Data & Analytics

What happens when once desirable models begin to show their age? Not the willowy, glamorous types that prowl high-fashion catwalks. But rather the aging scoring models you use to predict risk and rank-order various consumer segments. Keeping a fresh face on these models can return big dividends, in the form of lower risk, accurate scoring and higher quality customers. In this post, we provide an overview of custom attributes and present the benefits of overlaying current scoring models with them. We also suggest specific steps communications companies can take to improve the results of an aging or underperforming model. The beauty of custom attributes Attributes are highly predictive variables derived from raw data. Custom attributes, like those you’ve created in house or obtained from third parties, can provide deeper insights into specific behaviors, characteristics and trends. Overlaying your scoring model with custom attributes can further optimize its performance and improve lift. Often, the older the model, the greater the potential for improvement. Seal it with a KS Identifying and integrating the most predictive attributes can add power to your overlay, including the ability to accurately rank-order consumers. Overlaying also increases the separation of “goods and bads” (referred to as “KS”) for a model within a particular industry or sub-segment. Not surprisingly, the most predictive attributes vary greatly between industries and sub-segments, mainly due to behavioral differences among their populations. Getting started The first step in improving an underperforming model is choosing a data partner—one with proven expertise with multivariate statistical methods and models for the communications industry. Next, you’ll compile an unbiased sample of consumers, a reject inference sample and a list of attributes derived from sources you deem most appropriate. Attributes are usually narrowed to 10 or fewer from the larger list, based on predictiveness Predefined, custom or do-it-yourself Your list could include attributes your company has developed over time, or those obtained from other sources, such as Experian Premier AttributesSM (more than 800 predefined consumer-related choices) or Trend ViewSM attributes. Relationship, income/capacity, loan-to-value and other external data may also be overlaid. Attribute ToolboxTM Should you choose to design and create your own list of custom attributes, Experian’s Attribute ToolboxTM offers a platform for development and deployment of attributes from multiple sources (customer data or third-party data identified by you). Testing a rejuvenated model The revised model is tested on your both your unbiased and reject inference samples to confirm and evaluate any additional lift induced by newly overlaid attributes. After completing your analysis and due diligence, attributes are installed into production. Initial testing, in a live environment, can be performed for three to twelve months, depending on the segment (prescreen, collections, fraud, non-pay, etc), outcome or behavior your model seeks to predict. This measured, deliberate approach is considered more conservative, compared with turning new attributes on right away. Depending on the model’s purpose, improvements can be immediate or more tempered. However, the end result of overlaying attributes is usually better accuracy and performance. Make your model super again If your scoring model is starting to show its age, consider overlaying it with high-quality predefined or custom attributes. Because in communications, risk prevention is always in vogue. To learn more about improving your model, contact your Experian representative. To read other recent posts related to scoring, click here.

