Lawyers BLM use AI to predict insurance claim case outcomes
Insurance law firm BLM is trying to predict the future – it is using artificial intelligence (AI) systems to help it forecast the outcome of insurance claims cases. The company has set up an analytics team of data scientists that will seek to predict the length, cost and likely outcome of claims litigation. “This is not about replacing lawyers," said Andrew Dunkley, a solicitor and the head of analytics at BLM. "It’s about giving them tools to help them make better predictions." The firm hopes the forecasts will help lawyers make quicker, more accurate decisions and reduce costs.
Insurance law firm BLM has set up a specialist data analytics team to help its lawyers make better predictions about their cases.

Headed by a solicitor and a data scientist, it uses machine learning, a form of artificial intelligence (AI), to predict the length, cost and result of litigation.

Andrew Dunkley, solicitor and head of analytics, told Legal Futures: “This is not about replacing lawyers. It’s about giving them tools to help them make better predictions.

“It’s like making weather forecasts. We want to make our statements to be as precise as they can be, so lawyers can decide whether to get their umbrellas out.

“Over time the weather industry has become much better at forecasting and law firms are on the same journey.”

Mr Dunkley qualified as a construction litigator at Herbert Smith, as it then was, before moving to Withers, where, in a change management role, he led the firm’s response to the Jackson reforms.

“I became very interested in the litigation funding and after-the-event insurance industries, which led me into thinking about how to predict case outcomes, or in Jackson’s case, costs.

“I’m not a computer scientist or a statistician, I’m a lawyer – just quite an unusual one.”

Mr Dunkley is joined in the analytics team by David Elliott, a data scientist who has spent most of his career working for hedge funds.

“We aim to combine cutting-edge computer techniques and legal understanding,” Mr Dunkley said.

“An unusual synthesis of skills will be the key to improving our predictive power. We have no set goal in mind, but this will be demand-led and things are moving very quickly at the moment.

“We’ve had a fantastic response from clients. The hard task is deciding what not to do first.”

Mr Dunkley said the insurance industry was investing in its own data analytics capability.

“It’s not mutually exclusive. We have a wealth of data across a whole industry. There are also plenty of data analytics companies out there. But the data is more important than the tools, and law firms have the data.”

Mr Dunkley said the team aimed to help litigators take earlier decisions, have greater confidence in making them, increase the accuracy of their predictions and help lawyers understand uncertainty and risk.

Mike Brown, senior partner at BLM, added: “The huge amount of case data generated by the insurance industry comes hand in hand with the need to make decisions easier, quicker and with greater certainty.

“The growing demand for price and resourcing efficiency has highlighted a key gap that will only be bridged by those with a sharp understanding of legal processes, supported by the added speed and accuracy of data analytics and AI.

“Not only will we be able to improve results for customers but we’ll also be better placed to add value in litigation.”

In 2014, London firm Hodge Jones & Allen teamed up with a leading academic to pioneer a predictive model of case outcomes to enable the firm to better assess the viability of its personal injury caseload.