Oliver Grossman, a consultant at LCP, has been named young actuarial professional of the year, recognising his major contribution to the integration of machine learning and automation in actuarial work.
As a core member of the team behind LCP InsurSight, LCP's reserving analytics platform, Grossman has played a pivotal role in developing the solution that is now used to assess over £150bn ($190bn) of reserves.
He has designed and developed machine learning algorithms for LCP InsurSight and led the teams in charge of automating two main trend and outlier detection features in InsurSight Predict. In doing so, he was one of the first actuaries to achieve practical benefits from using machine learning in the end-to-end reserving process.
Grossman 's innovative approach has changed the industry. For example, he developed a framework and implemented a process that uses machine learning-backed trend identification to highlight potential under-reserving and unaccounted-for inflation across various companies and lines of business.
Throughout 2024, Oli has also been at the forefront of knowledge sharing. He presented research at various events, including the Institute and Faculty of Actuaries' GIRO 2023 conference, where he demonstrated the application of large language models to capital modelling. He demonstrated how open-source software, in this case, Python, can be used to help build capital models from the ground up.
His work on forecasting reserve deteriorations, presented at the London Market Actuaries' Group has garnered considerable interest in the market.
Grossman's work bridges the gap between traditional actuarial practices and cutting-edge data science techniques. The judging panel also noted the importance of actuaries having strong data science skill to complement their insurance expertise.
Grossman has also helped to drive forward the use of coding in modern actuarial work at LCP. He has developed and delivered a Python training course open to all 1,300 employees in the company, fostering a culture of innovation and continuous learning within the consultancy and the wider market.
Asked how artificial intelligence (AI) is likely to impact actuarial work in the future, Grossman says: "To be really effective, AI needs to work within a transparent framework, and in particular, one that allows for human-in-the-loop feedback. This is what I think the next few years will focus on.
"Take reserving as an example. Reserves are typically set using triangle-based methods, feeding off all available information – meeting-notes with claims handling, underwriting and reserving teams; last month’s results and assumptions; happenings in the external environment; as well as feedback from reserving committees, independent reviews and auditors.
"Where AI would be incredibly powerful, is being able to synthesise all of the above and translating it into justifiable actuarial assumptions for us to review and set. AI will then enable actuaries to spend more time on value-add judgement over the repetitive/mundane tasks, and best of all, allowing us to enjoy doing the ‘fun’ bits at work."