ANALYSIS: ARTIFICIAL INTELLIGENCE

Enabled Insurer of the Future

be when it comes to AI maturity and enterprise-wide integration.

“Insurers with in-depth insight into their AI readiness are better equipped for the next step: creating a road map for implementing AI solutions across the front-, middleand back-office functions of their companies,” McKinsey’s Chung, Jain, and Purushothaman co-wrote.

This road map allows company leaders to calibrate expectations as well as the resources, time, and investments needed.

However, whilst each insurers’ journey to AI readiness varies, the end goal remains the same: a more innovative, profitable, digitalforward organisation that meets and anticipates customers’ evolving needs with highly personalised, omnichannel experiences, McKinsey & Co. said.

Personalisation

Insurers’ senior management agendas are undoubtedly colored with notes on creating more exceptional customer experiences, which is something that AI could bolster.

“Some Asian insurers have used micro personalisation based on consumer personas to realise gains in overall engagement; nonetheless, most have fallen short of employing dynamic, one-to-one customer targeting to create the personalised, consistent, omnichannel customer experience that characterises mature AI-powered engagement. In other words, personalisation at scale,” the McKinsey experts said. In Asia, most large insurers are halfway along the path of achieving personalisation at scale, they added. These insurers prioritised four key metrics: measurement and attrition; aggregating data into a single platform; application of analytics models to support customer acquisition, cross-selling and sales functions; and delivery of individually curated, personalised content at every interaction and point of contact.

Three models Chung, Jain, and Purushothaman further identified for the McKinsey report three models that Asian insurers can adapt moving forward.

The first is building a digital hybrid agency. As an example, they noted one global insurer who redesigned its agency channel to be AI-ready, and in turn realised an incremental impact of several million dollars over the subsequent years.

Specifically, the insurer reportedly used geospatial network optimisation to identify geography-specific agents' demand and capture growth opportunities and then used this data to inform its local recruitment strategy. Ramp-up time from newly hired agents to full productivity fell significantly, and retention rates rose.

The company did this by adopting a behaviour-driven, next-based action recommendation engine and customised learning plans based on agents’ individual performance.

Another insurer in Asia used AI-based assistants to support online interactions in real-time. This resulted in the insurers recording a monthly average of approximately 100,000 client-meeting hours. AI-facilitated policy issuance at this company was more than US$100,000 in 2021, and agent productivity improved, as measured by a 25%-30% increase in net book value per agent.

Bancassurance and ecosystems

Apart from using AI to build a digital hybrid agency, insurers may also opt to explore the use of AI in digital bancassurance; or take a leaf out of InsurTech’s books and explore how to embed services in ecosystems.

Bancassurance remains the second-largest channel driving life insurance sales globally, the McKinsey analysts noted. However, due to legacy bank systems, it is perhaps the most challenging to transform.

One way that an Asian insurer transformed its bancassurance service is by using customer analytics and microsegmentation-based customer personas. Based on these analytics, journeys selected were either “fast” (moved directly to the product list) or “long” (with content integration), depending on customer preferences.

Within four to five years, bancassurance penetration almost doubled and first-year premiums increased by 30%-40%, McKinsey said. Several InsurTechs have adopted their own approach in using AI and the digital ecosystem to advance their business, that is, through partnerships.

“Partnerships with leading players — generally the top 15% — to offer select products with simple terms, a short process, and fast and convenient claims can help meet specific user needs for health, auto, life, accident, and other types of coverage,” read the McKinsey report.

“User data analysis can provide insurers with customer insights to inform product innovation and achieve differentiation in the market,” the report also stated.

As an example, the McKinsey analysts cited a leading InsurTech which harnessed its parent group’s platform. Insurance services are embedded in the parent company’s mobile app, which has more than a billion monthly active users. This InsurTech company then integrated its mobile app’s ecosystem, expanding its distribution channels and providing app users with access to offline medical networks not restricted to policyholders.