Digital transformation and legacy modernisation across insurance is powered by artificial intelligence. However, as Darran Simons, FICO, explains, two main challenges continue to block the road to wider adoption.
Artificial intelligence (AI) is already beginning to change the insurance industry for the better. But what does its future hold? If the atmosphere at this year’s BIBA conference and last year’s Insurance Innovators Summit was anything to go by, the industry is more than ready to take on the challenges and find out where AI can take it. There was palpable excitement at the event about the application of AI within insurance.
The insurance industry is seeing a surge in AI adoption, with three key areas leading the charge: risk management, advanced fraud detection beyond traditional modelling, and personalised policyholder experiences. Insurers are increasingly embracing AI’s potential for broader application, often combined with existing technologies and processes. For instance, we expect a rise in blended approaches for risk management, leveraging both AI and established modelling techniques. This will ensure explainability, crucial for regulatory compliance and building trust with policyholders.
As I noted in my foreword for the Insurance Innovators Trend Report, “For an industry looking to futureproof its role, its relevance and its revenues in a turbulent world, AI is a potent tool. Presenting an unprecedented opportunity to not only understand and price risk better than ever before, AI will transform the customer relationship, enabling insurers to get closer to customers in ways that add real value to their finances, their health, and their daily lives. Hyper-personalised, dynamic and adaptive, the next generation of insurance will see customers navigate a complex and changing world with confidence, knowing that a powerhouse of data analytics, risk insight and financial resilience has their back 24/7.”
The personalised AI potential
While Generative AI has elevated discussions of artificial intelligence in every industry, not just the insurance industry, we’re still a long way from fully leveraging its power, or even clearly understanding the full potential. Looking beyond Generative AI, I’m excited to see the ways that advanced analytics and AI-powered systems are driving decisions and improving customer journeys. The insurance industry has made tremendous progress, and while insurers are a far cry from Netflix or Uber in their use of AI, it is powering a lot of digital transformation and legacy modernization.
AI has the potential to drive hyper-personalised customer experiences, which are increasingly becoming the norm as customers expect to be treated as individuals. And it doesn’t just bring benefits to customers, it also helps with cost reduction and revenue growth. A Gartner survey has shown that brands risk losing more than 1 in 3 of their customers if personalisation is poor.
Challenges lie ahead
However, despite enthusiasm and initial successes with AI, there are still a number of challenges to tackle before AI can get anywhere near its potential.
The two main ones today are:
Execution / deployment: Gartner has reported that only 10% of analytics and machine learning models are deployed into production. That’s a shockingly low figure. For any model, being able to operationalise it at speed across the business is key.
Explainability: The days of the black box are over. For AI models to get real traction with insurers, they need to be explainable. Legislation is coming as industry regulators get to grips with the need to protect consumers and businesses from the ‘computer says no’ aspect and ensuring AI is used responsibly. But it’s not just about legislation, it’s about understanding the way the model makes decisions so that insurers can be confident about applying it to more use cases.
Working together to break through these roadblocks will help us realise the potential of AI for insurance. This is our key to unlocking what makes customers tick, knowing how to serve them better and how to bring them the expected hyper-personalised offers. This kind of technology has benefits across the spectrum — pricing, underwriting risk decisioning, claims assessment and triage, fraud prevention, and even supercharging the ‘old school’ actuarial and data science activities.
If any insurers haven’t yet realised that they need to prioritise AI, they are the ones that will be left behind.
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