Debt collection contact centers and Accounts Receivables Management (ARM) firms face a constant challenge: being able to maximize payments while staying compliant and up to date with new rules and regulations. Speech analytics can help ease this challenge by analyzing every agent contact – either during or after the call – to eliminate compliance risk, improve agent performance, and increase recovery rates.
Taking on the Compliance Challenge
There were over 11,000 Fair Debt Collection Practices Act (FDCPA) lawsuits filed by consumers in 2012 according to WebRecon. In addition, cases claiming a violation of the Fair Credit Reporting Act (FCRA) were up 17 percent from 2011; cases claiming violations of the Telephone Consumer Protection Act (TCPA) were up nearly 34 percent. Manual sampling of recorded calls or contacts provides little to no prevention of non-compliant behavior or protection against litigation.
Speech analytics can track every call for Mini Miranda language, Right Party Contact language, FDCPA violations, abusive language from either party, and other risky language. Every call is scored to identify relative risk level associated with any aspect of compliance based on the content of the conversation. The result is lower cost and effort in monitoring, faster response times, and ultimately reduction/elimination of fines or lawsuits for non-compliance with Consumer Financial Protection Bureau (CFPB) regulations and the FDCPA.
Poor collector performance can represent significant risk to the organization; whether within on-premise call centers or through third party service organizations (outsourcers). By tracking 100 percent of calls, contact analytics ensures agent procedural compliance and reveals behaviors and activities that lead to successful collections. Speech analytics has helped ARM clients quickly identify specific factors contributing to negative performance trends as well as determining the root causes of issues.
CBE Group, a leader in the debt collection industry, is successfully using speech analytics to pinpoint training opportunities and improve agent performance. Some of their major accomplishments include: achieving a 9.6 percent increase in collections revenue by optimizing targeting practices during tax season, reducing the time needed to implement changes by 200 percent, and improving scorecard performance from an average of 89.6 percent over three quarters to 98.4 percent. Another leading firm has significantly reduced “wrong number” complaints by correlating speech data with agent captured data. A third firm is using speech data to reduce risk associated with voicemail, analyzing for Foti compliant language.
Speech analytics can also reveal behavioral patterns that would otherwise be undetectable in random call sampling. Often, agencies discover that their collectors are not asking for payment as often as they should, or are consistently asking for lower repayments. Perhaps some agents display a pattern of overly long calls, reducing overall dialer throughput. ARM agencies that work quickly to improve and refine their business processes based on the intelligence mined from their collector interactions can dramatically increase their revenues.
By using speech analytics to improve collection rates and reduce the risk of fines and lawsuits as a result of non-compliance, agencies can consistently place higher in their end-client’s rankings in addition to solidifying those client relationships. The result: a larger collections portfolio and significant revenue growth.
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As a Product Marketing Manager at CallMiner, Jason is responsible for defining, developing and implementing market strategies and plans that drive both short-term results and long-term sustainable growth. An accomplished writer and public speaker, Jason has published on topics including performance management, customer experience, and marketing strategy. He holds a MBA from Rollins College, Crummer Graduate School of Business and a Six Sigma Green Belt certification.