A major challenge of debt collection organizations is determining which calls to monitor in order to identify potential issues before they escalate, especially meeting critical compliance requirements.
Of all the useful contact center technologies available today, one of the most valuable I’ve seen in addressing this challenge is real-time speech analytics.
The following are three ways that speech analytics can help improve your debt collection efforts and reduce compliance violations.
- The ability to identify when debt collectors break the rules. Regulatory compliance is a well-defined problem. Analyzing call recording with speech analytics is an effective way to identify compliance violations. In order to prepare for training needs, search within a speech analytics application for key words and phrases that would reveal non-compliant calls, offending agents, and use of prohibited terminology. Results can then be cited during agent training sessions.
- The ability for a supervisor to identify “good” calls. Speech analytics can also be used to identify positive words or phrases during a call. For example, when a caller expresses his or her thanks to an agent for being especially helpful. These calls serve as powerful training aids that can help agents improve their problem-solving skills. They are also important positive reinforcements that can bolster morale and provide greater incentive for good performance.
- The ability to target the right calls for monitoring. Contact centers have long struggled to determine which calls to monitor and evaluate. Do you pick the 10 longest calls? Do you always select calls from Monday because that’s peak call volume day? Or maybe afternoon calls because that’s the highest right-party-contact (RPC) timeframe? Real-time speech analytics can offer far more relevant criteria for call monitoring. For instance, how about monitoring every call that included the phrase “I’m going to sue you” (or any variation of it). And if that phrase was uttered by an agent, it can be sent to his or her supervisor. If it was said by the debtor, it can be flagged for follow-up by the legal team. You can see how speech analytics would dramatically fine-tune call monitoring so supervisors are addressing the right calls with minimum effort – the end result being more effective and efficient debt collection efforts while avoiding hefty fines.
Have your collection efforts been helped by other speech analytics capabilities? If so, I’d love to hear about them.