ANALYSIS: ARTIFICIAL INTELLIGENCE 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.

Insurers in Asia are ill-prepared to take a slice from the trilliondollar market value that artificial intelligence offers for the global insurance industry, McKinsey & Company’s analysts revealed.

“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’s Hong Kong Senior Partner Violet Chung, Singapore Consultant Pranav Jain, and Chennai Partner Karthi Purushothaman

These legacy structures meant that insurers are missing out on the US$1.1t of annual value. Approximately US$400b of this could come from pricing, underwriting, and promotion technology upgrades. Another US$300b could come from AI-powered customer service and personalised offerings.

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

For most Asian insurance leaders, traditional organisational structures make it difficult to visualise the potential of AI tandem with human resource, AI’s ability to analyse 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.

“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 machinelearning 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

Whilst 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.

“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.

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