This is the third and final post in an interview between Experian’s Tom Whitfield and Dr. Michael Turner, founder, president and CEO of the Policy and Economic Research Council (PERC)—a non-partisan, non-profit policy institute devoted to research, public education, and outreach on public and economic policy matters. In this post Dr. Turner discusses mandatory credit-information sharing for communications companies, and the value of engaging and educating state regulators. _____________________________ Does it make sense for the FTC to mandate carriers to report? Credit information sharing in the United States is a voluntary system under the Fair Credit Reporting Act (FCRA). Mandating information sharing would break precedent with this successful, decades-old regime, and could result in less rather than more information being shared, as it shifts from being a business matter to a compliance issue. Additionally, the voluntary nature of credit reporting allows data furnishers and credit bureaus to modify reporting in response to concerns. For example, in reaction to high utility bills as a result of severe weather, a utility provider may wish to report delinquencies only 60 days or more past due. Similarly, a credit bureau may not wish to load data it feels is of questionable quality. A voluntary system allows for these flexible modifications in reporting. Further, under existing federal law, those media and communications firms that decide they want to fully report payment data to one or more national credit bureaus are free to do so. In short, there is simply no need for the FTC to mandate that communications and media companies report payment data to credit bureaus, nor would there be any immediate benefit in so doing. How much of the decision is based on the influence of the State PUC or other legislative groups? Credit information sharing is federally regulated by the Fair Credit Reporting Act (FCRA). The FCRA preempts state regulators, and as such, a media or communications firm that wants to fully report may do so regardless of the preferences of the state PUC or PSC. PERC realizes the importance of maintaining good relations with oversight agencies. We recommend that companies communicate the fact of fully reporting payment data to a PUC or PSC and engage in proactive outreach to educate state regulators on the value of credit reporting customer payment data. There have been notable cases of success in this regard. Currently, just four states (CA, OH, NJ and TX) have partial prohibitions regarding the onward transfer of utility customer payment data to third parties, and none of these provisions envisioned credit reporting when drafted. Instead, most are add-ons to federal privacy legislation. Only one state (CA) has restrictions on the onward transfer of media and communications customer payment data, and again this has nothing to do with credit reporting. Agree, disagree or comment Whether you agree with Dr. Turner’s assertions or not, we’d love to hear from you. So please, take a moment to share your thoughts about full-file credit reporting in the communications industry. Click here to learn more about current and pending legislation that impacts communications providers.

By: John Straka The U.S. housing market remains relatively weak, but it’s probably not as weak as you think. To what extent are home prices really falling again? Differing Findings Most recent media coverage of the “double dip in home prices” has centered on declines in the popular Case-Schiller price index; however, the data entering into this index is reported with a lag (the just released April index reflects data for February-April) and with some limitations.  CoreLogic publishes a more up-to-date index value that earlier this month showed a small increase, and more importantly, CoreLogic also produces an index that excludes distressed sales.  This non-distressed index has shown larger recent price increases, and it shows increases over the last 12 months in 20 states. Others basing their evidence on realtors’ listing data have concluded that there was some double dip last year, but prices have actually been rising now for several months (See Altos).  These disparate findings belie overly simplistic media coverage, and they stress that “the housing market” is not one single market, of course, but a wide distribution of differing outcomes in very many local neighborhood home markets across the nation. (For a pointed view of this, see Charron.) Improved Data Sources Experian is now working with the leading source of the most granular and timely home market analytics and information, from nationwide local market data, and the best automated valuation model (AVM) provider based on these and other data, Collateral Analytics. (Their AVM leads in accuracy and geographic coverage in most large lender and third party AVM tests). While acknowledging their popularity, value, and progress, Collateral Analytics President Dr. Michael Sklarz questions the traditional dominance of repeat-sales home price indexes (from Case-Shiller etc.).  Repeat-sales data typically includes only around 20 to 30 percent of the total home sales taking place. Collateral Analytics instead studies the full market distribution of home sales and market data and uses their detailed data to construct hedonic price indexes that control for changing home characteristics.  This approach provides a similar “constant quality” claim as repeat-sales—without throwing away a high percentage of the market observations. Collateral Analytics indexes also cover over 16,000 zip codes, considerably more than others. Regular vs. Distressed Property Sales Nationwide, some well-known problem states, areas and neighborhoods continue to fare worse than most others in today’s environment, and this skewed national distribution of markets is not well described by overall averages. Indeed, on closer inspection, the recent media-touted gloomy picture of home prices that are “falling again” or that “continue to fall” is a distorted view for many local home markets, where prices have been rising a little or even more, or at least remaining flat or stable.  