Insurers Embrace AI Innovations in Australia, New Zealand

Insurers in Australia and New Zealand are increasingly adopting artificial intelligence (AI) and generative AI (GenAI) to enhance their operations, improve customer experiences, and manage risks more effectively. According to a recent report by Information Services Group (ISG), insurers in the region are investing in new technologies and services, including AI, to become data-driven and digital-first organizations.

AI adoption rates among insurers in Australia and New Zealand are on par with global averages. A survey conducted by KPMG in 2023 found that 52 percent of respondents picked AI (including machine learning and GenAI) as the most important technology in helping them achieve their ambitions over the next three years. Additionally, 58 percent of CEOs in insurance felt confident about achieving returns on investment within five years, indicating a significant degree of trust in AI among Australian and New Zealand insurers.

The most promising AI use cases for insurers in the region align with global trends, focusing on enhanced underwriting, predictive risk assessment, and personalized product recommendations. Here are some specific examples and data points to support this:

1. Enhanced Underwriting and Risk Assessment:
- Generative AI can help insurers simulate future scenarios, enhance risk estimation, and drive better pricing (KPMG, 2023).
- AI can identify false claims more effectively, reducing fraud and improving risk management (KPMG, 2023).
- In Australia and New Zealand, P&C insurers are implementing data analytics to improve risk assessment and customer segmentation, leading to better decision-making (ISG Provider Lens™ report, 2024).

2. Predictive Analytics and Personalization:
- AI can help insurers predict customer churn, identify cross-selling opportunities, and personalize product offerings (EY-Parthenon GenAI in insurance survey, 2023).
- AI-driven chatbots and virtual assistants are streamlining customer queries and claims processing, providing quick and CX-friendly responses 24/7 (KPMG, 2023).
- In the region, insurers are integrating traditional and digital channels to improve and personalize customer service (ISG Provider Lens™ report, 2024).

3. Fraud Detection and Cybersecurity:
- AI can help insurers detect fraudulent claims and activities, reducing losses and improving overall profitability (EY-Parthenon GenAI in insurance survey, 2023).
- AI can also help insurers manage cybersecurity risks by identifying potential threats and vulnerabilities (KPMG, 2023).
- In Australia and New Zealand, insurers are adopting AI for fraud detection and cybersecurity (ISG Provider Lens™ report, 2024).

Insurers balance the risks and benefits of AI implementation, particularly in terms of data privacy and cybersecurity, by taking a dual-track approach that combines rapid experimentation with methodical long-term planning. This approach allows them to leverage AI's potential while mitigating associated risks. Here's how they do it:

1. Rapid, bottom-up experimentation: Insurers promote rapid, bottom-up experimentation to define viable use cases for the near term. This approach enables them to test AI applications in specific areas, such as fraud detection or customer service, without exposing the entire organization to risk. For example, EY's research found that insurers are actively exploring and implementing AI applications, with 52% of respondents picking AI as the most important technology for achieving their ambitions over the next three years (KPMG, 2023).
2. Methodical, top-down planning: Simultaneously, insurers develop an enterprise-wide AI vision with the necessary infrastructure, governance, and capabilities to execute it over the long term. This methodical approach helps them address potential risks and ensure responsible AI implementation. For instance, the National AI Centre (NAIC) in Australia is working with market research firm Fifth Quadrant to track AI adoption and perception among SMEs, highlighting the importance of understanding and managing AI risks (NAIC, 2024).
3. Strong underlying governance: To balance risks and benefits, insurers establish strong underlying governance structures. This includes:
* Data privacy: Implementing robust data privacy measures, such as anonymization, encryption, and access controls, to protect sensitive customer and operational data. For example, the ISG Provider Lens™ report (2024) highlights the importance of controls to prevent data leakage from AI models in the insurance industry.
* Cybersecurity: Strengthening cybersecurity measures to safeguard AI systems and data from unauthorized access, attacks, or manipulation. The NAIC's research (2024) indicates that while businesses feel confident about managing regulatory compliance, there is room for improvement in cybersecurity readiness.
* Ethical considerations: Ensuring that AI systems are fair, unbiased, and transparent, and that they respect ethical principles and regulations. EY's research (2024) on the use of generative AI in insurance emphasizes the importance of addressing ethical concerns and responsible AI implementation.



In conclusion, insurers in Australia and New Zealand are embracing AI innovations to enhance their operations, improve customer experiences, and manage risks more effectively. By adopting a dual-track approach that combines rapid experimentation with methodical long-term planning, insurers can balance the risks and benefits of AI implementation, particularly in terms of data privacy and cybersecurity. As AI continues to evolve, insurers in the region will need to stay informed and adapt to new technologies and trends to remain competitive in the global insurance market.