Debt & Collections

  Auditing provides the organization with assurance that all financial controls are in place to ensure that trust account funds are maintained, access to financial records at the vendor location is tightly controlled, customer data is secure, and that the vendor is in full compliance with contractual requirements (i.e., minimum account servicing requirements for issues such as vendor actions following initial placement, ongoing contact efforts, remittance processing, settlement authorizations, etc.). There are two basic auditing processes that occur from a best practices perspective. The first one is fairly common, and involves use of an on-site audit. Onsite Auditing The onsite audit is required to examine financial records involving customer transactions, accounting processes, trust accounts and remittances, IT and security for handling sensitive customer information and records, and documentation of the processes that have occurred towards customer communication, contact efforts and results. There are differences of opinion as to both the frequency of onsite audits, and whether they should be announced or unannounced. Frequency is primarily an issue of the size of the overall vendor relationship and the degree of financial risk associated with a default, typically involving the trust account and legal exposure to litigation and brand reputation risk. Most utilities should follow an annual onsite audit schedule due to size of portfolio and attendant financial exposure. While surprise audits have the advantage of reducing any opportunity by the vendor to potentially alter records to cover up what would normally be audit violations, it does result in a more time-consuming audit schedule onsite, as the vendor is unable to prepare and have documentation available. The use of substantial online documentation lessens this issue, but nonetheless, there is more work to do onsite when nothing has been captured for review in advance. The other issue is that key managers from the vendor may not be available on the dates of a surprise audit. One way in which organizations chose to resolve the issue of surprise versus planned audit is to conduct one pre-planned and announced audit annually, and a smaller scaled unannounced onsite audit annually at least 2 quarters separated from the planned audit. The use of remote auditing and monitoring lessens the requirements for onsite audits in certain areas, other than IT / Security, financial and compliance. Remote Auditing / Monitoring Remote auditing and monitoring of vendors is a stronger tool for credit grantors to improve performance of agencies, in that it combines some of the same auditing checks to ensure compliance and quality of collections with an added value of focus on performance. The best tool in the arsenal is the use of digital logging to capture the collection call between the vendor and customers. When digital logging technology first came into use, it was cost prohibitive for collection agencies, and not fully accepted by the industry due to its possible use in litigation against the agencies. Over the past decade, as the costs of deployment have lessened, and agencies became more attuned to customer satisfaction and full FDCPA compliance, more agencies have installed digital logging into their call centers. Most agencies that utilize digital logging capture every customer contact effort that results in either a right party contact, or third party contact for messages, etc. Many of those agencies will tag each of these voice records as to whether they were a right party contact or not. The intent is to be able to audit more frequently those calls that were right party contacts, so that collector skills can be assessed in terms of how they managed the customer, their ability to create and sell payment solution, and ability to negotiate successfully with the customer. Typically, an organization that is using digital logging will have an internal quality assurance team that will create a compliance audit process that establishes a number of right party and non-right party contacts per collector. These calls are typically evaluated using a scorecard approach, and used for training purposes. They might alter the frequencies of monitoring based upon the tenure of the collector, their performance levels, and the results of prior monitoring, such that sample sizes are affected. Utilities and other credit grantors should have access to the entire inventory of raw digital log files for their projects and randomly audit them remotely. These should not be “assembled” or pre-selected by the vendor, so that there is no undue influence in deciding which calls / collectors to review. If the vendor is using a QA monitoring / compliance program and separately maintains a scorecard driven monitoring process, the credit grantor should have access where those calls and evaluations related to their own customers and contacts. The intent of the process is to listen for both quality of the communication with the customer from the perspective of effectiveness, but also to ensure compliance with FDCPA and that the customer was treated with respect and appropriately. Typically, a credit grantor would establish a remote monitoring schedule where x calls across the agent pool handing their assigned portfolio are monitored and evaluated with a simple checklist. Ideally, the credit grantor should be listening to a range of 100-150 right party contacts per month, based upon overall inventory and activity, but typically no more than 1-2% of the total right party contacts per month on their customer accounts. The credit grantor should provide monthly feedback to the agency regarding the monitoring of quality and compliance, noting any compliance or policy violations, and any concerns relating to customer contact quality and performance. Other aspects of the remote auditing that occurs each month should include ensuring that all servicing requirements are met. As an example, we would expect that the agency should perform various external checks for bankruptcy, deceased, etc. before initiating contact once the file has been received from the credit grantor as a placement. These database checks should be performed within the first 24 hours once placed, and then a letter of representation should be sent to those not flagged. The initial call to the customer should also occur within 24-48 hours from placement by the credit grantor, subject to phone number availability. Skip trace processes should commence immediately on those without phone numbers. There are requirements for how often accounts are attempted for contact, and settlement authorizations. All of these requirements are subject to the remote monitoring that is performed to ensure these are met.    Coming soon...  Best practices for improving agency performance.

