Generative artificial intelligence models are 10,000 times more powerful compared to just five years ago. An increase in power on this scale creates significant opportunities for insurers.
The life insurance industry is at a turning point, with rapid transformation being driven by factors including technological innovation and changing market dynamics.
AI in particular has the potential to redefine traditional practices and revolutionise the entire value chain, from greatly improving customer services and risk assessments, to retention and policy customisation.
AI for code – the next big milestone
The use of GenAI for coding for in-house applications is set to be the next big thing in 2024 as the industry realises just how powerful the latest models have become and insurers find ways to leverage this power.
In a recent conversation, a non-executive director in a major UK insurance firm revealed that they had already started using GenAI for a coding project to translate all the code from the insurer’s entire legacy box of business into their preferred code to sit more efficiently with their newer main block of business.
When looking at exactly how these technologies can positively impact our day-to-day work, the writing of computer code is a prime example of a core application of AI. For example, an AI coding system can help generate and test code, as well as assist in the debug process, which many developers struggle with.
AI can also significantly help to improve documentation and adherence to coding best practice.
AI technologies can also facilitate code translation, such as transforming an Excel macro file into an open-source code like Python or R, with the endgame of fitting such applications into a better governed process.
There are many other applications of GenAI that can help the insurance industry, such as report drafting, checking the consistency of reports in large groups or compliance with group or professional standards, and process automation that requires collation and large numbers of documents to be inspected.
Insurance firms are also undertaking competitions internally to see who can come up with the best GenAI use case, such as feeding GenAI an insurer’s complete collection of training and underwriting manuals to create an expert bot.
This approach also benefits from avoiding the risk of any external interaction, which is sensible for insurers in 2024 that are considering how best to use GenAI, while a better understanding and a level of control are still being established.
AI regulation on the rise
The opportunities of AI do not come without risks, which means implementing AI must be approached with care.
As AI becomes progressively more integrated into insurance industry practices, regulatory oversight is also on the rise. This means insurers need to make sure that their AI practices comply with relevant regulations.
With such a heavy reliance on data, protecting data privacy and maintaining ethical standards are crucial. For this reason, insurers will need to comply with data protection regulations and handle personal or sensitive data ethically when using AI.