Nationwide or MSA averages that include distressed-property sales (as Case-Shiller tends to do) can be misleading for most markets. The reason for this is that distressed-property sales, while given much prominence in recent years and lowering overall home-price averages, have affected but not dominated most local home markets. The reporting of continued heavy price discounts (twenty percent or significantly more) for distressed sales in most areas is a positive sign of market normality.  It typically takes a significantly large buildup of distressed property sales in a local area or neighborhood home market to pull down regular property sale prices to their level.  For normal or regular home valuation, distressed sales are typically discounted due to their “fire sale” nature, “as is” sales, and property neglect or damage. This means that the non-distressed or regular home price trends are most relevant for most homes in most neighborhoods. Several examples are shown below. As suggested in these price-per-living-area charts, regular (non-distressed) home-sale prices have fared considerably better in the housing downturn than the more widely reported overall indexes that combine regular and distressed sales(1). Regular-Sale and Combined Home Prices in $ Per Square Foot of Living Area and Distress Sales as a Pct of Total Sales In Los Angeles, combined sale prices fell 46 percent peak-to-trough and are now 16 percent above the trough, while regular sale prices fell by considerably less, 33 percent, and are now 3 percent above the trough.   Distressed sales as a percent of total sales peaked at 52 percent in 2009:Q1, but then fell to a little under 30 percent by 2010:Q2, where it has largely remained (this improvement occurred before the general “robo-signer” process concerns slowed down industry foreclosures).  L.A. home prices per square foot have remained largely stable for the past two years, with some increase in distressed-sale prices in 2009. Market prices in this area most recently have tended to remain essentially flat—weak, but not declining anew, with some upward pressure from investors and bargain hunters (previously helped by tax credits before they expired). Double-Dip: No. In Washington DC, single-family home prices per square foot have been in a saw- tooth seasonal pattern, with two drops of 15-20% followed by sizable rebounds in spring sales prices. The current combined regular & REO average price is 17 percent below its peak but 13 percent above its trough, while the regular-sale average price is just 12 percent below the peak and 10 percent above its trough. Distressed sales have been comparatively low, but rising slowly to a peak of a little over 20 percent in 2010, with some slight improvement recently to the high teens. Single-family prices in DC have remained comparatively strong; however, more of the homes in DC are actually condos, and condo prices have not been quite as strong, with the market data showing mixed signals but with the average price per square foot remaining essentially flat.  Double-Dip: No. In the Miami area, the combined average home price per square foot fell by 48 percent peak to trough and is now just 1 percent above the 2009:Q2 trough. The regular-sale average price already experienced an earlier double-dip, falling by 32 percent to 2009:Q2, then stabilizing for a couple of quarters before falling another 9 percent relative to the peak; since 2010:Q3 this average has been choppy but basically flat, now 3 percent above that second trough. Prices in Miami have been among the weakest in large metro areas, but average prices have been largely flat for the past year, without any sharp new double dip. Distressed sales as a percent of the total peaked at 53 percent in 2009:Q1, but then fell to a little under 30 percent by 2010:Q2; since then there has been some return to a higher distress share, in the mid to upper 30s (but all of these figures are about 10 percentage points lower for condos).   New Double-Dip: No. The Dallas area has seen some of the strongest prices in the nation. The combined price per square foot had an earlier peak and fell by 31 percent peak to trough, but it is now 33 percent above the trough. The regular-sale average price fell briefly by 22 percent peak to trough, but it has since risen by 32 percent from the 2009:Q1 trough to where it is now 3 percent above the peak. The increases have occurred in a saw-tooth seasonal pattern with spring prices the highest, but prices here have been largely rising considerably. Distress sales as a percent of the total peaked at 22 percent in 2009:Q1 but have largely fallen since and now stand at just 11 percent.   Double-Dip: No. Here You Can See 47 More Examples of Where Double-Dips Are and Are Not: »         Pacific West »         Southwest »         Mountain West »         Midwest »        Northeast »         Mid Atlantic »         Southeast  To summarize this information and gain a little more insight into the general area conditions for most homes and individuals in the U.S., we can add up the number of homes and the total population across the counties examined.  To be sure, this information is not a rigorous random sample across homes, but I have tried to include and show the details of both stronger and weaker metro-area counties throughout the U.S. As shown in the tables below, the information used here has covered 51 metro-area counties, including a total population of over 15 million homes and nearly 75 million individuals(2).  