Organizations approach agency management from three perspectives: (1) the need to audit vendors to ensure that they are meeting contractual, financial and legal compliance requirements; (2) ensure that the organization’s clients are being treated fairly and ethically in order to limit brand reputation risk and maintain a customer-centric commitment; (3) maximize revenue opportunities through collection of write-offs through successful performance management of the vendor. Larger organizations manage this process often by embedding an agency manager into the vendor’s site, notably on early out / pre charge-off outsourcing projects. As many utilities leverage the services of outsourcers for managing pre-final bill collections, this becomes an important tool in managing quality and driving performance. The objective is to build a brand presence in the outsourcer’s site, and focusing its employees and management team on your customers and daily performance metrics and outcomes. This is particularly useful in vendor locations in which there are a number of high profile client projects with larger resource pools competing for attention and performance, as an embedded manager can ensure that the brand gets the right level of attention and focus. For post write off recovery collections in utility companies, embedding an agency manager becomes cost-prohibitive and less of an opportunity from an ROI perspective, due to the smaller inventories of receivables at any agency. We urge that clients not spread out their placements to many vendors where each project is potentially small, as the vendors will more likely focus on larger client projects and dilute the performance on your receivables. Still, creating a smaller pool of agency partners often does not provide a resource pool of >50-100 collectors at a vendor location to warrant an embedded agency management approach. Even without an embedded agency manager, organizations can use some of the techniques that are often used by onsite managers to ensure that the focus is on their projects, and maintain an ongoing quality review and performance management process. The tools are fairly common in today’s environment --- remote monitoring and quality reviews of customer contacts (i.e., digital logging), monthly publishing of competitive liquidation results to a competitive agency process with market share incentives, weekly updates of month-to-date competitive results to each vendor to promote competition, periodic “special” promotions / contests tied to performance where below target MTD, and monthly performance “kickers” for exceeding monthly liquidation targets at certain pre-determined levels. Agencies have selective memory, and so it’s vital to keep your projects on their radar. Remember, they have many more clients, all of whom want the same thing – performance. Some are less vocal and focused on results than others. Those that are always providing competitive feedback, quality reviews and feedback, contests, and market share opportunities are top of mind, and generally get the better selection of collectors, team /project managers, and overall vendor attention. The key is to maintain constant visibility and a competitive atmosphere. Over the next several weeks, we'll dive into more detail for each of these areas: Auditing and monitoring, onsite and remote Best practices for improving agency performance Scorecards and strategies Market share competition and scorecards

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.

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.

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.

By: Kari Michel As consumers and businesses continue to experience financial hardship, the likelihood of continued bankruptcy filings is fairly strong. Data from the Administrative Office of the U.S. Courts show there were 1,222,589 filings through September, versus 1,100,035 in the first nine months of 2009. According to American Bankruptcy Institute executive director Samuel J. Gerdano, "As the economy looks to climb out of the recent recession, businesses and consumers continue to file for bankruptcy to regain their financial footing. With unemployment hovering near 10% and access to credit remaining tight, total filings in 2010 will likely exceed 1.6 million." Given the bankruptcy trends, what can lenders do to protect themselves from acquiring consumers that are at risk for filing for bankruptcy? Bankruptcy scores are available, such as Bankruptcy PLUS, and are developed to accurately identify characteristics specific to a consumer filing for bankruptcy. Bankruptcy scores are typically used in conjunction with risk scores to set effective acquisition strategies. _________________ Source:  http://www.collectionscreditrisk.com/news/bankruptcy-filings-up-3003998-1.html  

By: Wendy Greenawalt Given the current volatile market conditions and rising unemployment rates, no industry is immune from delinquent accounts. However, recent reports have shown a shift in consumer trends and attitudes related to cellular phones. For many consumers, a cell phone is an essential tool for business and personal use, and staying connected is a very high priority. Given this, many consumers pay their cellular bill before other obligations, even if facing a poor bank credit risk. Even with this trend, cellular providers are not immune from delinquent accounts and determining the right course of action to take to improve collection rates. By applying optimization, technology for account collection decisions, cellular providers can ensure that all variables are considered given the multiple contact options available. Unlike other types of services, cellular providers have numerous options available in an attempt to collect on outstanding accounts.  This, however, poses other challenges because collectors must determine the ideal method and timing to attempt to collect while retaining the consumers that will be profitable in the long term.  Optimizing decisions can consider all contact methods such as text, inbound/outbound calls, disconnect, service limitation, timing and diversion of calls.  At the same time, providers are considering constraints such as likelihood of curing, historical consumer behavior, such as credit score trends, and resource costs/limitations.  Since the cellular industry is one of the most competitive businesses, it is imperative that it takes advantage of every tool that can improve optimizing decisions to drive revenue and retention.  An optimized strategy tree can be easily implemented into current collection processes and provide significant improvement over current processes.

