The economic downturn and slow recovery, combined with continued regulatory overhead and uncertainty, have rendered many lending products potentially obsolete for large portions of a portfolio. This in turn will reduce the amount of capital a credit union is willing to invest in a product line or line of business for new loan growth.

To offset these pressures and generate returns required to drive greater earnings, which will fuel future loan growth, portfolio managers are aggressively expanding their policies and practices to drill more deeply and frequently into their portfolios by identifying those members where relationships can be expanded and conversely identify those which are accelerating debt and stress.

To do that, a growing number of lenders are finding that it pays to look not only at a score or snapshot of a consumer profile, but take into consideration the magnitude and direction of change as well as frequency of review on all obligations and beyond the obligations they manage.

Increasingly, this requires the ability to trend consumer credit data, identify specific member metrics, and track those changes over time. The most successful lenders have incorporated these metrics into their day-to-day processes. They consider trending one of the most important and effective techniques used to vector behavior and segment appropriately.

Lenders today look at internal and external trended data, for both traditional risk uses, such as in underwriting, as well as expanded uses that help identify retention, cross-sell and revenue opportunities. Trended data has the ability to focus on short-term changes (1-3 months), and longer periods (6-24 months), thus providing deeper behavioral transparency. One such solution, for instance, uses a consumer’s trended credit data to estimate an individual’s annual spend on each credit and charge card. It then aggregates those trade lines to provide a full view of an individual’s discretionary spending power.

The spend algorithm strongly correlates with income, deposit balances and net worth, therefore helping lenders differentiate the highest spenders from non-spending populations, allowing them to focus their capital where it counts.

The Importance of Trended Data

By quantifying a direction and magnitude of change, lenders are finding that while two members might have the same credit score and credit card debt today, they fall within two markedly different risk profiles.

For instance, just focusing on card data for the past five months, one member we’ll call Mary might show that her debt has declined to $12,000 from $29,500, reducing the utilization on Mary’s $50,000 credit line to 24% from 59%. At the same time, the other member, let’s call him Peter, has debt that has climbed to $12,000 from $4,100, increasing the utilization of Peter’s $50,000 credit line to 24% from 8%. Who is likely the best credit risk? Is the fact that Peter’s monthly payments have almost tripled in the last five months an early sign of stress?

Using trended data gives lenders the ability to segment portfolios into homogeneous populations, allowing them to

• Build stable risk models
• Identify consumer stress
• Target higher-spending members (or prospects)
• Assign credit lines (and pricing) based on actual spending need
• Retain members that contribute to the bottom line

Portfolio management is a science, but there is no all-encompassing solution or standard approach to maximizing return on an investment. With more than 7,000 NCUAinsured credit unions and an equal number of banks, creating an efficient process to manage risk and return is a continuous challenge. Below is a basic set of capabilities that can be modified to suit a lenders portfolio or budget:

• As a foundation, lenders should periodically analyze all existing members’ credit risk on a monthly or quarterly basis; this data allows for transparency in business planning and provides the ability to take actions if business, economic or consumer conditions change.
• Consumer stress happens quickly. Continually monitor key credit events such as bankruptcy filings, which have nearly 100% expected loss rate. This can help reduce any open exposure.
• Conversely, your best members may be seeking credit elsewhere. Why lose wallet share when simple notifications can be automatically sent to you allowing you to retain your existing members?
• Continually revalidating and calibrating strategies is basic safety and soundness. Risk thresholds and models, such as credit scores, must be adjusted quarterly. In addition, when considering the changing economic landscape and consumer behavior, revenue and usage assumptions change even more frequently.
• Use all member information available when making decisions. “Risk Score”-only decisions didn’t predict the economic downturn. Any risk score should be combined with income, spend and an understanding of all obligations when assigning pricing or credit lines. Bypassing any data reported about a customer, can leave gaps in risk assessment. For example, mortgage lenders should examine those consumers who are very late in their auto payments and those whose cars have been repossessed. They’re probably in such financial straits that they’re doing everything they can to make their home-loan payments.

What You Should Be Following

Follow credit-reporting developments closely. A trade line item on a credit report refers to a past or present credit relationship for vehicle loans, credit cards, mortgages, leases and other loans. A credit report lists separate trade lines for each account or credit card number, whether open or closed. A seasoned trade line is one that’s current with a history of timely payments. Also, public record items such as bankruptcy, court judgments and tax liens are key to completing the full picture of risk.

While there’s no crystal ball we can peer into to adapt to a changing economic and consumer landscape, adding trending capabilities and increasing the frequency of review can help create a more stable and predictable portfolio, generating not only the return needed but confidence that your product line or line of business deserves more capital for growth.

By Trevor Carone, Vice President of Product Marketing, Portfolio and Collection Solutions at Experian.

Originally published in the Credit Union Journal, April 23, 2012 – Download and Print the full article.

Collection industry under the CFPB microscope. Learn how to protect yourself.

A record 12,788 lawsuits were filed in 2011 against accounts receivable management companies for regulatory violations, with the majority related to the Fair Debt Collection Practices Act. This year began with increased concern from the collection industry as the Consumer Financial Protection Bureau (CFPB) shows heightened interest in debt collectors.

Companies are facing potential litigation and fines

With this increased scrutiny, collection companies are under the microscope even more than before. Companies face potential litigation, fines and negative publicity if they attempt to collect on past-due consumers without proper handling. It’s now critical to identify accounts with a protected status before making collection efforts, in order to minimize legal risk and optimize your resources.

Experian’s FirstSweep^SM can help you optimize your treatment strategy to deal with regulatory risk. Experian^® can identify which consumers may be bankrupt, deceased or active duty military. Additionally, phone type and fraud indicators can be provided.

Act now by contacting your Experian account executive or calling 1 888 471 0066 to learn how FirstSweep can help you reduce regulatory risk.

Many clients can benefit from knowing a consumers ability to pay

Income Insight^SM and Income Insight W2^SM, Experian’s income estimation models, were developed primarily to assist credit card lenders in assessing a consumer’s ability to pay to minimize the likelihood of extending credit beyond what the consumer can repay. However, as mentioned in a recent USA Today article, many other types of clients besides credit card lenders have found uses for income estimation models.

Governmental entities and regulated utility companies use the models to identify those consumers who are eligible for financial assistance programs. Tenant screening companies incorporate the models in their processes to verify an applicant’s income. Retail catalog companies can target the right prospects by utilizing income in their prescreen campaigns. Debt collection companies combine the models with a recovery score to determine those consumers most likely to repay their debt. Having this additional insight into a consumer’s ability to pay helps many different types of clients make more informed decisions.

If you would like more information talk to one of our representatives today by calling 1 888 414 1120 or complete this form and a representative will contact you.