determine if approved loans are being lost to specific competitor segments. Once the analysis is complete, auto lenders can leverage optimization software to create robust pricing, loan amount and term account strategies to effectively compete within specific geographic regions and grow profitable portfolio segments. Optimization software utilizes a mathematical decisioning approach to identify the ideal consumer level decision to maximize organizational goals while considering defined constraints. The consumer level decisions can then be converted into a decision tree that can be deployed into current decisioning strategies to improve profitability and meet key business objectives over time.
By: Staci Baker With the shift in the economy, it has become increasingly more difficult to gauge -- in advance -- what a consumer is going to do when it comes to buying an automobile. However, there are tools available that allow auto lenders to gain insight into auto loans/leases that were approved but did not book, and for assessing credit risk of their consumers. By gaining competitive insight and improving risk management, an auto lender is able to positively impact loan origination strategies by determining the proper loan or lease term, what the finance offer should be and proactively address each unique market and risk segment. As the economy starts to rebound, the auto industry needs to take a more proactive approach in the way its members acquire business; the days of business-as-usual are gone. All factors except the length of the loan being the same, if one auto dealer is extending 60-month loans per its norm and the dealer down the road is extending 72-month loans, a consumer may choose the longer loan period to help conserve cash for other items. This is one scenario for which auto dealers could leverage Experian’s Auto Prospect Intelligence(SM). By performing a thorough analysis of approved loans that booked with other auto lenders, and their corresponding terms, auto lenders will receive a clear picture of who they are losing their loans to. This information will allow an organization to compare account terms within specific peer group or institution type (captive/banks/credit union) and address discrepancies by creating more robust pricing structures and enhanced loan terms, which will result in strategic portfolio growth.
By: Wendy Greenawalt Optimization has become somewhat of a buzzword lately being used to solve all sorts of problems. This got me thinking about what optimizing decisions really means to me? In pondering the question, I decided to start at the beginning and really think about what optimization really stands for. For me, it is an unbiased mathematical way to determine the most advantageous solution to a problem given all the options and variables. At its simplest form, optimization is a tool, which synthesizes data and can be applied to everyday problems such as determining the best route to take when running errands. Everyone is pressed for time these days and finding a few extra minutes or dollars left in our bank account at the end of the month is appealing. The first step to determine my ideal route was to identify the different route options, including toll-roads, factoring the total miles driven, travel time and cost associated with each option. In addition, I incorporated limitations such as required stops, avoid main street, don’t visit the grocery store before lunch and must be back home as quickly as possible. Optimization is a way to take all of these limitations and objectives and simultaneously compare all possible combinations and outcomes to determine the ideal option to maximize a goal, which in this case was to be home as quickly as possible. While this is by its nature a very simple example, optimizing decisions can be applied to home and business in very imaginative and effective means. Business is catching on and optimization is finding its way into more and more businesses to save time and money, which will provide a competitive advantage. I encourage all of you to think about optimization in a new way and explore the opportunities where it can be applied to provide improvements over business-as-usual as well as to improve your quality of life.
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