By: Kari Michel   Lenders are looking for ways to improve their collections strategy as they continue to deal with unprecedented consumer debt, significant increases in delinquency, charge-off rates and unemployment and, declining collectability on accounts. Improve collections To maximize recovered dollars while minimizing collections costs and resources, new collections strategies are a must. The standard assembly line “bucket” approach to collection treatment no longer works because lenders can not afford the inefficiencies and costs of working each account equally without any intelligence around likelihood of recovery. Using a segmentation approach helps control spend and reduces labor costs to maximize the dollars collected. Credit based data can be utilized in decision trees to create segments that can be used with or without collection models. For example, below is a portion of a full decision tree that shows the separation in the liquidation rates by applying an attribute to a recovery score This entire segment has an average of 21.91 percent liquidation rate. The attribute applied to this score segment is the aggregated available credit on open bank card trades updated within 12 months. By using just this one attribute for this score band, we can see that the liquidation rates range from 11 to 35 percent. Additional attributes can be applied to grow the tree to isolate additional pockets of customers that are more recoverable, and identify segments that are not likely to be recovered. From a fully-developed segmentation analysis, appropriate collections strategies can be determined to prioritize those accounts that are most likely to pay, creating new efficiencies within existing collection strategies to help improve collections.

In my previous two blogs, I introduced the definition of strategic default and compared and contrasted the population to other types of consumers with mortgage delinquency.  I also reviewed a few key characteristics that distinguish strategic defaulters as a distinct population. Although I’ve mentioned that segmenting this group is important, I would like to specifically discuss the value of segmentation as it applies to loan modification programs and the selection of candidates for modification. How should loan modification strategies be differentiated based on this population? By definition, strategic defaulters are more likely to take advantage of loan modification programs. They are committed to making the most personally-lucrative financial decisions, so the opportunity to have their loan modified - extending their ‘free’ occupancy – can be highly appealing.  Given the adverse selection issue at play with these consumers, lenders need to design loan modification programs that limit abuse and essentially screen-out strategic defaulters from the population. The objective of lenders when creating loan modification programs should be to identify consumers who show the characteristics of cash-flow managers within our study. These consumers often show similar signs of distress as the strategic defaulters, but differentiate themselves by exhibiting a willingness to pay that the strategic defaulter, by definition, does not. So, how can a lender make this identification? Although these groups share similar characteristics at times, it is recommended that lenders reconsider their loan modification decisioning algorithms, and modify their loan modification offers to screen out strategic defaulters.  In fact, they could even develop programs such as equity-sharing arrangements whereby the strategic defaulter could be persuaded to remain committed to the mortgage.  In the end, strategic defaulters will not self-identify by showing lower credit score trends, by being a bank credit risk, or having previous bankruptcy scores, so lenders must create processes to identify them among their peers. For more detailed analyses, lenders could also extend the Experian-Oliver Wyman study further, and integrate additional attributes such as current LTV, product type, etc. to expand their segment and identify strategic defaulters within their individual portfolios.    

In my last blog, I discussed the presence of strategic defaulters and outlined the definitions used to identify these consumers, as well as other pools of consumers within the mortgage population that are currently showing some measure of mortgage repayment distress. In this section, I will focus on the characteristics of strategic defaulters, drilling deeper into the details behind the population and learning how one might begin to recognize them within that population. What characteristics differentiate strategic defaulters? Early in the mortgage delinquency stage, mortgage defaulters and cash flow managers look quite similar – both are delinquent on their mortgage, but are not going bad on any other trades. Despite their similarities, it is important to segment these groups, since mortgage defaulters are far more likely to charge-off and far less likely to cure than cash flow managers. So, given the need to distinguish between these two segments, here are a few key measures that can be used to define each population. Origination VantageScore® credit score • Despite lower overall default rates, prime and super-prime consumers are more likely to be strategic defaulters  Origination Mortgage Balance • Consumers with higher mortgage balances at origination are more likely to be strategic defaulters, we conclude this is a result of being further underwater on their real estate property than lower-balance consumers Number of Mortgages • Consumers with multiple first mortgages show higher incidence of strategic default.  This trend represents consumers with investment properties making strategic repayment decisions on investments (although the majority of defaults still occur on first mortgages where the consumer has only one first mortgage) Home Equity Line Performance • Strategic defaulters are more likely to remain current on Home Equity Lines until mortgage delinquency occurs, potentially a result of drawing down the HELOC line as much as possible before becoming delinquent on the mortgage Clearly, there are several attributes that identify strategic defaulters and can assist in differentiating them from cash flow managers. The ability to distinguish between these two populations is extremely valuable when considering its usefulness in the application of account management and collections management, improving collections, and loan modification, which is my next topic. Source: Experian-Oliver Wyman Market Intelligence Reports; Understanding strategic default in mortgage topical study/webinar, August 2009.

