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Some borrowers who are deemed subprime by traditional credit scoring criteria are actually quite creditworthy and are identified as prime or near-prime consumers when using the more inclusive VantageScore® credit score. Based on a VantageScore® Solutions' study of infrequent users of credit, 15.5 percent were found to have either prime or super-prime risk. In addition, among new entrants to the credit scene — including students who recently graduated, immigrants and recently divorced consumers — 26.5 percent were found to have either prime or super-prime risk profiles. Learn more about VantageScore® Solutions, identified as a Preferred Partner by the National Association of Federal Credit Unions (NAFCU). Source: VantageScore Solutions summer 2012 newsletter, The Score VantageScore® is owned by VantageScore Solutions, LLC.

Consumers want to hear about data breaches - Eighty five percent of respondents in a recent study say learning about the loss of their data is pertinent to them. However, when they do, 72 percent indicated that they are dissatisfied with the notification letters they receive. Companies need to take note of these findings because more than one-third of consumers who receive a notification letter contemplate ending their relationship with the company. Providing affected individuals with a membership in an identity protection product is extremely important since 58 percent of consumers consider identity protection to be favorable compensation after a breach. Learn five pitfalls to avoid in your notification letters and how Experian Data Breach Resolution can help. Source: Download the complete 2012 consumer study on data breach notification.

2011 was the 12th consecutive year that identity theft topped the list of FTC consumer complaints. Florida had the highest rate of complaints, followed by Georgia and California. Rank State Complaints per 100,000 population 1 Florida 179 2 Georgia 120 3 California 104 Learn how to detect and manage fraud activity while meeting regulatory requirements. Source: Consumer info.com infographic and FTC's Consumer Sentinel Network Data Book for January-December 2011.

The FDIC has proposed a new rule that will change the way large lenders define and calculate risk for their FDIC Deposit Insurance Assessment. The revised definitions in the proposed rule rely on "probability of default" and eliminate all references to the traditional three-digit credit score used to calculate subprime exposure -- changing the way large banks calculate their FDIC assessments. This new ruling will allow lenders to uniformly assess risk in their portfolios--regardless of the scoring models they use. View a recent webinar to hear from a panel of experts on the "The New Subprime Definition: Who is subprime now?" Source: FDIC Proposed Ruling Announcement

The pressures for both credit unions and banks, to generate returns to drive greater earnings are ever present. According to recent data released by the National Credit Union Administration, the nation's 7,019 federally-insured credit unions added 667,000 new members in the first quarter of 2012 to a record of 92.5 million. To offset these pressures, portfolio managers are aggressively expanding their policies and practices to drill more deeply and frequently into their portfolios. Increasingly, this requires the ability to trend consumer credit data, identify specific member metrics, and track those changes over time. Redefining the information your portfolios provide can by key to developing increased ROI. Learn how trended data can help you maximize your strategies and process to produce results in today's complex business environments. Source: How to drill deeper into your portfolio

The cumulative effect of Basel III is expected to have a substantial impact on capital requirements. The total minimum regulatory capital will increase from 8 percent to 10.5 percent. For institutions that are considered "systematically important," an additional holding requirement may be imposed of up to 3.5 percent. Download our white paper to learn more about how your peers are reacting to Basel III and how Experian can help banks to optimize risk-weighted assets. Source: Creating value in challenging times: An innovative approach to Basel III compliance by Experian's Global Consulting Practice

A recent survey of 1,000 representative American consumers showed that while 78 percent of respondents are aware that they have more than one credit score, some key misperceptions remain: • Fewer than half (44 percent) understand that a credit score typically measures risk of not repaying loans rather than amount of debt (22 percent), financial resources (21 percent) or other factors. • More than half still think that a person's age (56 percent) and marital status (54 percent) are factors used to calculate credit scores, and 21 percent incorrectly believe that ethnic origin is a factor. Click here to get the facts on the types of credit scores and what influences them. Source: VantageScore® press release, May 2012. VantageScore® is owned by VantageScore Solutions, LLC.

