Financial Services

By: Joel Pruis Small Business Application Requirements The debate on what constitutes a small business application is probably second only to the ongoing debate around centralized vs. decentralized loan authority (but we will get to that topic in a couple of blogs later). We have a couple of topics that need to be considered in this discussion, namely: 1.     When is an application an application? 2.     Do you process an incomplete application? When is an application an application? Any request by a small business with annual sales of $1,000,000 or less falls under Reg B.  As we all know because of this regulation we have to maintain proper records of when we received an application and when a decision on the application was made as well as communicated to the client. To keep yourself out of trouble, I recommend that there be a small business application form (paper or electronic) and that you have clearly stated the information required for a completed application in your small business application procedures. The form removes ambiguities in the application process and helps with the compliance documentation. One thing is for certain – when you request a personal credit bureau on the small business owner(s)/guarantor(s) and you currently do not have any credit exposure to the individual(s) – you have received an application and to this there is no debate. Bottom line is that you need to define your application and do so using objective criteria. Subjective criteria leaves room for interpretation and individual interpretation leaves doubt in the compliance area. Information requirements Whether or not you use a generic or custom small business scorecard or no scorecard at all, there are some baseline data segments that are important to collect on the small business applicant: ·         Requested amount and purpose for the funds ·         Collateral (if necessary based upon the product terms and conditions) ·         General demographics on the business o    Name and location o    Business Entity type (corporation, llc, partnership, etc.) o    Product and/or service provided o    Length of time in business o    Current banking relationship ·         General demographics on the owners/guarantors o    Names and addresses o    Current banking relationship o    Length of time with the business ·         External data reports on the business and/or guarantors o    Business Report o    Personal Credit Bureau on the owners/guarantors ·         Financial Statements (?) – we’ll talk about that in part II of this post. The demographics and the existing banking relationship are likely not causing any issues with anyone and the requested amount and use of funds is elementary to the process. Probably the greatest debate is around the collection of financial information and we are going to save that debate for the next post. The non-financial information noted above provides sufficient data to pull personal credit bureaus on the owners/guarantors and the business bureau on the actual borrower. We have even noted some additional data informing us the length of time the business has been in existence and where the banking relationship is currently held for both the business and the owners. But what additional information should be requested or should I say required? We have to remember that the application is not only to support the ability to render a decision but also supports the ability to document the loan and maybe even serve as a portion of the loan documentation.  We need to consider the following: ·         How standardized are the products we offer? ·         Do we allow for customization of collateral to be offered? ·         Do we have standard loan/fee pricing? ·         Is automatic debit for the loan payments required? Optional? Not available? ·         Are personal guarantees required? Optional? We again go back to the 80/20 rule. Product standardization is beneficial and optimal when we have high volumes and low dollars. The smaller the dollar size of the request/relationship the more standardized we need to have our products and as a result our application can be more streamlined. When we do not negotiate rate, we do not need to have a space to note requested rate. When we do not negotiate on personal guarantees we always require the personal financial information be collected on all owners of the business (some exceptions for very small ownership interests). Auto-debit for the loan payments means we always need to have some form of a DDA account with our institution. I think you get the point that for the highest volume of applications we standardize and thus streamline the process through the removal of ambiguity. Do you process an incomplete application? The most common argument for processing an incomplete application is that if we know we are going to decline the application based upon information on the personal credit bureau, why go through the effort of collecting and spreading the financial information. Two significant factors make this argument moot:   customer satisfaction and fair lending regulation. Customer satisfaction This is based upon the ease of doing business with the financial institution. More specifically the number of contact points or information requests that are required during the process. Ideally the number of contact points that are required once the applicant has decided to make a financing request should be minimal the information requirements clearly communicated up front and fully collected prior to rendering a decision. The idea that a quick no is preferable to submitting a full application actually is working to make the declination process more efficient than the actual approval process. So in other words we are making the process more efficient and palatable for those clients we do NOT consider acceptable versus those clients that ARE acceptable. Secondly, if we accept and process incomplete applications, we are actually mis-prioritizing the application volume. Incomplete applications should never be processed ahead of completed packages yet under the quick no objective, the incomplete application is processed ahead of completed applications simply based upon date and time of submission. Consequently we are actually incenting and fostering the submission of incomplete applications by our lenders. Bluntly this is a backward approach that only serves to make the life of the relationship manager more efficient and not the client. Fair lending regulation This perspective poses a potential issue when it comes to consistency.  In my 10 years working with hundreds of financial institutions, only a very small minority of times have I encountered a financial institution that is willing to state with absolute certainty that a particular characteristic will cause an application to e declined 100% of the time. As a result, I wish to present this scenario: ·         Applicant A provides an incomplete application (missing financial statements, for example). o    Application is processed in an incomplete status with personal and business bureaus pulled. o    Personal credit bureau has blemishes which causes the financial institution to decline the application o    Process is complete ·         Applicant B provides a completed application package with financial statements o    Application is processed with personal and business bureaus pulled, financial statements spread and analysis performed o    Personal credit bureau has the same blemishes as Applicant A o    Financial performance prompts the underwriter or lender to pursue an explanation of why the blemishes occurred and the response is acceptable to the lender/underwriter. Assuming Applicant A had similar financial performance, we have a case of inconsistency due to a portion of the information that we “state” is required for an application to be complete yet was not received prior to rendering the decision. Bottom line the approach causes doubt with respect to inconsistent treatment and we need to avoid any potential doubt in the minds of our regulators. Let’s go back to the question of financial statements. Check back Thursday for my follow-up post, or part II, where we’ll cover the topic in greater detail.