By: Wendy Greenawalt In my last blog on optimization we discussed how optimized strategies can improve collection strategies. In this blog, I would like to discuss how optimization can bring value to decisions related to mortgage delinquency/modification. Over the last few years mortgage lenders have seen a sharp increase in the number of mortgage account delinquencies and a dramatic change in consumer mortgage payment trends.   Specifically, lenders have seen a shift in consumer willingness from paying their mortgage obligation first, while allowing other debts to go delinquent. This shift in borrower behavior appears unlikely to change anytime soon, and therefore lenders must make smarter account management decisions for mortgage accounts. Adding to this issue, property values continue to decline in many areas and lenders must now identify if a consumer is a strategic defaulter, a candidate for loan modification, or a consumer affected by the economic downturn. Many loans that were modified at the beginning of the mortgage crisis have since become delinquent and have ultimately been foreclosed upon by the lender. Making optimizing decisions related to collection action for mortgage accounts is increasingly complex, but optimization can assist lenders in identifying the ideal consumer collection treatment. This is taking place while lenders considering organizational goals, such as minimizing losses and maximizing internal resources, are retaining the most valuable consumers. Optimizing decisions can assist with these difficult decisions by utilizing a mathematical algorithm that can assess all possible options available and select the ideal consumer decision based on organizational goals and constraints. This technology can be implemented into current optimizing decisioning processes, whether it is in real time or batch processing, and can provide substantial lift in prediction over business as usual techniques.    

In my last blog, I discussed the basic concept of a maturation curve, as illustrated below: Exhibit 1 In Exhibit 1, we examine different vintages beginning with those loans originated by year during Q2 2002 through Q2 2008. The purpose of the vintage analysis is to identify those vintages that have a steeper slope towards delinquency, which is also known as delinquency maturation curve. The X-axis represents a timeline in months, from month of origination.  Furthermore, the Y-axis represents the 90+ delinquency rate expressed as a percentage of balances in the portfolio.  Those vintage analyses that have a steeper slope have reached a normalized level of delinquency sooner, and could in fact, have a trend line suggesting that they overshoot the expected delinquency rate for the portfolio based upon credit quality standards. So how can you use a maturation curve as a useful portfolio management tool? As a consultant, I spend a lot of time with clients trying to understand issues, such as why their charge-offs are higher than plan (budget).  I also investigate whether the reason for the excess credit costs are related to collections effectiveness, collections strategy, collections efficiency, credit quality or a poorly conceived budget. I recall one such engagement, where different functional teams within the client’s organization were pointing fingers at each other because their budget evaporated. One look at their maturation curves and I had the answers I needed. I noticed that two vintages per year had maturation curves that were pointed due north, with a much steeper curve than all other months of the year. Why would only two months or vintages of originations each year be so different than all other vintage analyses in terms of performance? I went back to my career experiences in banking, where I worked for a large regional bank that ran marketing solicitations several times yearly. Each of these programs was targeted to prospects that, in most instances, were out-of-market, or in other words, outside of the bank’s branch footprint. Bingo! I got it! The client was soliciting new customers out of his market, and was likely getting adverse selection. While he targeted the “right” customers – those with credit scores and credit attributes within an acceptable range, the best of that targeted group was not interested in accepting their offer, because they did not do business with my client, and would prefer to do business with an in-market player. Meanwhile, the lower grade prospects were accepting the offers, because it was a better deal than they could get in-market. The result was adverse selection...and what I was staring at was the "smoking gun" I’d been looking for with these two-a-year vintages (vintage analysis) that reached the moon in terms of delinquency. That’s the value of building a maturation curve analysis – to identify specific vintages that have characteristics that are more adverse than others.  I also use the information to target those adverse populations and track the performance of specific treatment strategies aimed at containing losses on those segments. You might use this to identify which originations vintages of your home equity portfolio are most likely to migrate to higher levels of delinquency; then use credit bureau attributes to identify specific borrowers for an early lifecycle treatment strategy. As that beer commercial says – “brilliant!”  

