Analytics is the Antidote to Collections Complaints – and Much More

As I noted in my last post, for the 23rd consecutive month, the CFPB handled more complaints about debt collection than any other type of complaint.  This represents 31% of complaints submitted in July of this year.

Compliance is the single most influential component within collections, and organizations that continually question processes and create strategies that improve the consumer experience – while following the regulations -- will succeed. For this group, compliance will serve as the springboard to reducing costs, staff turnover, litigation and legal fees, and lastly, complaints. Compliance will migrate to less of a cost center and more of a business driver.

Analytics will play a major role. But many in the industry continue to ignore this powerful tool.

The use of analytics, including predictive scores and models for determining account treatment, is much more common in other phases of the credit lifecycle, including origination and account management. In collection and recovery, determining how best to “work” accounts is often left to judgment. To the extent that organizations use analytics, many rely on account management behavior scores that rapidly lose precision when the account enters collection.

Behavior scores generally predict a longer-term trend in an account: for example, the probability that an account will go into late-stage delinquency, charge-off or bankruptcy over the next six or twelve months. Collection-specific scoring is designed to predict what will happen in a much shorter timeframe – the next month or two – and what’s predicted is very different:

• Likelihood an account will become more delinquent
• Likelihood an account will self-correct during the current cycle
• Probability of a payment coming in the next month
• Amount of payment or expected time to payment

These types of predictions can be used to great effect in your collection strategies – especially now, when communicating with consumers by manually dialing can mean additional time and expense. Scores, predictive and collection analytics help you make decisions that prevent accounts from becoming more delinquent, support a better consumer experience and lower your risk of alienating consumers in the midst of a temporary setback.

When you know which consumers to contact, the optimal method of contact, best time to call and use the appropriate tone for each message, collection efforts become more successful.  And minimize complaints submitted to the CFPB, too.

To read more about the importance of analytics in debt collection, read the FICO white paper, “Boost Collections and Recovery Results with Analytics.”