The financial marketplace, especially collections, was forever changed by the subprime mortgage crisis. As TransUnion noted in its 2008 first quarter Trend Data analysis; mortgage loan delinquency increased for the fifth straight quarter, hitting a national average high of 3.23 percent. Credit and auto delinquency rates, on average, have also continued to rise.
A common misconception is there is more debt to collect and therefore a better windfall for collectors. But in reality, providing a “windfall for collectors” may not be true. Actually, there is a bigger pond — or more paper — going into collections; however, this pond is becoming increasingly shallow with less financial reserves for debtors to pull from. There is more debt to collect on, but the amounts of debt and actual returns are trending lower, leading to lower liquidity rates.
Given these challenges, collection agencies and debt buyers need to utilize proven ways to maximize time spent versus return on the dollar. If a company is buying, selling or collecting on debt, the goal is still essentially the same – focus on ways to harness credit data analytics to better prioritize debt collection.
The best predictor of future credit and collection behavior is past credit behavior. Other debt collection methods, using demographics-based models, don’t provide sufficient insight to predict the likelihood of future payments. Liquidity rates are declining on purchased debt; however, the cost of collecting this debt remains consistent. Despite these challenges there is still a large amount of debt to profitably recover with the right execution and combination of strategy and tactics .
Use of Analytics in Prioritization of Debt
Analytics and credit-based data sources provide some of the most robust forms of predictive information that can be applied to collection. For example, prioritization and analysis, using proven-credit recovery models, credit data, event monitoring and descriptive and predictive characteristics, help debtors make more informed decisions on the treatment strategies of their portfolios. This can mean saving thousands of dollars simply be determining the best collection strategies before taking action on an account. This type of analysis and simulation exercise provides insight into which accounts to focus on first – ones that will generate the greatest liquidation rates. There are credit-based solutions today that help you make informed business decisions to optimize recovery efforts before the first letter is mailed or the first phone call is placed.
There is no short fall on information to be used in collection efforts, but knowing how to maximize its potential is the key to success. Collectors need to know when to use, how to value and what to combine in terms of information and analytics (contact data, recovery scores, credit attributes) to determine the most appropriate treatment strategies for their collection portfolios. Best practices in the industry mandate using these credit tools to prioritize strategies, which in turn helps create a competitive edge.
In addition, by monitoring changes in debtors’ lifestyle or financial status, one can continually determine and update treatment of these debtors, producing more effective results for the bottom line. The changes to debtors’ status can be returned to the collector as frequently as daily, if warranted. This provides a way to gain a competitive edge in collection of a debt.
Use of Analytics in Selling, Bidding or Purchasing a Debt
It is also recommended to regularly analyze debt portfolios for evaluation of pricing or bidding on a portfolio for sale. Valuating a portfolio using credit-based analytics, debt buyers and collectors gain additional insight into the potential collectability of a portfolio. Recovery management tools should include an analysis from highly predictive credit-based recovery scores, providing quantifiable data to support decision-making and set strategies.
Since debt collection is an opportunity as well as a risk, it is important to leverage analytics to determine a portfolios’ true value (and establish the selling or buying price). This can be achieved by creating cost-effective strategies based on the repayment probability. Big pond, shallow pond; in the end all that matters is the return on investment.
Michelle Nacker is director of product development for TransUnion’s Collections vertical. She can be reached at email@example.com.