These results may be regarded as suggestive of findings from a more thoroughgoing study. Based on these reviews of the market price averages and other data, my assessment is that a little over half of the counties examined are not currently or recently experiencing a double-dip in home prices. Moreover, these counties, where home prices appear to be at least flat or relatively stronger, encompass almost two-thirds (65%) of the total affected U.S. population examined, and nearly three-fifths (58%) of the total properties covered by the data studied. Conclusion This is, on balance, good news. But there are remaining concerns. One is the continued high, or more recently rising, shares of distressed sales in many markets, and the “shadow inventory” of distressed sales now being held up in the current foreclosure pipeline. But it is also interesting to see that many of the reductions in the distressed-property shares of total sales in high-stress areas occurred before the foreclosure processing slowdowns. Another interesting observation is that most of the recent double-dips in prices have been relatively mild compared to the previous original peak-to-trough meltdown. While, to be sure, there are plenty of reasons to remain uncertain and cautious about U.S. home prices, home markets in general do vary considerably, with significant elements of improvement and strength as well as the continuing weaknesses. Despite many reports today about “the beleaguered housing market,” there really is no such thing … not unless the report is referring to a very specific local market.  There definitely are double dips in many areas, and reasons for continuing overall concern. But the best available evidence suggests that there are actually double-dip markets—most relatively moderately so, stable markets, and stronger markets, with markets affecting a majority of homes and individuals actually in the stable and stronger categories.  Note: In a next installment, we’ll look at some more granular micro market data, to explore in greater depth the extensive variety of home-price outcomes and market conditions in weak pockets and strong pockets across various local areas and home markets. This will highlight the importance of having very good information, at sub-county and even sub-zip code levels, on local-neighborhood home markets. Source of Home Price and Market Information: Collateral Analytics HomePriceTrends. I thank Michael Sklarz for providing the extensive information for this report and for comments, and I thank Stacy Schulman for assistance in this posting. __________________ (1) Based on analysis by Collateral Analytics, price/living sq ft is a useful, simple “hedonic” measure which typically controls for around 70 percent or more of the changing characteristics in a housing stock and home sale mix. Patterns in home prices without dividing by the square footage are generally similar, but not always. (2) The property inventory counts are from Collateral Analytics, while the population estimates are from the 2010 U.S. Census.

This is the second in a three-part interview between Experian’s Tom Whitfield and Dr. Michael Turner, founder, president and CEO of the Policy and Economic Research Council (PERC)—a non-partisan, non-profit policy institute devoted to research, public education, and outreach on public and economic policy matters. Dr. Turner is a prominent expert on credit access, credit reporting and scoring, information policy, and economic development. Mr. Whitfield is the Director of Marketing for Experian’s Telecommunications, Energy and Cable practice. In this post Dr. Turner explains how full-file credit reporting actually benefits consumers and why many communications providers haven’t yet embraced it. _____________________________ Why is full-file credit reporting good for communications customers? Approximately 54 million Americans either have no credit report, or have very little information in their credit reports to generate a credit score. Most of these “thin-file/no-file” persons are financially excluded and many of them are media and communications customers. By having their payment data fully reported to a credit bureau and included in their credit reports, many will be able to access affordable sources of mainstream credit for the first time; others will be helped by repairing their damaged credit. In this way, consumers will save by not relying on high-cost lenders to have their credit needs met. Why don’t providers embrace reporting like other major industries/lenders? A major reason is inertia—providers haven’t done it before and are not sure how they would benefit from change. Just recently, PERC released a major study highlighting the business case for fully reporting customer payment data to one or more nationwide credit bureaus. This includes customer survey results, peer survey results and case studies. The results all point to tremendous upside from fully reporting payment data, with only manageable downsides—including external communications and regulators.   Misperceptions and misunderstandings Another significant reason is regulator misperceptions and misunderstandings. State public service and public utility commissions (PSCs and PUCs) aren’t experts in credit reporting or the regulatory framework around credit-information sharing. Many mistakenly believe the data is unregulated and can be used for marketing. Not wanting to contribute to an increase in commercial mail and telemarketing calls, some regulators have a knee-jerk reaction when the topic of credit reporting is raised by an interested media, communications or utility company. PERC has been working to educate regulators and has had success in their outreach efforts. PERC can be a resource to firms interested in full-file reporting in direct communications with regulators. Part 3: Wednesday, June 29 Next, in the concluding post of this interview with PERC founder, president and CEO Dr. Michael Turner, the doctor discusses mandatory credit-information sharing for communications companies, and the value of engaging and educating state regulators. Agree, disagree or comment Whether you agree with Dr. Turner’s assertions or not, we’d love to hear from you. So please, take a moment to share your thoughts about full-file credit reporting in the communications industry.

