By Sheba Fernando, Head – Data science & AI practice, Larsen & Toubro Infotech (LTI)

Over the last few years, the insurance industry has experienced a huge acceleration in the pace of digital transformation. According to research by KPMG, ‘COVID-19 has been the digital catalyst insurers so dearly needed’, with 85% of insurance CEOs saying the pandemic has accelerated digitisation of their operations and creation of next-generation operating models.

KPMG also suggests that the pandemic has fast tracked progress on creating a seamless digital customer experience and indicated there was a fresh urgency for insurers to develop new business models and revenue streams.

While insurers explore new ways of creating innovative products, processes, and tools to enrich the customer experience and retain a competitive edge, AI is playing a significant role in enabling them to achieve this. From automating the claims process to improving risk assessment and preventing fraud, here are three trending use cases, where AI is revolutionising the insurance industry:

1. Automating the claims process.

Claims processing has multiple stages: review, investigation, evaluation and payment or denial, however, due to its highly repetitive nature, the process is often prone to errors. While there are already significant efforts to automate claims routing, advanced algorithms and AI will improve the speed and accuracy of this process.

With the increase of consumer-connected devices, there is significantly more data available to insurers. IoT and the various data-capture technologies could replace traditional, manual methods of first notice of loss, meaning claims triage and repair services could be triggered automatically.

Take a vehicle collision, for example, a policyholder could in theory stream a video of the damage right after it happens, and an AI module might translate this into loss descriptions and estimate amounts. Vehicles with autonomous features could then either direct themselves to repair facilities if the damage is minor or call for recovery and/or a replacement if it is significant.

Following this, AI-enhanced customer service apps could handle most policyholder interactions through voice and text directly. These apps could interface with not just the claims function but also fraud, medical, policy and repair services.

While this would dramatically improve resolution times, it would also allow knowledge workers to focus on the most complex and contested claims, and those resulting from new and unfamiliar risk areas.

2. Improved risk assessment

AI and ML are critical for capitalising on the explosion of sensory data to radically improve risk assessment.

Take healthcare insurance. By deploying real-time data from consumer wearables such as measuring heart health and monitoring fitness levels, insurers could use AI and ML to gain a deeper understanding of their customers’ health and anticipate any future risks. This will enable insurance professionals to improve their risk assessment and increase the speed and accuracy of the application process.

The experience of purchasing insurance will become much faster, with less active involvement on the part of the insurer and the customer. AI algorithms could develop sophisticated and ever-evolving risk profiles, reducing the time to purchase, but also giving insurers the ability to identify very targeted risk and adapt products and prices accordingly.

More accurate risk-based pricing, however, which rewards low-risk customers and impose penalty for those that represent higher-risk, may be efficient but may also challenge traditional definitions of fairness.

3. Fraud prevention

A new insurance fraud claim is uncovered every five minutes, that’s 300 a day, according to research by ABI. As fraudsters become smarter and more sophisticated, spotting a scam becomes harder.

But AI goes a long way in helping to prevent fraud. As agents process a claim, AI enables them to investigate an alleged accident by analysing data, such as claims notes and documents, background checks, involved parties, as well as customer insight and behaviour. Then by connecting data sets that might otherwise be viewed in siloes, AI enables insurance companies to quickly identify fraud as it happens in near real time.

An AI future

It’s clear AI is going to completely transform the way insurers sell products and interact with their customers. By providing access to deeper customer insights, underwriters, claims processing teams and brokers will be able to deliver personalised services based on customer circumstances and preferences, rather than rely on historical data to predict future trends.

So, as technology advances, wide-scale adoption is on the horizon. Insurers therefore need to move away from the traditional ways and embrace AI to enable the next generation of data-driven decision-making. This will enable them to deliver a myriad of new customer centric solutions, build deeper customer relationships and trust and gain a strong competitive advantage.