by Bradley Fitzakerley, process transformation specialist, Markerstudy Group
Last year’s report from Earnix, an artificial insurance (AI) provider to the insurance industry, predicted that AI deployment in insurance would expand significantly, with 70% of survey respondents planning to implement AI models that use real-time data predictions within the next two years. That projection represented a major increase from the 2024 adoption rate of less than 30%, suggesting that real-time predictive analytics would become vital to the sector’s business strategies.
One year on, AI continues to be rolled out at pace across the insurance industry, supporting carriers’ underwriting processes, claims management and fraud detection. One area in which insurance providers are beginning to harness the benefits of AI to enhance customer experience is the identification of vulnerable customers.
The Financial Conduct Authority defines a vulnerable customer as anyone who, due to personal circumstances, is especially susceptible to harm. Although contact centres rely on their agents to identify vulnerable customers, many consumers are unwilling to admit or unaware that they are vulnerable.
AI now makes it possible to objectively and accurately identify these customers on every call.
Identifying vulnerable customers
AI-driven speech analytics can significantly improve agents’ handling of sensitive calls by providing deeper insights into call reasons and sentiment analysis.
For example, Markerstudy Distribution can now monitor approximately half a million calls a month in real time, ensuring vulnerable customers receive prompt support. One improvement is enhanced identification of calls with hard-of-hearing customers using relay services. This has led to smoother interactions and ensures all customers receive a high level of service.
Speech analytics transforms a previously manual process for identifying vulnerable customers into an automated system of call scoring and caller vulnerability analysis. It actively identifies hard-of-hearing customers, for example, and looks objectively at soft skills to analyse call sentiment in real time and generate an agent’s behavioural score.
This data-driven approach enables organisations to identify call reasons, allowing them to make informed recommendations for process improvements. These recommendations can be used to enhance agent training and ensure better handling of sensitive calls.
Speech analytics can also help insurance providers to distinguish between standard and vulnerable customers based on similar-sounding words or phrases that may be used in a particular situation.
For instance, a word like “passed” could indicate that a motor insurance customer has obtained their driving licence (“passed my test”), but it could also mean that a customer has died (“passed away”) and needs to have their policy cancelled. In the latter situation, call handlers are trained to be alert to the caller’s emotional fragility. AI facilitates the call triage process, allowing agents to focus their skills and attention where they are needed the most.
Avoiding the one-size-fits-all approach
In addition to enhancing caller identification processes, AI can provide a welcome means for customers to engage with an organisation when they are feeling at their most vulnerable.
Customers who have suffered a bereavement are typically required to inform a host of organisations of their relative’s death. By the time they contact their relative’s insurance provider, they may have already spoken to a dozen or more call handlers. This can leave them feeling as though they are now receiving performative empathy and bring them to a stage of emotional burnt-out. The last thing they want is to have to repeat their upsetting telephone script one more time.
In this situation, AI virtual assistants offer a less onerous way for vulnerable customers to communicate with an insurance provider via a service that is bespoke and more likely to feel empathetic.
A force for inclusivity
Aside from optimising caller-identification and call-handling processes to benefit vulnerable customers, AI ultimately helps insurance providers to make their organisations more inclusive.
Diversity, equity and inclusion is often discussed in terms of gender, age or ethnicity, but physical and technological disability is another key determining factor in how catered for or excluded an organisation’s stakeholders can feel.
From adapting fonts and background colours to make website copy easier to read for customers affected by dyslexia to improving relay services for customers with hearing loss, AI enables insurance providers to deliver tailored customer experiences that point the way to a more equitable industry.
