AI-based claims management to increase the CLV

How to increase CLV with AI-based claims management

Claims management: AI helps to increase CLV

The personalization of the customer journey should not stop just because a customer is late with their payment.

A personalized, data-driven approach enables the customer to be brought back into the buying cycle, thereby increasing customer lifetime value.

Increasing CLV with artificial intelligence

In the age of digital business models, customers have an enormous choice of offers, which makes it easier for them to switch quickly between providers. This confronts companies with new challenges.
At the same time, these business models also offer a wide variety of new and also necessary opportunities to address customers individually in the context of accounts receivable management and thus differentiate themselves from competitors due to a high information density. In this context, it is crucial to recognize the needs of a customer and to respond to them in the best possible way at different stages of the customer journey.

The consequences of late payment

Due to flexible contract design, companies in the subscription economy in particular are required to work on customer loyalty over the long term. The personalization of the customer journey offers enormous potential for long-term customer loyalty and consequently also increased customer lifetime value. However, the personalized customer experience often ends as soon as a customer defaults on a payment. A missed payment can have a wide variety of reasons. At this point, a customer should not be considered lost.

On the contrary, it is precisely in this sensitive phase that it is important to meet the customer at eye level and thus ultimately return him or her to the subscription. The right approach to claims management can therefore increase customer lifetime value and safeguard the company’s reputation.

In case of late payment, communication with the customer during the dunning and collection process is crucial. A customer-oriented and personalized approach can be based, for example, on whether a customer prefers to be contacted by e-mail or WhatsApp, in the evening or in the morning, or more formally than amicably. Our changing media behavior also plays an important role. We all look at our smartphones about 100 times a day and respond most quickly to messages here. So why don’t we in claims management – as part of the value chain – also communicate digitally with our customers?

A recently published typology study based on anonymized customer data collected in the collection process provides important insights into the personal communication preferences of customer types who are in arrears.

The findings of the study by collection service provider PAIR Finance form the basis for digital and individual customer communication that optimizes the customer journey in claims management (Ghaffari, Kaniewicz & Stricker, 2021).

Why don’t customers pay on time?

It is known from previous studies that an understanding of the situation in which defaulting customers find themselves must be created in order to be able to design communication that is both target-oriented and at eye level (for example, Dominy & Kempson, 2003 or Watson & Barnao, 2009). This includes understanding the reasons a person does or does not make a payment.

In the past, two dimensions have been used to explain delinquent behavior: willingness to pay and ability to pay (Dominy & Kempson, 2003). PAIR Finance, in examining real data (n = 400,000) from the accounts claims management process, has now been able to identify two additional behavioral dimensions: financial organization and a customer’s emotional behavior.

Each of these four dimensions has two opposite expressions that can be assigned to delinquent customers depending on factors such as their age, gender, communication style, and so on:

The combination of the various characteristics along the four dimensions ultimately results in 16 different customer types, which differ in their response and payment behavior.

Among the almost 400,000 defaulting customers analyzed, five types occurred particularly frequently:

Conclusion

Artificial intelligence is about to fundamentally change claims management. It is the key to making debt collection an effective part of the customer journey. PAIR Finance’s study shows: With rapidly changing consumer behavior, companies must rely on dynamic solutions that take individual behavior into account, especially in their communications.

The Corona pandemic in particular has underscored the importance of unique payment experiences tailored to each individual in the new boom of digital subscription models to increase customer lifetime value. Today’s sophisticated consumers demand modern and personalized communications across the entire customer journey. This can be achieved today through the use of Artificial Intelligence, Behavioral Psychology and Data Science.