With increases in living costs, a significant number of people are now living in debt or experiencing problems paying their bills. Research indicates that as a direct result of the rising cost of living, individuals are spending 75% of their take-home pay on serving debt.

That’s why it’s more important than ever to understand your customers’ situations and identify those who are vulnerable and need more support. Organisations have more data than ever to help them identify these in-need customers and support them in avoiding late payments. In doing so, organisations can increase propensity to pay, including those who are spending three-quarters of their take-home pay on debt.

How can organisations increase propensity to pay?

With access to data insights, organisations can identify customers who are at risk of non-payment, separate them from those who can, and then manage them to ensure appropriate solutions are provided, case by case. For example, by gaining insights into customer behaviours, such as a long string of on-time payments and only recent late payments, organisations can make better decisions about how to handle customers who may be struggling.

Furthermore, your contact centre agents — the people most likely to engage with your vulnerable customers — can be better coached and trained to display necessary empathy. With AI-powered tools, like conversation intelligence, you can identify words, phrases and acoustic qualities that demonstrate vulnerability, and then alert agents in real time to better support agents through their conversations.

How can AI help?

Organisations looking to deliver the best customer experiences and outcomes possible need access to technology that helps them uncover insights into the how, why and when of customer circumstances. These insights can drive improvements, such as:

Streamlining and automating processes, allowing for a more informed, unbiased actions to be taken.
Sharing best practices enterprise-wide to benefit from understanding areas of concern or success. For example, specific use of language by successful collections agents, common objections from debtors and how they’re best overcome.
Identifying patterns that indicate potential late or non-payers, enabling you to implement a proactive, not reactive, strategy.
Customer segmentation, highlighting customers who are most likely to pay, when they pay, and when they don’t, such as correlations between when someone pays (for example, mid-month) and successful rate of payment or if a customer regularly has third parties (for example, family members) pay on their behalf.

Including AI in your collections strategy allows you to gain deeper insight into your customers’ financial situation that helps improve experiences and loyalty, while also supporting your organisation’s long-term business performance and growth.

If you’re interested in learning more about how AI and how it can drive value to your organisation, as well as improving the customer experience, download CallMiner’s How AI Improves the Customer Experience white paper today.