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How Generative AI is transforming South Africa’s Non-Life Insurance Industry

ARTICLE BY

  • Nicholas Dempsey
  • Executive for On Platform Business Solutions
  • Old Mutual Insure

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Generative artificial intelligence (Gen AI) is reshaping industries across the globe, with non-life insurance being no exception. In South Africa, insurers are already leveraging this powerful technology to streamline operations, improve customer experiences and accelerate quotes handling. But the impact goes beyond efficiency: Gen AI also holds promise for tackling long-standing challenges like financial exclusion and fraud, opening the door to a more inclusive and responsive insurance sector.

Generative AI, first unleashed in late 2022, has already changed the way that many organisations operate. The ability of large language models (LLMs) like ChatGPT to read and write, as well as analyse vast amounts of data, has meant many high-volume, low-value tasks are now best left to machines.

In the non-life insurance industry, there is a growing trend to use Gen AI to engage with customers using chatbots, generate quotes quickly, assess risks more accurately and detect insurance fraud. As with any new technology, adopting it to existing systems takes time, which means the potential gains from Gen AI won’t be felt overnight, but they are nevertheless promising, especially as far as saving time and money are concerned, as well as improving accuracy.

Chatbots

Already, AI-powered chatbots are widely used in the non-life insurance industry. Customers can talk to them to ask questions, request a quote or update information. They can provide instant responses to client queries, enhancing customer engagement.

An example of a chatbot is Old Mutual Insure’s Usage-Based Insurance (UBI). Launched during COVID-19, UBI lets vehicle policyholders submit monthly odometer readings via WhatsApp to earn premium discounts for driving less.

Speeding up the quotes process

Gen AI is streamlining quote generation by analysing client documents and extracting key data to produce accurate, risk-matched quotes in minutes. At Old Mutual Insure, this has not only improved the accuracy of our data capturing but also significantly shortened turnaround times and, in turn, improved the overall service for both our customers and brokers. In terms of underwriting and claims, we are still exploring ways to dovetail AI’s immense capabilities with our needs. Gen AI tools can make underwriters and claims assessors become more efficient by automatically surfacing the rules for each individual insurance case. Less time searching for rules will mean enhanced productivity, fewer errors and more accurate risk profiling.

Inclusion and integrity

However, Gen AI isn’t just about speed and automation – it’s also helping insurers solve deeper, systemic issues. Financial exclusion remains a major hurdle in South Africa, especially for underbanked communities. Gen AI can help by analysing alternative data to create personalised, affordable policies, automating onboarding to reduce friction and deploying multilingual chatbots to guide users in plain language.

At the same time, fraud detection is getting smarter. Gen AI can flag anomalies in claims, cross-check documents for tampering and analyse behavioural cues in communications – all in real time. That means faster payouts for genuine claims and stronger protection against synthetic fraud.

Cost of automation

As with all new technology, there are downsides, too. One of the biggest potential hurdles in adopting generative AI is data privacy. Insurers who use this technology must ensure that client data is handled securely and in compliance with regulations, such as POPIA and the South African Cybercrimes Act. Another challenge is how to integrate Gen AI with existing systems, which can be complex, as well as training brokers to work alongside AI tools effectively.

At Old Mutual Insure, we have a change management strategy in place to integrate human and Gen AI capabilities. We believe the AI revolution can yield tangible business results, address risk concerns, overcome skills gaps and foster innovation. But our staff need to be involved in both building the tool and ensuring uptake. To achieve this, each product line has its own dedicated change champion who acts as an intermediary between users and the Gen AI working group. In this way, we’re able to develop statement-of-work templates to meet users’ needs, while communicating with users and improving their skills.

The transformative impact of Gen AI on the non-life insurance industry can’t be underestimated, streamlining quotes and personalising service. While challenges exist, the benefits in operational efficiency and enhanced broker-client interactions make a compelling case for adoption, leading to less paperwork and more human contact.

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