By: Joel Pruis The debate on what constitutes a small business application is probably second only to the ongoing debate around centralized vs. decentralized loan authority (but we will get to that topic in a couple of blogs later).  We have a couple of topics that need to be considered in this discussion, namely:      1.      When is an application an application?      2.     Do you process an incomplete application? When is an application an application? Any request by a small business with annual sales of $1,000,000 or less falls under Reg B.  As we all know because of this regulation we have to maintain proper records of when we received an application and when a decision on the application was made as well as communicated to the client.  To keep yourself out of trouble, I recommend that there be a small business application form (paper or electronic) and that you have clearly stated the information required for a completed application in your small business application procedures.  The form removes ambiguities in the application process and helps with the compliance documentation. One thing is for certain – when you request a personal credit bureau on the small business owner(s)/guarantor(s) and you currently do not have any credit exposure to the individual(s) – you have received an application and to this there is no debate. Bottom line is that you need to define your application and do so using objective criteria.  Subjective criteria leaves room for interpretation and individual interpretation leaves doubt in the compliance area. Information requirements Whether or not you use a generic or custom small business scorecard or no scorecard at all, there are some baseline data segments that are important to collect on the small business applicant: Requested amount and purpose for the funds Collateral (if necessary based upon the product terms and conditions) General demographics on the business Name and location Business Entity type (corporation, llc, partnership, etc.) Product and/or service provided Length of time in business Current banking relationship General demographics on the owners/guarantors Names and addresses Current banking relationship Length of time with the business External data reports on the business and/or guarantors Business Report Personal Credit Bureau on the owners/guarantors Financial Statements (??) – we’ll talk about that in part II of this post. The demographics and the existing banking relationship are likely not causing any issues with anyone and the requested amount and use of funds is elementary to the process.  Probably the greatest debate is around the collection of financial information and we are going to save that debate for the next post. The non-financial information noted above provides sufficient data to pull personal credit bureaus on the owners/guarantors and the business bureau on the actual borrower.  We have even noted some additional data informing us the length of time the business has been in existence and where the banking relationship is currently held for both the business and the owners.  But what additional information should be requested or should I say required? We have to remember that the application is not only to support the ability to render a decision but also supports the ability to document the loan and maybe even serve as a portion of the loan documentation.  We need to consider the following: How standardized are the products we offer? Do we allow for customization of collateral to be offered? Do we have standard loan/fee pricing? Is automatic debit for the loan payments required?  Optional? Not available? Are personal guarantees required?  Optional? We again go back to the 80/20 rule.  Product standardization is beneficial and optimal when we have high volumes and low dollars.  The smaller the dollar size of the request/relationship the more standardized we need to have our products and as a result our application can be more streamlined.  When we do not negotiate rate, we do not need to have a space to note requested rate.  When we do not negotiate on personal guarantees we always require the personal financial information be collected on all owners of the business (some exceptions for very small ownership interests).  Auto-debit for the loan payments means we always need to have some form of a DDA account with our institution.  I think you get the point that for the highest volume of applications we standardize and thus streamline the process through the removal of ambiguity. Do you process an incomplete application? The most common argument for processing an incomplete application is that if we know we are going to decline the application based upon information on the personal credit bureau, why go through the effort of collecting and spreading the financial information.  Two significant factors make this argument moot: customer satisfaction and fair lending regulation. Customer satisfaction This is based upon the ease of doing business with the financial institution.  More specifically the number of contact points or information requests that are required during the process.  Ideally the number of contact points that are required once the applicant has decided to make a financing request should be minimal the information requirements clearly communicated up front and fully collected prior to rendering a decision.  The idea that a quick no is preferable to submitting a full application actually is working to make the declination process more efficient than the actual approval process.  So in other words we are making the process more efficient and palatable for those clients we do NOT consider acceptable versus those clients that ARE acceptable.  Secondly, if we accept and process incomplete applications, we are actually mis-prioritizing the application volume.  Incomplete applications should never be processed ahead of completed packages yet under the quick no objective, the incomplete application is processed ahead of completed applications simply based upon date and time of submission.  Consequently we are actually incenting and fostering the submission of incomplete applications by our lenders.  Bluntly this is a backward approach that only serves to make the life of the relationship manager more efficient and not the client. Fair lending regulation This perspective poses a potential issue when it comes to consistency.  In my 10 years working with hundreds of financial institutions, only a very small minority of times have I encountered a financial institution that is willing to state with absolute certainty that a particular characteristic will cause an application to e declined 100% of the time.  As a result, I wish to present this scenario: Applicant A provides an incomplete application (missing financial statements, for example).  {C}Application is processed in an incomplete status with personal and business bureaus pulled. Personal credit bureau has blemishes which causes the financial institution to decline the application Process is complete Applicant B provides a completed application package with financial statements Application is processed with personal and business bureaus pulled, financial statements spread and analysis performed Personal credit bureau has the same blemishes as Applicant A Financial performance prompts the underwriter or lender to pursue an explanation of why the blemishes occurred and the response is acceptable to the lender/underwriter. Assuming Applicant A had similar financial performance, we have a case of inconsistency due to a portion of the information that we “state” is required for an application to be complete yet was not received prior to rendering the decision.  Bottom line the approach causes doubt with respect to inconsistent treatment and we need to avoid any potential doubt in the minds of our regulators. Let’s go back to the question of financial statements.  Check back Thursday for my follow-up post, or part II, where we’ll cover the topic in greater detail. 

Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} By: Mike Horrocks Earlier this week, my wife and I were discussing the dinner plans for Thanksgiving.  The yams, cranberries, and pumpkin pies were purchased and the secret family recipes were pulled out of the cupboard.  Everything was ready…we thought.  Then the topic of the turkey was brought up.  In the buzz of work, family, kids, etc., both of us had forgotten to get the turkey.   We had each thought the other was covering this purchase and had scratched if off our respective lists.  Our Thanksgiving dinner was at risk!  This made me think of what best practices from our industry could be utilized if I was going to mitigate risks and pull off the perfect dinner.  So I pulled the page from the Basel Committee on Banking Supervision that defines operational risk as "the risk of loss resulting from inadequate or failed internal processes, people, systems or external events” and I have some suggestions that I think work for both your Thanksgiving dinner and for your existing loan portfolios. First, let’s cover “inadequate or failed processes”.  Clearly our shopping list process failed.   But how are your portfolio management processes?  Are they clearly documented and can they be implemented throughout the organization?  Your processes should be as well communicated and documented as the “Smashed Yam Bake” recipe or you may be at risk. Next, let focus on the “people and systems”.    People make mistakes – learn from them, correct them, and try to get the “systems” to make it so there are fewer mistakes.  For example, I don’t want the risk of letting the turkey cook too long, so I use a remote meat thermometer.  Ok, it is a little geeky; however the turkey has come out perfect every year.    What systems do you have in place to make your quarterly reviews of the portfolio more consistent and up to your standards?  Lastly, how do I mitigate those “external events”?  Odds are I will be able to still get a turkey tonight.  If not, I talked to a friend of mine who is a chef and I have the plans for a goose.   How flexible are your operations and how accessible are you to the subject matter experts that can get you out of those situations?  A solid risk management program takes into account unforeseen events and can make them into opportunities. So as the Horrocks family gathered in Norman Rockwell like fashion this Thanksgiving, a moment of thanks was given to the folks on the Basel committee.  Likewise in your next risk review, I hope you can give thanks for the minimized losses and mitigated risks.  Otherwise, we will have one thing very much in common…our goose will be cooked.