By: Joel Pruis From a score perspective we have established the high level standards/reporting that will be needed to stay on top of the resulting decisions.  But there is a lot of further detail that should be considered and further segmentation that must be developed or maintained. Auto Decisioning A common misperception around auto-decisioning and the use of scorecards is that it is an all or nothing proposition.  More specifically, if you use scorecards, you have to make the decision entirely based upon the score.  That is simply not the case.  I have done consulting after a decisioning strategy based upon this misperception and the results are not pretty.  Overall, the highest percentage for auto-decisioning that I have witnessed has been in the 25 – 30% range.  The emphasis is on the “segment”.  The segments is typically the lower dollar requests, say $50,000 or less, and is not the percentage across the entire application population.  This leads into the discussion around the various segments and the decisioning strategy around each segment. One other comment around auto-decisioning.  The definition related to this blog is the systematic decision without human intervention.  I have heard comments such as “competitors are auto-decisioning up to $1,000,000”.  The reality around such comments is that the institution is granting loan authority to an individual to approve an application should it meet the particular financial ratios and other criteria.  The human intervention comes from verifying that the information has been captured correctly and that the financial ratios make sense related to the final result.  The last statement is the key to the disqualification of “auto-decisioning”.  The individual is given the responsibility to ensure data quality and to ensure nothing else is odd or might disqualify the application from approval or declination.  Once a human eye is looking at an application, judgment comes into the picture and we introduce the potential for inconsistencies and or extension of time to render the decision.  Auto-decisioning is just that “Automatic”.  It is a yes/no decision and is based upon objective factors that if met, allow the decision to be made.  Other factors, if not included in the decision strategy, are not included. So, my fellow credit professionals, should you hear someone say they are auto-decisioning a high percent of their applications or a high dollar amount for an application, challenge, question and dig deeper.  Treat it like the fishing story “I caught a fish THIS BIG”. No financials segment The highest volume of applications and the lowest total dollar production area of any business banking/small business product set.  We had discussed the use of financials in the prior blog around application requirements so I will not repeat that discussion here.  Our focus will be on the  decisioning of these applications.  Using score and application characteristics as the primary data source, this segment is the optimal segment for auto-decisioning.  Speeds the  decision process and provides the greatest amount of consistency in the decisions rendered.  Two key areas for this segment are risk premiums and scorecard validations. The risk premium is important as you are going to accept a higher level of losses for the sake of efficiencies in the underwriting/processing of the application.  The end result is lower operational costs, relatively higher credit losses but the end yield on this segment meets the required, yet practical, thresholds for return. The one thing that I will repeat from a prior blog is that you may request financials after the initial review but the frequency should be low and should also be monitored.  The request of financials should not be the “belt and suspenders” approach.  If you know what the financials are likely to show, then don’t request them.  They are unnecessary.  You are probably right and the collection of the financials will only serve to elongate the response time, frustrate everyone involved in the process and not change the expected results. Financials segment The relatively lower unit volume but the higher dollar volume segment.  Likely this segment will have no auto-decisioning as the review of financials typically will mandate the judgmental review.  From an operational perspective, these are high dollar and thus the manual review does not push this segment into a losing proposition.  From a potential operational lift perspective, the ability to drive a higher volume of applications into auto-decisioning is simply not available as we are talking probably less than 40% (if not fewer) of all applications in this segment. In this segment, the consistency becomes more difficult as the underwriter tends to want to put his/her own approach on the deal.  Standardization of the analysis approach (at least initially) is critical for this segment.  Consistency in the underwriting and the various criteria allows for greater analysis to determine where issues are developing or where we are realizing the greatest success.  My recommended approach is to standardize (via automation in the origination platform) the various calculations in a manner that will generate the most conservative approach.  Bluntly put, my approach was to attempt to make the deal as ugly as possible and if it still passed the various criteria, no additional work was needed nor was there any need for detailed explanation around how I justified the deal/request.  Only if it did not meet the criteria using the most conservative approach would I need to do any work and only if it was truly going to make a difference. Basic characteristics in this segment include – business cash flow, personal debt to income, global cash flow and leverage.  Others may be added but on a case by case basis. What about the score?  If I am doing so much judgmental underwriting, why calculate the score in this segment?  In a nutshell, to act as the risk rating methodology for the portfolio approach. Even with the judgmental approach, we do not want to fall into the trap thinking we are going to be able to adequately monitor this segment in a proactive fashion to justify the risk rating at any point in time after the loan is booked.  We have been focusing on the origination process in this blog series but I need to point out that since we are not going to be doing a significant amount of financial statement monitoring in the small business segment, we need to begin to move away from the 1 – 8 (or 9 or 10 or whatever) risk rating method for the small business segment.  We cannot be granular enough with this rating system nor can we constantly stay on top of what may be changing risk levels related to the individual clients.  But I am going to save the portfolio management area for a future blog. Regardless of the segment, please keep in mind that we need to be able to access the full detail of the information that is being captured during the origination process along with the subsequent payment performance.  As you are capturing the data, keep in mind, the abilities to Access this data for purposes of analysis Connect the data from origination to the payment performance data to effectively validate the scorecard and my underwriting/decisioning strategies Dive into the details to find the root cause of the performance problem or success The topic of decisioning strategies is broad so please let me know if you have any specific topics that you would like addressed or questions that we might be able to post for responses from the industry.