--by Jeff Bernstein In the current economic environment, many lenders and issuers across the globe are struggling to manage the volume of caseloads coming into collections. The challenge is that as these new collection cases come into collections in early phases of delinquency, the borrower is already in distress, and the opportunity to have a good outcome is diminished. One of the real “hot” items on the list of emerging best practices and innovating changes in collections is the concept of early lifecycle treatment strategy. Essentially, what we are referring to is the treatment of current and non-delinquent borrowers who are exhibiting higher risk characteristics.  There are also those who are at-risk of future default at higher levels than average. The challenge is how to identify these customers for early intervention and triage in the collections strategy process. One often-overlooked tool is the use of maturation curves to identify vintages within a portfolio that is performing worse than average. A maturation curve identifies how long from origination until a vintage or segment of the portfolio reaches a normalized rate of delinquency. Let’s assume that you are launching a new credit product into the marketplace. You begin to book new loans under the program in the current month. Beyond that month, you monitor all new loans that were originated/booked during that initial time frame which we can identify as a “vintage” of the portfolio. Each month’s originations are a separate vintage or vintage analysis, and we can track the performance of each vintage over time. How many months will it take before the “portfolio” of loans booked in that initial month reach a normal level of delinquency based on these criteria: the credit quality of the portfolio and its borrowers, typical collections servicing, delinquency reporting standards, and factor of time?  The answer would certainly depend upon the aforementioned factors, and could be graphed as follows:   Exhibit 1        In Exhibit 1, we examine different vintages beginning with those loans originated during Q2 2002, and by year Q2 2008. The purpose of the analysis is to identify those vintages that have a steeper slope towards delinquency, which is also known as a delinquency maturation curve.  The X-axis represents a timeline in months, from month of origination.  Furthermore,, the Y-axis represents the 90+ delinquency rate expressed as a percentage of balances in the portfolio. Those vintages that have a steeper slope have reached a normalized level of delinquency sooner, and could in fact, have a trend line suggesting that they overshoot the expected delinquency rate for the portfolio based upon credit quality standards. So how do we use the maturation curve as a tool? In my next blog, I will discuss how to use maturation curves to identify trends across various portfolios.  I will also examine differentiate collections issues from originations or lifecycle risk management opportunities.    

-- by Dan Buell Towards the end of 2007, the management of Bay Area Credit Service embarked on an agressive strategy to dramatically enhance the company's market position and increase its collection revenues.  These goals could be achieved only through superior performance at competitive rates.  At the same time, though, the company needed to drastically reduce internal operating expenses while facing significant competition.  The company's major goals for 208 included: *  Earn a much larger share of business from one of the nation's top five cellular phone service providers; *  Become a major collections partner for one of the nation's largest banking institutions; *  Earn more than 50 percent of the market in the pre-charge-off, early-out segment for the nation's largest landline communications provider; *  Enhance the company's position in the secondary collections tier. It's an interesting case study.  Navigate to the link to learn more: https://www.experian.com/whitepapers/index.html

By: Wendy Greenawalt In the second installment of my three part series, dispelling credit attribute myths, we will discuss why attributes with similar descriptions are not always the same. The U.S. credit reporting bureaus are the most comprehensive in the world. Creating meaningful attributes requires extensive knowledge of the three credit bureaus’ data. Ensuring credit attributes are up-to-date and created by informed data experts.  Leveraging complete bureau data is also essential to obtaining long-term strategic success. To illustrate why attributes with similar names may not be the same let’s discuss a basic attribute, such as “number of accounts paid satisfactory.” While the definition, may at first seem straight forward, once the analysis begins there are many variables that must be considered before finalizing the definition, including: Should the credit attributes include trades currently satisfactory or ever satisfactory? Do we include paid charge-offs, paid collections, etc.? Are there any date parameters for credit attributes? Are there any trades that should be excluded? Should accounts that have a final status of "paid” be included? These types of questions and many others must be carefully identified and assessed to ensure the desired behavior is captured when creating credit attributes. Without careful attention to detail, a simple attribute definition could include behavior that was not intended.  This could negatively impact the risk level associated with an organization’s portfolio. Our recommendation is to complete a detailed analysis up-front and always validate the results to ensure the desired outcome is achieved. Incorporating this best practice will guarantee that credit attributes created are capturing the behavior intended.