This is the first in a three-part interview between Experian’s Tom Whitfield and Dr. Michael Turner, founder, president and CEO of the Policy and Economic Research Council (PERC)—a non-partisan, non-profit policy institute devoted to research, public education, and outreach on public and economic policy matters. Dr. Turner is a prominent expert on credit access, credit reporting and scoring, information policy, and economic development. Mr. Whitfield is the Director of Marketing for Experian’s Telecommunications, Energy and Cable practice. In this post Dr. Turner discusses how communications providers and their customers can both benefit from full-file credit reporting. Comments, suggestions and differing viewpoints are welcome.   _____________________________ Why is full reporting to the bureaus so critical for communication providers? PERC’s research has found at least three good business reasons for media and communications companies to consider this practice: 1) Improved cash flow. In a survey of nearly 1,000 heads of household (those with primary bill paying responsibility), media and communications payments ranked below payments that were fully reported to credit bureaus. When asked how credit reporting would impact bill payment prioritization, half of all respondents indicated they would be “much more likely” or “more likely” to pay their media and communications bills on time. Such an outcome would represent a significant cash flow improvement. In fact, case study results substantiate this, and demonstrate further benefits from reduced delinquencies and charge offs. 2) Cost savings. In a survey of media, communications, and utilities the perceived costs of reporting payments to a bureau were, in fact, substantially greater than actual costs incurred, and perceived benefits significantly lower than actual benefits. In most cases, the actual benefits reported by firms fully reporting payment data to one or more nationwide credit bureaus were multiples higher than the actual costs, which were reported as being modest as a ratio of IT and customer service expenditures. 3) More customer loyalty, less churn. In a competitive deregulated environment, telling customers about the benefits of fully reporting payment data (building a good credit history, reducing costs of credit and insurance, increasing credit access and credit limits, improving chances of qualifying for an apartment rental or job) could result in increased loyalty and less churn. How do providers stand to benefit from reporting? Providers benefit because fully reporting payment data to a nationwide credit bureau for inclusion in credit reports actually changes customer behavior. Reporting negative-only data doesn’t affect customers in the same way, and, in the vast majority of cases, does not affect payment behavior at all, as consumers are entirely unaware of reporting or see it as a “black list.” By communicating the many customer benefits of fully reporting payment data to a credit bureau for inclusion in a credit report, the provider benefits from improved cash flow, reduced charge offs, and improved customer loyalty. Part 2: Monday, June 27 In Part 2 of this interview, Dr. Turner explains how full-file credit reporting actually benefits consumers and why many communications providers haven’t yet embraced it. The primary reason uncovered in PERC’s research may surprise you, so be sure to come back for Part 2. Agree, disagree or comment Whether you agree with Dr. Turner’s assertions or not, we’d love to hear from you. So please, take a moment to share your thoughts about full-file credit reporting in the communications industry.

