Asian insurers’ AI-readiness dictates their competitive advantage

Experts reveal why insurers that adapted AI earlier are now realising bigger extra earnings or cost reductions.

Artificial intelligence (AI) will add US$1.1t in annual value in the global insurance industry, analysts say. Of this, approximately US$400b could come from using AI in pricing, underwriting, and promotion technology upgrades; and about US$300b will be from AI-powered customer service and personalised offerings.

Asian insurers as they are now, however, are not fully prepared to take advantage of this multi-billion dollar potential.

“For most Asian insurance leaders, traditional organisational structures with multiple intermediaries and limited in-house tech and data resources make it difficult to visualise, let alone quantify, the potential benefits of investing more broadly in AI,” read a report by McKinsey & Company’s Hong Kong Senior Partner Violet Chung, Singapore Consultant Pranav Jain, and Chennai Partner Karthi Purushothaman.

Critical differentiator
AI has been named by experts as amongst the biggest trends that will shape the insurance industry in the coming years.

When applied in tandem with human resource, AI’s ability to analyze data quickly and accurately will enable vast amounts of data to be leveraged in efficient and innovative ways. This is the main assertion of business management services company, Accenture, in its Insurance Industry 2023 Outlook.

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“What generative AI finally presents for the industry is a very manageably actionable way to start balancing the efficiencies that they’re looking to gain with the experiences that consumers are increasingly demanding in the commercial and in the personal space,” Daria Sharman said in Accenture’s “Insurance News Analysis” segment.

“So when we think about — particularly, I talk about underwriting and the challenges of underwriting — and what generative AI finally does is, it gives underwriters and the actuaries of the world both a strategic and a tactical asset,” added the senior manager for insurance at digital agency, Accenture Song.

In the report “Insurer of the future: Are Asian insurers keeping up with AI advances?”, McKinsey & Company noted that investment in AI is increasingly becoming a source of competitive advantage amongst insurers.

Out of the 1,492 respondents surveyed in December 2022, insurers who reported the most significant gains from AI adoption – 20% or more earnings before interest and taxes – employed advanced  AI practices, use cloud technologies, and spend efficiently on AI.

More notably, these companies are more likely than others to engage in a range of AI risk mitigation efforts.

Accenture Song’s Sharman echoed this sentiment.

“From a risk assessment perspective on the strategy side, what generative AI does with the machine-learning algorithms is [that it] really speeds up that analysis of the data and leverages those algorithms to truly get to an accelerated predictive modeling capability for forecasting anything from just like a climate casualty to personal behaviour changes,” Sharman said.

Challenges for Asian insurers
While some insurers have achieved select wins by implementing AI solutions within individual layers, the transformation required to achieve the full-stack capability that powers the companies mentioned above remains elusive in insurance, McKinsey’s Chung, Jain, and Purushothaman said.
Oftentimes, the problem Asian insurers face is identifying where to start.

“The first step is to determine how AI can support the organisation’s strategic goals and then assess the organisation’s current state of AI readiness across each of the four layers. A simple scoring methodology can help insurers identify their readiness on a scale from one to five for each layer, with stage five signifying the highest level of AI maturity,” the analysts said.

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Another challenge, according to McKinsey & Co, is determining the optimal path forward depending on how far along they are in AI readiness, to reach where they need to 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-, middle- and back-office functions of their companies,” McKinsey said.

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, digital-forward organisation that meets and anticipates customers’ evolving needs with highly personalised, omnichannel experiences, McKinsey 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. 

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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,” it added.
As an example, Chung, Jain, and Purushothaman 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. 

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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.

There’s no question that Asian insurers face challenges in harnessing the potential of AI to create personalised, omnichannel customer experiences. But there is a pressing need to crossover and experts suggest building digital hybrid agencies and exploring bancassurance and ecosystem partnerships as strategic models for embracing AI in the new insurance industry.