The dramatic transformation of the financial services industry requires new advances and innovation in credit strategies to respond to the growing number of underbanked customers who need to be served. The underbanked, or unbanked, market now represents nearly 64 million U.S. consumers who have limited or no traditional credit history. Take a quiz now to test your knowledge of America's underbanked. Source: Experian News, May 2012

Previously, we looked at the various ways a dual score strategy could help you focus in on an appropriate lending population. Find your mail-to population with a prospecting score on top of a risk score; locate the riskiest of all consumers by layering a bankruptcy score with your risk model. But other than multiple scores, what other tools can be used to improve credit scoring effectiveness? Credit attributes add additional layers of insight from a risk perspective. Not everyone who scores an 850 represent the same level of risk once you start interrogating their broader profile. How much total debt are they carrying? What is the nature of it - is it mortgage or mostly revolving? A credit score may not fully articulate a consumer as high risk, but if their debt obligations are high, they may represent a very different type of risk than from another consumer with the same 850 score.  Think of attribute overlays in terms of tuning the final score valuation of an individual consumer by making the credit profile more transparent, allowing a lender to see more than just the risk odds associated with the initial score. Attributes can also help you refine offers. A consumer may be right for you in terms of risk, but are you right for them? If they have 4 credit cards with $20K limits each, they’re likely going to toss your $5K card offer in the trash. Attributes can tell us these things, and more. For example, while a risk score can tell us what the risk of a consumer is within a set window, certain credit attributes can tell us something about the stability of that consumer to remain within that risk band. Recent trends in score migration – the change in a level of creditworthiness of a consumer subsequent to generation of a current credit score – can undermine the most conservative of risk management policies. At the height of the recession, VantageScore® Solutions LLC studied the migration of scores across all risk bands and was able to identify certain financial management behaviors found within their credit files. These behaviors (signaling, credit footprint, and utility) assess the consumer’s likelihood of improving, significantly deteriorating, or maintaining a stable score over the next 12 months.  Knowing which subgroup of your low-risk population is deteriorating, or which high risk groups are improving, can help you make better decision today.

Mortgage origination volumes increased to $427 billion in Q4 2011 – a 31 percent quarterly gain. However, overall 2011 originations of $1.35 trillion were 16 percent lower than 2010 volumes. Sign up to attend our upcoming Webinar, which will focus on current credit trends and feature a closer look at the overleveraged consumer. Source: Experian-Oliver Wyman Market Intelligence Reports.

Year over year retail spend continues to trend up, translating into Bankcard balance growth and new originations. New Bankcard volumes (limits) came in at $59 billion in Q4 2011 – a 52 percent increase over the previous year. Register now for our upcoming credit trends webinar. Source: Experian Infographic: Bankcard and Retail Spending Trends.

Outstanding automotive loan balances were at $708 billion in Q1 2012 – a figure last seen two years ago. Banks and captive auto lenders hold two-thirds of the outstanding balances (34 percent and 33 percent respectively), while credit unions hold 21 percent. Listen to the latest automotive credit trends by attending our upcoming webinar. Source: Experian-Oliver Wyman Market Intelligence Reports.  

The average turnaround time to make a lending decision varies materially between financial institutions. Institutions with low-level automation are typically less competitive on price due to the higher cost of manual reviews. For customers, it leads to high levels of dissatisfaction, complaints and switching of institutions. To learn more practical insights and best practices for key areas of business banking and to look at the features of a leading-edge approach to customer management, download the full white paper. Source: Strategic customer management for business banking portfolios by Experian's Global Consulting Practice.

As part of its expanded guidance, the Office of the Comptroller of the Currency explicitly recommends that financial services firms utilizing predictive models and decision analytics run regular validations to gauge model efficacy. The VantageScore® credit score model was recently measured against the best credit score models from each of the three largest credit reporting companies (CRCs). When comparing KS values, there is exceptionally strong performance for mortgage originations, with the VantageScore® credit score model outperforming the CRC models in a range from 8 percent to 12 percent. The average range of outperformance is 3 percent to 4 percent across the board for most of the key industries. View the VantageScore® Webinar: Executing Effective Validations in 2011 and Beyond. Source: Executing Effective Validations, American Banker. VantageScore® is owned by VantageScore Solutions, LLC.