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ARTICLE BY

  • Fidelis Masheka
  • Head of Finance and Profitability
  • Old Mutual Insure

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AI-powered underwriting helps the insurance value chain with faster decisions and better pricing – and no, it will not put brokers out of jobs.

The rapid adoption of artificial intelligence (AI) and other technologies is seeing non-life insurers reimagine every part of the insurance value chain, from claims management to compliance, distribution, product design, and underwriting.

Significant scope for emerging tech

AI solutions are increasingly deployed in underwriting to accelerate decision-making, enhance accuracy, and optimise enhanced risk pricing strategies. There is significant potential for AI to refine data collection, improve risk scoring, and streamline decision-making. At Old Mutual Insure, we aim to leverage this technology to deliver more precise, risk-appropriate pricing and enhance overall underwriting efficiency.

In practice, we are already making strides in the motor insurance class, using AI to assess driver behaviour “harvested” by another recent tech innovation, the telematics device. Over time, customers with safer driving habits will benefit from lower premiums based on real-time enhanced risk pricing carried out over live behaviour-related data. Similar gains await in property underwriting, where AI models can recommend risk mitigations and predict the likelihood of future claims by analysing photos or data streamed from connected devices.

Benefits and risks

AI adoption already offers measurable benefits for insurers. According to a report by Accenture, “Why AI in Insurance Claims and Underwriting? Improving the insurance experience”, widespread AI use in underwriting can improve operational efficiency, potentially reducing insurers’ combined ratios by up to 16%. However, these gains must be balanced against challenges, including inherent biases in AI models and compatibility with legacy systems. Insurers must ensure that the historical data used to inform their models does not compromise fairness in decision-making.

Compliance and risk management teams will also need to address ethical and regulatory challenges. Adherence to data protection laws, such as the European Union’s GDPR, which governs the processing and transfer of personal data within the EU, as well as South Africa’s Protection of Personal Information (POPI) Act, will require careful oversight. Insurers must establish clear guidelines for using personal information in automation to ensure compliance with these laws.

Advantages for brokers and customers

AI’s potential to enhance efficiencies in underwriting will transform our intermediated distribution network too. Brokers can expect faster decisions and competitive rates that reflect the true risk profiles of their clients. By automating repetitive tasks, AI will free brokers to focus on advisory services and relationship building, strengthening their contribution to the insurance value chain.

Investments in AI are significant, with leading domestic insurers already spending millions of rand on this and other technology. Customers may wonder how they will benefit from these expenditures. The answer lies in two key outcomes: First, AI reduces costs by automating underwriting processes that previously relied on costly manual assessments. Second, policyholders collectively benefit from the setting of risk-appropriate premiums.

AI algorithms can process vast amounts of data at speeds unattainable by human underwriters, enabling faster, data-driven decisions. These efficiencies, derived from advanced data analysis and predictive modelling, will improve customer experiences and help brokers and insurers write more business.

And no, AI will not put brokers out of jobs. The reality is that human expertise remains vital throughout insurance – AI complements brokers’ expertise rather than replacing it. Stated differently, AI improves operational efficiencies, but it cannot replicate the personal connections that brokers bring to the table.

Delivering future value
AI algorithms that are capable of assessing risks and predicting future claims create a win-win-win scenario for brokers, insurers, and policyholders by delivering competitive, risk-appropriate rates. For insurers, the effective adoption of AI will deliver a competitive advantage in acquiring new policyholders and retaining existing ones.

As for the future, Old Mutual Insure expects AI-powered underwriting to become more autonomous as our data resources improve. We envisage a virtuous cycle where AI applications generate new data for continuous learning, enhancing accuracy and efficiency over time. The technology will enable personalised insurance products and allow insurers to improve risk management and profitability while delivering more value to brokers and policyholders.

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