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How can machine learning play a role in the development of the next generation of collections?

The future of machine learning in collections.

Because of factors such as growing inflation and rising costs of living, an increasing number of people are finding themselves unable to meet their payments or are now living with debt.

According to research, the rising cost of living is directly responsible for the fact that over 57% of individuals are already having trouble making ends meet. It is probable that this percentage will only continue to rise.

Because of this, it is more necessary than ever to understand your consumers’ circumstances and identify vulnerable people with a greater requirement for support. The availability of more data than ever before has provided businesses with an advantage in locating clients who require assistance and assisting them in avoiding payment delays. By doing so, companies have the ability to improve customers’ inclination to pay, even for the more than 57% of those who are currently having trouble making ends meet financially.

How can businesses boost the likelihood that their customers will pay them?

One out of every five clients who are financially vulnerable are now behind on their payments. In light of this constantly shifting economy, what strategies should businesses employ to ensure their continued viability?

Organisations that have access to data can identify consumers that pose a risk of not paying, differentiate them from customers who are able to pay, and then manage these clients to ensure that suitable solutions are delivered individually. By collecting insights on client behaviours, such as a lengthy series of on-time payments and only recent late payments, businesses can make better decisions about how to handle customers who may be struggling. This can help businesses manage customers more effectively.

In addition, the employees working in your contact centre, who are the ones most likely to interact with your most vulnerable consumers, can be better instructed and prepared to show the necessary empathy in the situations in which they find themselves. Recognising words, phrases, and acoustic features that show susceptibility is possible using AI-powered technologies such as Conversation Intelligence. Once identified, you can inform agents in real-time to provide improved assistance as they carry on conversations.

How can AI be of assistance?

Suppose a company wants to provide the greatest possible customer experience and outcomes. In that case, it needs access to technology that can help it unearth insights into the how, why, and when of the customer’s circumstances. These insights can inspire changes such as streamlining and automating procedures, enabling better informed and unbiased actions to be taken.

You can employ a proactive plan instead of a reactive one if you identify patterns that signal future customers who will pay late or not at all.

Implementing AI into the strategy of your business gives you the ability to gain a more in-depth understanding of the financial circumstances of your customers. This, in turn, helps improve customer experiences while supporting your business’s long-term performance and growth.

AI can be used in digital conversations to help identify potentially vulnerable customers and ensure their query is prioritised to the correct agent/response needed in line with the organisation’s own procedures and the FCA’s treating customers fairly initiative.

Saascoms Omnireach AI conversational technology is utilised by nine collections and arrears organisations in the UK, who, on average, process 2.8 million interactions per month. Sectors include energy, telecoms, vehicle finance, home shopping (catalogues), personal finance/loans, and student loans.

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