Bringing AI on Board For Your Insurance Company? Here’s What to Consider First

In this article Roi Amir, CEO, Sprout.ai, looks at the power of AI and how best to utilise it.

The insurance industry’s slow response to new technology is well documented, often operating on the back foot when it comes to leveraging innovation such as AI to improve its key pain points. This is particularly true in the claims arena, which has historically been of lower priority when it comes to budget allocation for digital transformation.

But step by step, the industry is opening up to new technologies, with the first phase of Lloyd’s Blueprint Two now ongoing and an increasing number of insurers adopting augmented underwriting systems. Insurers are recognising the potential of both digitisation and automation to improve operational efficiency, customer service and increase margins and profitability. In the claims function, for example, 95% of claim handlers are confident that technologies such as AI will have a major impact on claims processing over the next five years, freeing up claims handlers’ time to focus on more complex claims.

But to achieve these goals, the adoption of technology must be championed at the C-Suite level, not by claims teams alone, which is where much of the drive currently stems from. There’s a distinct need for strong leadership to first determine where and how technology can add the most value and to then actively support the transition. Like a major new hire, AI must be directed towards the right focus areas from the very
outset to have its intended impact, or risk adding little value in practice. Its various different use cases must, therefore, be carefully considered at the C-Suite level to ensure the industry’s effective adaptation to new technologies.

This article explores four primary use cases for AI in the insurance claims process and their potential to fix some key pain points that continue to plague the industry today.

Automation of routine tasks

AI can be leveraged to improve claims from the very outset of the process, from First Notification of Loss (FNOL) to the final steps of claims decision-making. By automating routine tasks, the overall claims process can be effectively streamlined, making this a key use case for insurance leaders to consider.

For instance, the automation of initial claims intake, such as the extraction of key policy information and coverage limits, has the potential to significantly reduce the time required to log and prioritise claims. Claims handlers can get underway with the process far quicker and thus instigate clear, direct communications with their customers from the moment a claim is filed. At a time when insurers are increasingly coming under the spotlight for the deterioration of customer service in claims, particularly around unexplained delays, this power to deliver customer service that meets expectations from the very beginning will be vital.

Predictive AI

The automation of time consuming, manual processes is now a well-established use case for AI, but technological advancements are unlocking new and exciting opportunities for insurers to improve the claims process. The use of predictive AI in insurance signals the application of technology moving to another level.

It is now possible for insurers to provide an immediate indication of where the claim is likely to go: What’s the probability of recovery? What would be the appropriate reserving value to maintain? Is the claim likely to head towards litigation? All can be predicted using AI. By improving predictive analytics, insurers can unlock higher levels of accuracy that provide both greater transparency for the customer and controls the overall cost of claims. After all, claims are insurers’ biggest expenditure today, swallowing 70% of their total earnings in GWP. Embracing emerging use cases for AI in this way could, therefore, help insurers to access value that may otherwise be overlooked in favour of more traditional technology applications.

Automated decision-making

Decision making support from AI – whether that be helping claims handlers to make more informed decisions with AI data insights, or automating the decision itself – can help insurers improve both the speed and accuracy with which claims are resolved. This is particularly important where insurers are faced with claims of increasing complexity. When leveraged by insurance companies, AI has the capacity to analyse vast amounts of unstructured data to provide deeper insights into claims risks and trends. Armed with this AI-powered insight, claims handlers can produce more consistent claims decisions, and much faster too. Not only this, but the data insight can also be fed back to insurers and customers to help make more informed decisions on the underwriting side.

Therefore, there are multiple ways in which AI can help insurers maintain their competitive edge. In some cases, claims can be settled with little to no human intervention whatsoever. We’re seeing evolving consumer demands for claims to be settled almost instantly that insurers are continually struggling to keep pace with, but with AI these demands can be met.

Detecting Fraud

Finally, fraud detection is a use case for AI that only continues to grow in importance. Insurance fraud is costing the industry an estimated $309 billion every year in the US alone, an issue aggravated by the widespread availability of AI tools making it easier than ever to produce convincing, fraudulent claims evidence But AI can be used to fight its own problems.

The technology is increasingly being applied to fraud detection, capable of identifying patterns and anomalies in claims documents with an accuracy rate far greater than human intervention can achieve. For instance, AI can analyse and cross reference data for a reported car accident claim, to ensure the imagery provided was taken at the exact time and place the claimant says it was. It can also be used to flag fraud hotspots, such as repeated claims filings, to help reduce the overall rate of successful fraud and save insurers billions each year.

What next?

These are just a few of the key ways in which AI can revolutionise the insurance industry as we know it today, and reduce the ongoing conflict between consumer expectations and the reality of the claims experience. But insurance leaders must have a clear use case in mind for AI to ensure the greatest benefits of technology aren’t left untapped.