Advancing AI across insurance

Download report | NZ case study | How are insurers approaching AI? | Navigating AI's risks | Get in touch

Artificial intelligence (AI), along with generative AI (Gen AI), offers untapped value for those who are willing to embrace change and can navigate the associated challenges.

Whether it’s automated claims, assessing risk, personalisation of products and services, or fighting cybercrime, insurance organisations are increasingly looking towards AI to help tackle complex and time-intensive tasks, and to streamline processes. However, there is an urgent need to pick up the pace in adoption of the technology.

Despite the use of AI in a handful of areas and pilots taking place elsewhere, insurance organisations are not gaining an advantage on competitors by using this technology more widely. Doing so could enable businesses to work faster, more flexibly and develop more sophisticated models in response to the evolving market.

So, how can insurers adopt AI effectively and unlock its full potential?

This report is intended to support insurance leadership teams in using AI to transform their organisations.

It also brings together insights from KPMG professionals and industry leaders from Generali Italia, PassportCard, Prudential and Zurich Australia who share their perspectives on how to unlock the technology's full potential.

Advancing AI across insurance

Unlocking transformation with speed and agility

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New Zealand case study: AI Fraud Detection Model

A client in the New Zealand Financial Services reached out to KPMG for an improved Fraud Detection Rate (FDR) in line with industry standards. KPMG successfully increased their FDR by 300% through designing and developing a composite AI Fraud Detection Model in agile model development cycles.

Overall, the project found three times the yearly customer claims within the pilot and uncovered new patterns of fraud/leakage that were previously undetectable in their claims process.

The key finding was a need for modernisation of the clients auto-accept rules into a scoring approach to balance claim speed with legitimacy risk.

New Zealand case study

Using AI to improve fraud detection rates

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How are insurers approaching AI?

AI offers huge potential benefits for insurers, with the AI market size estimated to grow to US$79 billion by 2032.¹

Leadership teams acknowledge that AI could completely transform their operating models and ultimately, the customer experience. However, insurance organisations appear to be approaching the technology strategically and with cautious optimism.

Many insurers have already started introducing machine learning (ML) or other AI technologies to help improve specific business processes, such actuarial models and fraud prevention processes. In customer service, AI is being leveraged to confirm identity through voice recognition, to provide a timely response to online queries through use of chatbots, and to generate more sophisticated ‘next best actions’ for customer service agents.

With enough training data, algorithms can better analyse risk and predict outcomes, adding accuracy to risk models and pricing structures. Both traditional and Gen AI could empower organisations to enhance actuarial models, deliver personalised insurance cover, or even increase the pace of insurance claims. But the process of doing so appears to be slow, with testing and implementation processes often taking several months to complete.

There is also growing recognition among insurers that a successful AI journey will likely be intrinsically linked to the maturity of their digital transformation. AI thrives on quality data and is best supported by cloud-based infrastructure and agile operating models; firms that are yet to fully embrace this are becoming aware of the urgency to do so.

¹Artificial Intelligence (AI) In Insurance Market Size, Share, and Trends 2024 to 2034, Precedence Research, July 2023.

Navigating AI’s risks

While the opportunities aligned with AI are significant, the associated risks are also increasing. Eighty-five percent of insurance CEOs believe that generative AI is a double-edge sword, in that it may not only aid in the detection of cyber-attacks but also provide new attack strategies for adversaries². Organisations should be mindful of this when developing and integrating AI solutions:

· Confidentiality risks

· Generative AI services ‘hallucinating’ or creating inaccurate outputs

· Data poisoning and drift

· ESG regulatory and reputational risks, given AI’s power demands

· Cultural risks over whether staff are happy to work alongside AI systems.

However, avoiding AI altogether may also expose insurers to the risk of missing out on potential opportunities and benefits, and losing competitive advantage. Doing so presents opportunity risks through reducing organisational knowledge, cutting abilities to develop new products and processes, and the risk of being overtaken by more technologically confident peers.

² 'KPMG Insurance CEO Outlook’, KPMG International, December 2023.

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