This paraphrased lament from Coleridge’s Rime of the Ancient Mariner may loosely reflect the predicament facing many communications companies today: afloat on vast sea of customer information, yet, lacking resources or expertise, unable to draw from it much new or actionable intelligence. Not that data mining is ever a small or insignificant task. It isn’t. Even when resources are plentiful, obstacles can loom large—especially across numerous lines of business, where risk can multiply exponentially. Siloed data, disparate customer records and other challenges also make the work difficult, as do: The dynamic nature of consumer information Inconsistent data quality and match logic throughout the enterprise The inability to reliably link active and inactive accounts failing to identify existing customer relationships at the point of application The missing link Experian has seen many communications companies overcome these issues through database linking—that is, connecting, integrating and packaging customer information from several sources into a more cohesive and accessible structure. Linking reduces risk by identifying overlap of consumers with multiple accounts across several lines of business. It also reveals duplicate records, as well as active accounts that may be current in one line of business, but delinquent or inactive in another. The benefits The broader perspective gained through database linking can drive new efficiencies and profitability in many vital areas of your business, from fraud prevention to skip tracing and collections. Should the need arise, newly linked information can also be used to locate elusive customers or former employees for legal purposes. What you can do right now Even if resources are currently limited you can still begin discovery—the process of identifying precisely what data you have, where it resides within the enterprise, how it’s being used, and by whom. This information, perhaps combined with guidance from an experienced external service, can provide a solid foundation from which to begin leveraging (and if indicated, supplementing) existing customer data. We know communications clients who have identified millions of dollars in uncollected bad debt that was linked directly to current, active customers, using a couple of “next generation” data tools. Like the old Mariner, your in-house data has a big story to tell. Question is, are you equipped to hear it? If you like this topic, click here to read the post entitled “Leveraging Internal Data to Create a Holistic View of Your Customers.

In an attempt to out-innovate competitors, today’s communications companies seem busier than ever. The number of new products, services, devices and bundles continues to skyrocket, giving consumers more shiny new options than ever before. A double-edged sword More choices means greater opportunity to cross-sell, upsell or otherwise optimize customer value. But there is also increased risk, due to process or information gaps between internal acquisition, billing, account management and collections teams. There are also threats from the outside. Avoid being hit by “cyclers” These include hard-to-monitor, multiple-account households, and high-risk account “cyclers” who attempt to game the system by manipulating personal data; for example, providing different information when opening an account, buying a device or activating service. Undetected, such activity can severely impact corporate profitability. Fortunately, you can gain a clearer picture of both positive and negative activity by using assets and resources you already own. Extra benefits. No extra cost. The first step is working with IT to better mine internal data by linking disparate databases together (tips and best practices will be presented in future posts). This will give you a holistic view of all accounts. Experian recently did this with greater-than-expected success. In a similar effort, one utility we know identified more than $2.5 million in uncollected bad debt from current, active customers. What benefits can you expect? Besides gaining insight into driving the full value of multi-product customers, linking together internal data sources also enables you to: Illuminate resell/cross-sell opportunities and unfulfilled revenue potential Mitigate risk by identifying low value, high risk customers, and fraudulent behaviors Help in-house credit professionals “bridge the gap” with marketing and work in a more collaborative and integrated fashion Improve the customer experience across sales and support Best practices yield best results You already own the data you need. The secret to success is linking it together and putting it to work—without burdening already overworked teams. A structured set of best practices can make it happen. So what say you? What challenges does your communications company face with regard to customer data?

