How AI could change insurance

The numbers are staggering. ChatGPT amassed 100 million users in its first two months, only for that record to be smashed a few months later by rival Threads, with 100 million users in just five days.

It took TikTok roughly nine months to reach that number of users and Instagram two-and-a-half years, but the uptake of ChatGPT after it launched in November 2022 was unprecedented. The speed of its adoption prompted a wave of speculation in the media and business world about the disruptive potential of such technology.

With digitalization increasing rapidly in many areas of life, the amount of data that can be leveraged is proliferating. As a data-driven industry, insurance is not new to artificial intelligence (AI) or using data analytics across its value chain to improve products, interactions, prevention, claims and processes. According to several studies, the industry is among those with the highest value potential from AI.

Estimates point to the market potential of generative AI (GenAI) reaching $15 billion by 2025 and $32 billion by 2027 in the insurance and finance industries alone. McKinsey foresees AI technologies could add up to $1.1 trillion in potential annual value for the global insurance industry.

AI versus GenAI – what is the difference?

Put simply, there are two types of AI application. The first uses AI’s ability to identify patterns in data and draw conclusions or make predictions from them. The second, GenAI, uses large language models (LLMs) trained on vast existing datasets to generate new content that mimics human creativity, whether it is images, text, coding, music, art or interactive simulations.

AI enables insurers to enhance their value proposition by better predicting and therefore preventing risks. AI depends on having good-quality data. We are constantly evolving and expanding our data quality across the business at Allianz — not only at Allianz Commercial, but across all Allianz entities — to train the models we use. This can help us assess and model extreme weather events, for example, gathering data on secondary perils such as floods. Or, by constantly improving the granularity of our location data, we can help corporate customers better identify climate-risk exposures.

AI can take on the role of ‘cool problem solver.’ By enabling us to adopt a more predictive, preventive and proactive approach, AI can shift our perspective from looking behind us in the rear-view mirror, and paying out claims, to evolving into an organization with a sharper view of the road ahead, supporting clients in preventing and mitigating risk, and avoiding losses. The power of AI-generated insights can help businesses and societies become more resilient.

As more data and risk intelligence becomes available, particularly for weather or cyber exposures, AI could enable insurers to provide coverage for emerging risks and technologies that are not yet insurable today, including parametric solutions.

Impacts on the insurance value chain

The potential of GenAI across the insurance value chain is an exciting prospect. Open AI’s ChatGPT hit the headlines first, but it has now been joined by Microsoft’s Co-Pilot and Google’s Bard as the most prominent tools in the market.

A wider range of risk data will enable underwriters to offer more targeted, bespoke insurance solutions and smarter pricing. GenAI will also automate underwriting tasks, including data extraction, and wording comparison.

Larger datasets will also provide more scope for GenAI to pick up anomalies or unusual patterns of behavior that could indicate fraud. Loss triggers could be spotted, and future claims could be better predicted, including claims surges. GenAI’s ability to analyze images and videos could be another useful tool in the claims process.

Risks and challenges

Although they are the focus of much excitement, GenAI solutions are in the early stages of development, with risks and limitations insurers must address before the technologies can be safely rolled out.

When it comes to affecting employment in insurance, we see the impact of AI as an evolution rather than a revolution, creating new jobs and changing existing job profiles gradually over a number of years. AI is not a replacement for human emotional intelligence, which is so important in the workplace. We see new roles being created for professionals who can develop, implement, and manage AI systems and evolve existing ones. AI will largely affect job profiles as a supporting, complementary technology, providing vast opportunities for digital upskilling.

Along with the opportunities offered by GenAI come significant risks such as data protection, confidentiality, ethical concerns and liability exposures. AI and GenAI solutions are only as effective as the data they are trained on, and historical data can reflect inequalities GenAI could perpetuate by creating biased content, possibly leading to discrimination.

GenAI can also create convincing-looking information that is factually incorrect, a process called hallucinations. This is already being used by cyber criminals to commit new types of fraud, phishing emails or generate deep fakes — digitally altered hoax videos using footage of real people.

AI has been a key strategic topic at Allianz for several years, and new trends are continuously monitored and explored by the company’s global team of data scientists and AI experts. Data is a core element of the business. Technology and data analytics are increasingly at the heart of what insurers do.

How AI is accelerating cyberattacks

Threat actors are already using AI-powered language models like ChatGPT to write code. GenAI can help less technically proficient threat actors write their own code or create new strains and variations of existing ransomware, potentially increasing the number of attacks they can execute.