With the most recent guidance newly issued by the Federal Financial Institutions Examination Council (FFIEC) there is renewed conversation about knowledge based authentication. I think this is a good thing.  It brings back into the forefront some of the things we have discussed for a while, like the difference between secret questions and dynamic knowledge based authentication, or the importance of risk based authentication. What does the new FFIEC guidance say about KBA?  Acknowledging that many institutions use challenge questions, the FFIEC guidance highlights that the implementation of challenge questions can greatly impact efficacy of its usefulness. Chances are you already know this.  Of greater importance, though, is the fact that the FFIEC guidelines caution on the use of less sophisticated systems and information that can be easily guessed or obtained from an Internet search, given the amount of information available.    As mentioned above, the FFIEC guidelines call for questions that “do not rely on information that is often publicly available,” recommending instead a broad range of data assets on which to base questions.  This is an area knowledge based authentication users should review carefully.  At this point in time it is perfectly appropriate to ask, “Does my KBA provider rely on data that is publicly sourced”  If you aren’t sure, ask for and review data sources.  At a minimum, you want to look for the following in your KBA provider:     ·         Questions!  Diverse questions from broad data categories, including credit and noncredit assets ·         Consumer question performance as one of the elements within an overall risk-based decisioning policy ·         Robust performance monitoring.  Monitor against established key performance indicators and do it often ·         Create a process to rotate questions and adjust access parameters and velocity limits.  Keep fraudsters guessing! ·         Use the resources that are available to you.  Experian has compiled information that you might find helpful: www.experian.com/ffiec Finally, I think the release of the new FFIEC guidelines may have made some people wonder if this is the end of KBA.  I think the answer is a resounding “No.”  Not only do the FFIEC guidelines support the continued use of knowledge based authentication, recent research suggests that KBA is the authentication tool identified as most effective by consumers.  Where I would draw caution is when research doesn’t distinguish between “secret questions” and dynamic knowledge based authentication, which we all know is very different.   

By: Mike Horrocks Have you ever been struck by a turtle or even better burnt by water skies that were on fire?  If you are like me, these are not accidents that I think will ever happen to me and I'm not concerned that my family doctor didn't do a rotation in medical school to specialize in treating them. On October 1, 2013, however, doctors and hospitals across the U.S. will have ability to identify, log, bill, and track those accidents and thousands of other very specific medical events.  In fact the list will jump from a current 18,000 medical codes to 140,000 medical codes.  Some people hail this as a great step toward the management of all types of medical conditions, whereas others view it as a introduction of noise in a medical system already over burdened.  What does this have to do with credit risk management you ask? When I look at the amount of financial and non-financial data that the credit industry has available to understand the risk of our consumer or business clients, I wonder where we are in the range of “take two aspirins and call me in the morning” to “[the accident] occurred inside a chicken coop” (code: Y9272).   Are we only identifying a risky consumer after they have defaulted on a loan?  Or are we trying to find a pattern in the consumer's purchases at a coffee house that would correlate with some other data point to indicate risk when the moon is full? The answer is somewhere in between and it will be different for each institution.  Let’s start with what is known to be predictable when it comes to monitoring our portfolios - data and analytics, coupled with portfolio risk monitoring to minimize risk exposure - and then expand that over time.  Click here for a recent case study that demonstrates this quite successfully with one of our clients. Next steps could include adding in analytics and/or triggers to identify certain risks more specifically. When it comes to risk, incorporating attributes or a solid set of triggers, for example, that will identify risk early on and can drill down to some of the specific events, combined with technology that streamlines portfolio management processes - whether you have an existing system in place or in search of a migration - will give you better insight to the risk profile of your consumers. Think about where your organization lies on the spectrum.    If you are already monitoring your portfolio with some of these solutions, consider what the next logical step to improve the process is - is it more data, or advanced analytics using that data, a combination of both, or perhaps it's a better system in place to monitoring the risk more closely. Wherever you are, don’t let your institution have the financial equivalent need for these new medical codes W2202XA, W2202XD, and W2202XS (injuries resulting from walking into a lamppost once, twice, and sequentially).

