Consumer Credit
Compelling conversations: Debt Collections Call Centres find value in speech analytics By Ashley Clayton*
Debt recovery is big business with one in three consumers having pastdue payments in collections totalling trillions of dollars for mortgages, car loans, credit cards and medical bills. With no end in sight and people carrying more debt each year, debt collections call centres and agencies have their work cut out for them. Collections organisations must maintain a balancing act between increasing recovery rates and staying compliant with industry regulations to avoid hefty fines as well as improve the consumer experience. In recent years, many companies have turned to Speech Analytics help maximise recovery and regulatory compliance.
Speech Analytics Defined
Ashley Clayton
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Speech Analytics refers to the technology that transcribes speech into data. It offers a detailed examination of both recorded and live conversations. In the context of the collections call centre, these conversations happen between agents and customers, clients or patients. It generates data on words used, sentiment and outcomes, and can uncover trends and identify issues so that companies can address them quickly. This becomes quite important to businesses, as 81% of companies
CREDIT MANAGEMENT IN AUSTRALIA • January 2021
say they compete solely based on customer experience. It’s through conversations that companies can learn about customer preferences and attitudes, which can be useful in refining the overall customer experience. Speech Analytics can go even deeper to help determine the moment when an agent gets the promise to pay or resolves an issue, or when the customer loses interest. A simple review of the conversations that recover funds, turn an unhappy customer into a happy one, or lose a customer can lead to script changes or coaching moments that can improve future customer outcomes. In addition, Speech Analytics provides a more holistic view of how customers are feeling. Through sentiment analysis, it can determine whether customers are happy, angry or indifferent. Sentiment analysis evaluates the language used, as well as voice inflections (volume), the rate of speech, the amount of stress in their voice, and any changes. This helps determines overall attitudes and opinions. By doing so, companies can quickly adapt to improve messaging, products, services and processes that can result in a better customer experience.
