The firm has embarked on a mission to predict outcomes on volume litigation and complex claims.
Insurance law firm BLM is working with the London School of Economics to develop a new model in litigation risk management. The law firm has teamed up with the university for two years to develop prediction models to guide BLM’s advice to its clients, as well as more sophisticated approaches to value litigation risk, improve decision-making and better manage portfolios of litigation risk. The new partnership will help BLM further diversify into additional areas with the potential to develop new services for new clients in other markets. It follows BLM's earlier steps to provide an innovative offering shaped around the advanced analytics capability in 2017, starting with the appointment of its head of analytics, Andrew Dunkley.
The partnership with LSE sees three professors work with BLM. Professor Henry Wynn, Chair of the Centre for the Analysis of Time Series and Head of the Decision Support and Risk Group, will lead the LSE side of the partnership. Also involved are Professor Pauline Barrieu, Head of LSE’s Statistics Department and Principal examiner for the Institute of Actuaries, who has extensive experience of the insurance sector, a traditional area of strength for BLM and Professor Milan Vojnovic, Chair in Data Science and expert on machine learning. They will be supported day to day by a dedicated post-doctorate fellow who will work closely with BLM’s Analytics team. The project will be co-funded by BLM and LSE’s Knowledge Exchange and Impact Fund.
Analytics to add value
BLM’s Analytics offering aims to add value beyond providing data about claims. BLM has long believed that the volume of case data generated by the insurance and other sectors provides a valuable resource, and that this can increasingly be exploited by the speed and accuracy of data analytics and artificial intelligence (AI). The approach provides tools and insights that better equip the firm’s lawyers and clients with the knowledge they need to make the right decisions at the right time.
The project will deliver valuable advances in relation to both volume litigation (which is often more amenable to AI and machine learning), and to high value complex claims. This will include exploring AI and statistical predictive models for valuing disputes and predicting outcomes, predicting cost overruns and case length and managing litigation at a portfolio level. The focus is on managing litigation risk, which will be achieved by taking full advantage of the legal, statistical, actuarial and AI skills of the combined BLM and LSE teams.
Andrew Dunkley, BLM’s Head of Analytics, said of the deal: 'LSE is a great, global brand and we are working with a team whose combined skills go to the core of what this is commercially all about – better valuation and management of litigation risk for individual claims and portfolios of disputes. There is a strong technology and AI component to this project, but we think combining this with decision science and actuarial expertise will lead to even more exciting developments in litigation risk management.Analytics are increasingly critical to risk assessment and claims management. This is a step forward for BLM in driving innovation that tangibly benefits our clients in relation to volume litigation and for high value claims. We look forward to working with LSE as we invest in this collaboration to deliver a better service to our clients.'
Greater predictability of outcomes
Professor Henry Wynn from LSE highlighted the potential opportunity which lay behind this work with BLM: 'This collaboration seeks to explore greater predictability of outcomes to try and determine the optimal strategy for litigation. The LSE Statistics Department and its Decision support and Risk Group has a substantial interest in quantifying risk and uncertainty. Building up a joint centre of research excellence in the valuation and management of litigation risk with BLM is an exciting development in this area, with a clear commitment on our part in terms of the investment and funding of this work. We look forward to working together to develop BLM’s ability to forecast the outcome, cost and length of litigation, and to understand what drives these factors.'