By: Wendy Greenawalt On any given day, US credit bureaus contain consumer trade data on approximately four billion trades. Interpreting data and defining how to categorize the accounts and build attributes, models and decisioning tools can and does change over time, due to the fact that the data reported to the bureaus by lenders and/or servicers also changes. Over the last few years, new data elements have enabled organizations to create attributes to identify very specific consumer behavior. The challenge for organizations is identifying what reporting changes have occurred and the value that the new consumer data can bring to decisioning. For example, a new reporting standard was introduced nearly a decade ago which enabled lenders to report if a trade was secured by money or real property. Before the change, lenders would report the accounts as secured trades making it nearly impossible to determine if the account was a home equity line of credit or a secured credit card. Since then, lender reporting practices have changed and, now, reports clearly state that home equity lines of credit are secured by property making it much easier to delineate the two types of accounts from one another. By taking advantage of the most current credit bureau account data, lenders can create attributes to capture new account types.  They can also capture information (such as: past due amounts; utilization; closed accounts and derogatory information including foreclosure; charge-off and/or collection data) to make informed decisions across the customer life cycle.

This post is a feature from my colleague and guest blogger, Barry Timm, Senior Process Architect in Advisory Services at Baker Hill, a part of Experian. 2008 has proven to be an unbelievably challenging year for the economy as a whole, let alone the financial industry.  Never before have we experienced the type and degree of turmoil that we did in 2008, even since the “Great Depression”. These economic challenges have been quick, severe and widespread; and, from large corporations to the individual consumer, all have been impacted to some degree.  The stock market is down, unemployment up, consumer confidence down, delinquencies up ….not exactly a pleasant roller coaster ride. And, there is no longer any projecting as to when the “bubble” is going to burst.  It happened.   Decreased real estate values have occurred not only in high impact geographic regions but throughout the country.  While home equity products have traditionally been the “golden child” of consumer loan product offerings, recent economic changes have caused a shift in that perspective.  As a result, tightened underwriting standards have limited the availability of the product as a whole.  In some markets the product offering has even been temporarily halted. We frequently hear the terminology “bailout” being used in the news.  While we all have expectations as it relates to the bailout approach, I thought I would “Google” the word “bailout” to see what would magically appear.  Interestingly enough, the first listing was titled “Walk away from your home”, with a link to the home page for a mortgage default legal team.  This is not exactly what I was expecting to find, but is definitely reflective of the times. And, according to the FDIC, there have been 25 failed financial instituions in the year 2008.  This single year number equates to the total number of failed financial institutions between the prior periods 2001 through 2007. Okay … enough doom and gloom.  In spite of all that has occurred within the economy, some financial institutions continue to maintain a strong credit quality position in their consumer portfolios and have maintained profitability throughout all of the market volatility. What are the strong survivors doing that differentiates themselves from the others? 1. They understand their portfolio.   Advisory Services frequently assists clients with various types of portfolio management analysis and often presents those findings to senior management.  We often hear that management is surprised by the results of that analysis. The point is that high-level management reporting is not enough these days. Additional detail and depth are necessary. More specifically, as opposed to evaluating payment performance at the portfolio level, it is important to consider the following: Do you know your delinquency numbers at the product level? How do delinquencies compare to your product approval rates? Do you routinely compare approval/decline rates and delinquencies to scorecard results and/or credit bureau scores? Do you know where pricing exceptions are being made and are you receiving sufficient return for the level of risk? 2. A focused strategy is in place. It is important to re-emphasize the specific, strategic direction and focus of your defined market.  Now is not the time to be “pushing the envelope” and extending into untested waters.  There is something to be said about focusing on your strengths, staying within your defined footprint and meeting the needs of your core, proven line of business while following sound financial risk management. 3. The underwriting process is under control. This does not automatically mean that a “tightening” of underwriting standards is necessary.  It does mean, however, that stronger attention to detail is warranted.  It is important that underwriting criteria is reviewed and that you are sure that defined underwriting practices are consistently applied.  As noted in item number one above, this may require digging a little deeper and reviewing current and past decisioned loans (preferably with a critical eye of an independent third party).  Assessing the underwriting process becomes increasing complex and more critical with a decentralized underwriting approach. Focus on the positive Now that 2008 is behind us, let’s continue to focus on the positives to come in 2009.  Reflect on the past, but strive to center your attention on ongoing portfolio monitoring, financial risk management assessments and improvements for the future.