The new age insurance: Personalisation with AI & data analytics applications

• Advances in AI and data analytics are shaping the next level of insurance personalisation, paving the way for usage-based insurance and customised claims handling. 

• Insurers’ product propositions are transforming thanks to an explosion of new data sources, from connected sensors to open-source data ecosystems. 

• The new age insurance of the future will be a multidimensional one, drawing together varied channels, technologies, and scenarios seamlessly to enhance customer experience.

An AI revolution is dawning on the insurance industry, and it looks set to light our way to a new age of hyper-personalisation.

You’re likely familiar with the popular use case of AI-powered chatbots – bots that can recommend personalised products and help customers file claims. But this is only the tip of the iceberg. Not far off lies a future where we can instantly purchase policies tailored to our individual habits, where health premiums may be based off our routines or where IoT sensors in our cars can detect accidents and trigger automatic claims.

Currently, only 15% of insurance companies and banks globally deploy AI extensively across their organisation. But by 2025, 86% say they plan to boost AI-related investments in technology. Concurrently, the global insurance analytics market is set to grow at a CAGR of 14.2% between 2020 and 2027, as more insurers tap into predictive analytics to enhance customer relationships.

As AI advances, it will take insurers far beyond simply streamlining existing functions. In an increasingly data-driven world, AI will enable insurers to understand their customers more deeply – birthing all-new product categories and next-level seamless experiences.

These trends were discussed during a panel on AI & data analytics applications in the new age of insurance personalisation, at the 2nd Insurance Analytics & AI Innovation Asia Pacific 2022. Hosted by Kaushal Silva, Client Business Solutions APAC at Zühlke, the panel brought together thought leaders in the use of data and AI.

Here’s a breakdown of the key insights:

The new data sources transforming product propositions

One immediate reason for insurers to start investing in advanced analytics and AI is speed. 

Nelson Chan, Head of Financial Services Business Development for Hong Kong and Taiwan at Amazon Web Services, highlighted three tangible benefits for insurers from the "speed" enabled by advanced analytics and AI.

"Firstly, insurers can obtain usable data faster with real-time processing of data streams. Secondly, insurers get actionable insights faster from data that’s continually analysed and available to their data scientists and business intelligence teams. Finally, insurers can execute faster with both rapid business case approval and cloud-native, agile teams using DevOps and application programming interface architectures."

Three key areas of opportunities for investment that Nelson predicts are in lifestyle or behavioural insights for better propositions and underwriting, enhanced customer experience in distributions and claims, and synced business and customer views. 

With these new areas for innovation, insurers will certainly need enhanced data management capabilities to keep up with the sheer explosion of consumer data.

The IDC forecasts over 55 billion connected IoT devices worldwide by 2025, generating a massive flood of insights into customers’ health, homes, and cars. For insurers, this means a decisive shift from dependence on internal, self-declared data to external, tracked data. 

Companies will be able to personalise pricing and customise claims processing through input from the connected sensors permeating every aspect of life: telematics, wearables, smart homes, even biometrics. As data analytics tools become more sophisticated, it will be possible to efficiently process unstructured data like social media activities and voice analytics too.

How will insurers obtain such data? McKinsey foresees the rise of open-source ecosystems that allow public and private entities to share data under certain regulations. Insurers can build partnerships with tech companies to create individualised products at a lower cost.

One intriguing example is Alipay’s free health insurance service. Offered in partnership with China-incorporated life insurance company Taikang, the service allows users aged below 60 to accumulate free insurance coverage by performing payments with their Alipay Wallet.

This partnership has proven wildly successful, with 13 million Alipay users opting in for coverage in the first 20 days after launch. In a new age of insurance, such partnerships can conceivably be leveraged to spot consumers’ changing purchasing patterns – for instance, purchases for a new home – and offer policies personalised to their needs.

With new data sources comes a pressing need to ensure responsible AI.

Only 35% of global consumers today trust organisations’ use of AI, making it essential for insurers to build trust among customers. Transparent communication, strict compliance with data privacy guidelines, and participation in AI governance initiatives like the Monetary Authority of Singapore’s Veritas consortium, must be the way forward for insurers.

“To build trust, we must balance the value we can give customers for their data with the assurance that the correct standards and security protocols are followed,” says Kaushal.