By: Mike Horrocks Let’s all admit it, who would not want to be Warren Buffet for a day?  While soaking in the tub, the “Sage of Omaha” came up with the idea to purchase shares of Bank of America and managed to close the deal in under 24 hours (and also make $357 million in one day thanks to an uptick in the stock). Clearly investor opinions differ when picking investments, so what did Buffet see that was worth taking that large of a risk? In interviews Buffet simply states that he saw the fundamentals of a good bank (once they fix a few things), that will return his investment many times over. He has also said that he came to this conclusion based on years of seeing opportunities where others only see risk. So what does that have to do with risk management? First, ask yourself as you look at your portfolio of customers what ones are you  “short-selling”  and risk losing and what customers are you investing into and expect Buffet-like returns on in the future? Second, ask yourself how are you making that “investment” decision on your customers? And lastly, ask yourself how confident you are in that decision? If you’re not employing some mode of segmentation today on your portfolio stop and make that happen as soon as you are done reading this blog. You know what a good customer looks like or looked like once upon a time. Admit to yourself that not every customer looks as good as they used to before 2008 and while you are not “settling”, be open minded on who you would want as a customer in the future. Amazingly, Buffet did not have Bank of America’s CEO Brian Moynihan’s phone number when he wanted to make the deal. This is where you are heads and shoulders above Garot’s Steak House’s favorite customer.  You have deposit information, loan activity and performance history, credit data, and even the phone number of your customers. This gives you plenty of data and solutions to build that profile of what a good customer looks like – thereby knowing who to invest in. The next part is the hardest. How confident are you in your decision that you will put your money on it? For example, my wife invested in Bank of America the day before Warren put in his $5 billion. She saw some of the same signs that he did in the bank. However, the fact that I am writing this blog is an indicator that she clearly did not invest to the scale that Warren did. But what is stopping you from going all in and investing in your customers’ future? If the fundamentals of your customer segmenting are sound, any investment today into your customers will come back to you in loyalty and profits in the future. So at the risk of conjuring up a mental image, take the last lesson from Warren Buffet’s tub soaking investment process and get up and invest in those perhaps risky today, yet sound tomorrow customers or run the risk of future profits going down the drain.

By: Kari Michel The way medical debts are treated in scores may change with the introduction of June 2011, Medical Debt Responsibility Act. The Medical Debt Responsibility Act would require the three national credit bureaus to expunge medical collection records of $2,500 or less from files within 45 days of their being paid or settled. The bill is co-sponsored by Representative Heath Shuler (D-N.C.), Don Manzullo (R-Ill.) and Ralph M. Hall (R-Texas). As a general rule, expunging predictive information is not in the best interest of consumers or credit granters -- both of which benefit when credit reports and scores are as accurate and predictive as possible. If any type of debt information proven to be predictive is expunged, consumers risk exposure to improper credit products as they may appear to be more financially equipped to handle new debt than they truly are. Medical debts are never taken into consideration by VantageScore® Solutions LLC if the debt reporting is known to be from a medical facility. When a medical debt is outsourced to a third-party collection agency, it is treated the same as other debts that are in collection. Collection accounts of lower than $250, or ones that have been settled, have less impact on a consumer’s VantageScore® credit score. With or without the medical debt in collection information, the VantageScore® credit score model remains highly predictive.

