AI: A Game Changer for the Insurance Industry

Posted on 13th April 2024

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AI: A Game Changer for the Insurance Industry

Posted on 13th April 2024

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AI: A Game Changer for the Insurance Industry

The insurance industry stands at a technological crossroads, where the buzz surrounding Generative Artificial Intelligence (AI) is louder than the crowds at Insurtech Insights. AI's promise to revolutionise the sector is immense, offering insurers a high-potential route to serving customers with better, more personalised products.

As our AI paper (an extract from INSTANDA’s crowdsourced global thought leadership report) explores, this new wave of AI will undoubtedly enhance the intelligence quotient of mundane tasks and liberate personnel for greater productivity. However, it’s crucial that insurers recognise that there are things that Generative AI is incredibly well suited to, and others that it is not – or at least not yet!

A Call for AI Curiosity

The imperative lies in insurers arming themselves with a deep understanding of what AI is and how it could bring measurable value to their business.

As contributors to INSTANDA’s AI paper, including EY, Microsoft, Deloitte, INSTANDA, Publicis Sapient, Celent, InsTech, InsurTech NY, Encora Europe and others share, there are some excellent AI use-cases emerging.

Case in Point: AI Impact on Underwriting

In underwriting, AI is showing its calibre as an efficiency catalyst. The integration of AI into the underwriting workbench has led to a significant transformation in the way underwriters operate. By streamlining the underwriting process and providing greater access to data, including non-traditional data, AI trims the fat off traditional time-consuming tasks and enhances the assessment of risk. Some innovative firms already harnessing AI and automation have reported a staggering 50% surge in underwriting productivity. This, of course, frees underwriters to focus on more complex cases.

Transforming Customer Experience

One overriding area that AI stands out for is its potential in refining customer segmentation, acquisition, and product personalisation. By leveraging predictive analytics and machine learning, insurers can create insurance products and experiences that align more closely with individual customer profiles and risk appetites, changing the face of customer engagement and satisfaction.

Crucially, AI is already proving to be an effective co-pilot in the customer’s hour of need (when they need to make a claim). In claims, AI can triage, classify and expedite claims at rates that claims assessors alone would struggle to keep pace with. The result? A claims process that is not just quicker but also smoothens the customer's post-incident experience.

This bodes well for the customer, but as INSTANDA’s paper explores, if AI is to become the panacea of insurance, the industry still has some way to travel.

The Prerequisite: A Well-Ordered Data Estate

Generative AI has the muscle to convert colossal datasets into significant, actionable insights on a scale that dwarfs human capacity. Yet, for all its virtues, AI's fruits will remain out of reach if insurers' data environments remain disparate and siloed. Having a strong data estate that’s underpinned by a data-driven culture across the entire business is a prerequisite for judicious AI application.

Currently, data is being used for very specific use-cases rather than thinking ‘how am I going to get the data to enable me to transform my enterprise?’. Insurers who are preparing for the future are already laying the groundwork for enterprise-scale AI. They understand that the data journey they are on today is unlikely to be the same journey in a year’s time.

As the paper covers, AI-curious insurers absolutely understand the value of data and are already on the AI journey, even if they have not implemented it at scale just yet. They are not just focused on the ‘here’ and ‘now’ - they are laser-focused on the future.

They also recognise that the challenge is not simply about amassing data—it's making it actionable, and this requires a very different cognitive skillset to traditional data mining.

Concluding thoughts…

In essence, AI will ultimately become an effective co-pilot across the insurance value chain. However, its application is neither universally apt nor a cure-all. It is an instrument whose song resonates best when played by those who understand its rhythm.

For the insurance professional, the message is clear: don’t be a passenger in your own destiny. Get to know what AI could mean for your business. Discern its strengths, flaws and measurable value, and prepare the ground—your data and ecosystem—for its advent.

To read how insurers across the world are already doing this, check out INSTANDA’s AI eBook.

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