According to WebRecon statistics, 3,336 consumers filed Consumer Financial Protection Bureau (CFPB) complaints against debt collectors in June 2014. An additional 1,081 consumers filed lawsuits under consumer statutes, including 806 Fair Debt Collection Practices Act (FDCPA) lawsuits, 207 Telephone Consumer Protection Act (TCPA) lawsuits, and 169 Fair Credit Reporting Act (FCRA) lawsuits.
These statistics reinforce one challenge collections contact centers constantly face: staying compliant and up-to-date with new rules and regulations. During the recent Association of Credit and Collections (ACA) International event in Chicago, IL, CallMiner had the opportunity to discuss this challenge and others affecting the industry with third-party collection agencies, law firms, asset buying companies, creditors and affiliates.
To help address this challenge, speech analytics for collections analyzes every agent contact – either during or after the call – to eliminate call center compliance risk, improve agent performance, and increase recovery rates. Here’s a closer look at how:
Eliminate compliance risk: An examination of credit bureau data by the Urban Institute shows nearly 12 million adults (or 5.3% of Americans with a credit file) are at least 30 days behind on a credit card or other nonmortgage account payment. Additionally, 77 million Americans (or 35% of adults with credit files) have a reported debt in collections, according to the research. Their average debt amount is $5,178.
Due to the resulting high volume of collections calls, maintaining compliance is critical for staying within state and federal licensing laws (as well as reducing or eliminating fines or lawsuits with the CFPB and the FDCPA). While manual sampling of recorded calls or contacts provides little to no prevention of non-compliant behavior or protection against litigation, CallMiner Eureka tracks every call for Mini Miranda language, Right Party Contact language, FDCPA violations, abusive language from either party, and other risky language.
Improve agent monitoring: Aside from eliminating compliance risk, another advantage to speech analytics for collections is improved agent monitoring. By using speech analytics, collections companies and Accounts Receivable Management (ARM) firms can quickly discover issue root causes, developing recommendations and creating coaching initiatives designed to address problems. The end result? Agents who are ultimately able to work more effectively.
Both CallMiner Eureka and myEureka performance portals give contact centers the ability to automatically and objectively score 100% of calls. This ensures agent procedural compliance and reveals behaviors and activities that lead to successful collections. CallMiner Eureka has also helped ARM clients quickly identify specific factors contributing to negative performance trends as well as determine the root causes of issues.
Increase recovery rates: By quickly identifying which agents are in need of training or require more grounding in best practice, speech analytics not only improves agent performance, but can also increase promise to pay ratios. According to a Fico Labs article, speech analytics software revealed that, for a leading debt recovery company, agents failed to follow the company’s “ask for payment” process 60% of the time!
“The old adage ‘If you don’t ask, you don’t get’ is always worth remembering,” says a Call Centre Helper article on speech analytics for collections. “Yet it’s surprising that many debt collectors fail to ask for payment – as recordings of call center conversations show. Many also do not follow guidelines designed to establish how the debtor pays other bills.”
Call center agents working in collections face a unique set of challenges with potentially serious ramifications. Fortunately, speech analytics solutions can help by analyzing thousands of hours of recorded calls, resulting in improved compliance, increased recovery rates, better agent performance, and more.
How has your collections contact center used speech analytics for improved business outcomes? We’d love to hear your feedback in the comments below.
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