By: Mike Horrocks The realities of the new economy and the credit crisis are driving businesses and financial institutions to better integrate new data and analytical techniques into operational decision systems. Adjusting credit risk processes in the wake of new regulations, while also increasing profits and customer loyalty will require a new brand of decision management systems to accelerate more precise customer decisions. There is a Webinar scheduled for Thursday that will insightfully show you how blending business rules, data and analytics inside a continuous-loop decisioning process can empower your organization - to control marketing, acquisition and account management activities to minimize risk exposure, while ensuring portfolio growth. Topics include: What the process is and the key building blocks for operating one over time Why the process can improve customer decisions How analytical techniques can be embedded in the change control process (including data-driven strategy design or optimization) If interested check out more - there is still time to register for the Webinar. And if you just want to see a great video - check out this intro.

With the raising of the U.S. debt ceiling and its recent ramifications consuming the headlines over the past month, I began to wonder what would happen if the general credit consumer had made a similar argument to their credit lender. Something along the lines of, “Can you please increase my credit line (although I am maxed out)? I promise to reduce my spending in the future!” While novel, probably not possible. In fact, just the opposite typically occurs when an individual begins to borrow up to their personal “debt ceiling.” When the amount of credit an individual utilizes to what is available to them increases above a certain percentage, it can adversely affect their credit score, in turn affecting their ability to secure additional credit. This percentage, known as the utility rate is one of several factors that are considered as part of an individual’s credit score calculation. For example, the utilization rate makes up approximately 23% of an individual’s calculated VantageScore® credit score. The good news is that consumers as a whole have been reducing their utilization rate on revolving credit products such as credit cards and home equity lines (HELOCs) to the lowest levels in over two years. Bankcard and HELOC utilization is down to 20.3% and 49.8%, respectively according to the Q2 2011 Experian – Oliver Wyman Market Intelligence Reports. In addition to lowering their utilization rate, consumers are also doing a better job of managing their current debt, resulting in multi-year lows for delinquency rates as mentioned in my previous blog post. By lowering their utilization and delinquency rates, consumers are viewed as less of a credit risk and become more attractive to lenders for offering new products and increasing credit limits. Perhaps the government could learn a lesson or two from today’s credit consumer.

As I’m sure you are aware, the Federal Financial Institutions Examination Council (FFIEC) recently released its, "Supplement to Authentication in an Internet Banking Environment" guiding financial institutions to mitigate risk using a variety of processes and technologies as part of a multi-layered approach. In light of this updated mandate, businesses need to move beyond simple challenge and response questions to more complex out-of-wallet authentication.  Additionally, those incorporating device identification should look to more sophisticated technologies well beyond traditional IP address verification alone. Recently, I contribute to an article on how these new guidelines might affect your institution.  Check it out here, in full:  http://ffiec.bankinfosecurity.com/articles.php?art_id=3932 For more on what the FFIEC guidelines mean to you, check out these resources - which also gives you access to a recent Webinar.

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.

The following article was originally posted on August 15, 2011 by Mike Myers on the Experian Business Credit Blog. Last time we talked about how credit policies are like a plant grown from a seed. They need regular review and attention just like the plants in your garden to really bloom. A credit policy is simply a consistent guideline to follow when decisioning accounts, reviewing accounts, collecting and setting terms. Opening accounts is just the first step. Here are a couple of key items to consider in reviewing  accounts: How many of your approved accounts are paying you late? What is their average days beyond terms? How much credit have they been extended? What attributes of these late paying accounts can predict future payment behavior? I recently worked with a client to create an automated credit policy that consistently reviews accounts based on predictive credit attributes, public records and exception rules using the batch account review decisioning tools within BusinessIQ. The credit team now feels like they are proactively managing their accounts instead of just reacting to them.   A solid credit policy not only focuses on opening accounts, but also on regular account review which can help you reduce your overall risk.

