1. 3 Ways Speech Analytics Helps and Protects the Collections Industry

    3 Ways Speech Analytics Helps and Protects the Collections Industry

    In a time when lawsuits, complaints, and CFPB audits are increasing, collections contact centers need to take steps to improve their processes and prove their compliance. Collections contact centers and Accounts Receivables Management (ARM) firms have to maximize payments while still staying compliant and up to date with new rules and regulations, which often proves to be more challenging than expected. Speech analytics helps by analyzing every single agent contact, either during or after the call. The result is lower cost and effort in call center compliance 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.

    More Data, More Accuracy

    Without speech analytics, the volume of collections calls represented in many compliance audits is often less than 5% of the real total. This small sample size is not a statistically valid representation of the overall population, making the results of any collections call center enforcement and improvement strategies impossible to accurately measure. Such a small sample size can also mask the real issues, simply because the data isn’t sufficient to provide real insights. However, with a speech analytics solution in place, call center managers see data from 100% of their calls, as opposed to just 5%. This means collections contact centers can trust the insights they learn from their audits to be based on valid data. The accuracy of speech analytics, at 90-95%, is also on par with manual audits, saving hours of manual effort. With more and better data, collections contact centers are in a better place to make real improvements.

    Better Compliance

    There were over 11,000 Fair Debt Collection Practices Act (FDCPA) lawsuits filed by consumers in 2012 In addition, cases claiming a violation of the Fair Credit Reporting Act (FCRA) were up 17% from 2011 and cases claiming violations of the Telephone Consumer Protection Act (TCPA) were up nearly 34%. Manual sampling of recorded calls provides little to no prevention of non-compliant behavior or protection against litigation.

    However, with a speech analytics solution in place, collections call centers can score every single call to identify risk level based on the content of the conversation. For instance, the QA departments at a credit union can use speech analytics for tracking escalation language. By building out several different language strings that could indicate an escalated call, analysts can identify the exact language that occurred most often in escalated calls. These insights can then be used as a training opportunity. By identifying some areas for agent improvement, the credit union could work to reduce the number of complaints.

    Continuous Improvement

    Using speech analytics to monitor 100% of calls allows collections call centers to more easily identify the real problems, as well as the real areas of opportunity. Because every call can be reviewed it’s much easier to discover the true root cause of the problem, which ensures the call center develops the right strategy for improvement and compliance. After the strategy is implemented, the effectiveness can be measured and if the process works as intended, the collections contact center can document the process and be on the lookout for ways to make it even better. This continuous improvement strategy, working alongside speech analytics technology, helps collections call centers stay ahead of the curve and eliminates any surprises from CFPB audits.

  1. Categories

    1. Verticals:

      Collections, Healthcare, Internet Marketing, Utilities
    2. Business Drivers:

      Agent Quality, Call Center Software, CEM, CFPB, Compliance, Contact Center, FDCPA, Performance, Sales Effectiveness, Script Adherence, Speech Analytics
    3. Internal Intel:

      Internal Competitors, Internal Partners, Internal Speech Analytics
  2. Topics Mentioned

  3. Authors