It’s time to focus on growth again.In 2010, credit marketers focused on testing new acquisition strategies. In 2011, credit marketers are implementing learnings from those tests.As consumer lending becomes more competitive, lenders are strategically implementing procedures to grow portfolios by expanding their marketable universe. The new universe of prospective customers is moving steadily beyond prime to a variety of near-prime segments outside of the marketing spectrum that lenders have targeted for the past three years.Many credit marketers have moved beyond testing based on new regulatory requirements and have started to market to slightly riskier populations. From testing lower-scoring segments to identifying strategies for unbanked/underbanked consumers, the breadth of methods that lenders are using to acquire new accounts has expanded. Portfolio growth strategies encompass internal process enhancements, product diversification, and precise underwriting and account management techniques that utilize new data assets and analytics to mitigate risk and identify the most profitable target populations.Experian® can help you identify best practices for growth and develop customized strategies that best suit your acquisition objectives. Whether your needs include internal methods to expand your marketable universe (i.e., marketing outside of your current footprint or offers to multiple individuals in a household) or changes to policies for external expansion strategies (i.e., near-prime market sizing or targeting new prospects based on triggered events), Experian has the expertise to help you achieve desired results. For more information on the new acquisition strategies and expanding your marketing universe, leave a comment below or call 1 888 414 1120.

By: John Straka Unsurprisingly, Washington deficit hawks have been eyeing the “sacred cows” of tax preferences for homeownership for some time now. Policymakers might even unwind or eliminate the mortgage interest deductions and capital-gains exemptions on home appreciation that have been in place in the U.S for many decades. There is an economic case to be made for doing this—more efficient resource allocation of capital, other countries have high ownership rates without such tax preferences, etc. But if you call or email or tweet Congress, and you choose this subject, my advice is to tell them that they should wait unti it’s 2005. In other words, now—or even the next few years most likely—is definitely not a good time at all to eliminate these housing tax preferences. We need to wait until it’s something like “2005”—when housing markets are much stronger again (hopefully) and state and local government finances are far from their relatively dire straits at present. If we don’t do this right, and insist on making big changes here now, then housing will take an immediate hit, and so will employment from both the housing sector and state and local governments (with further state and local service cutbacks also, due to budget shortfalls). The reason for this, of course, is that most homeowners today have not really benefited much, and won’t, from those well-established tax preferences. Why not? Because these preferences have been in place for so long now that the economic value (expected present discounted value) of these tax savings was long ago baked into the level of home prices that most homeowners paid when they bought their homes. Take the preferences away now, and the value of homes will immediately drop, and therefore so will property tax revenues collected by local governments across the U.S. This strategy will thus further bash the state- and-local sector in order to plump up some (we hope) our federal tax revenues by the value of the tax preferences. Housing will become a further drag on economic growth, and so will the resulting employment losses from both construction and local government services. As a result, it’s possible that on net the federal government may actually lose revenue from making this kind of change at precisely the wrong time. It may very well never be quite like “2005” again. But waiting for greater housing and local government strength to change long-standing housing tax preferences should make the macroeconomic impact smaller, less visible, and more easily absorbed.

The high-profile data breaches in recent months not only left millions of consumers vulnerable to the threat of identity theft and caused businesses to incur significant costs, but it also brought data security to the top of the agenda in Washington. In Congress, members of both the House and the Senate have used the recent data breaches to demonstrate the need for a uniform national data breach notification standard and increased data security standards for companies that collect consumer information. Hearings have been held on the issue and it is expected that legislation will be introduced this summer.At the same time, the Obama Administration continues to call for greater data security standards. The White House released its highly anticipated cybersecurity initiative in May. In addition to implementing a national data breach notification law, the proposal would require certain private companies to develop detailed plans to safeguard consumer data.As legislation develops and advances through multiple Congressional committees, Experian will be working with allies and coalitions to ensure that the data security standards established under the Gramm-Leach-Bliley Act and the Fair Credit Reporting Act are not superseded with new, onerous and potentially ineffective mandates.We welcome your questions and comments below.