ACC releases new guide to help in-house counsel use data analytics to predict and manage legal risk

Resource released by ACC Docket lists steps for gathering data, analyzing trends, applying insights
ACC releases new guide to help in-house counsel use data analytics to predict and manage legal risk

A quick-start guide released by the ACC Docket, the Association of Corporate Counsel’s publication, offered a practical approach to implementing data analytics in legal practice.

In today’s rapidly changing legal environment, in-house counsel need to predict and manage risks effectively, the resource said. By leveraging technology and data analytics, legal professionals can enhance their predictive capabilities, improve case management, and ultimately contribute to their clients’ financial success, the guide explained.

The guide provided by the ACC Docket outlined steps for gathering relevant data, analyzing trends, and applying insights to achieve cost control and efficiency.

The resource identified the first step in using data analytics as collecting comprehensive, relevant, accurate, and timely data from both internal and external sources, which should be diverse and high-quality sources.

This data would include claim history, customer information, market trends, weather patterns, and industry reports, the guide said. IoT (Internet of Things) devices, such as sensors and wearables, could provide real-time data and could offer deeper insights into potential risk areas.

The second step, according to the resource, involved analyzing the data gathered to identify patterns and trends. To uncover these trends, the resource suggested that in-house lawyers employ tools like predictive analytic software – such as Lex Machina, Judicata, Lexis+ AI, Westlaw Edge – as well as machine learning and statistical modeling.

Trend analysis could, for example, reveal seasonal increases in specific types of litigation or highlight areas within operations carrying higher risks, the guide said.

The third step, according to the resource, entailed forecasting future risks through developing predictive models using the patterns and trends identified through data analysis.

The enhanced predictive capabilities of these models could transform legal practices, including by helping in-house counsel assess cases more efficiently, expedite claim settlements, and detect fraudulent claims through comparing them against historical data, the guide explained.

The last step was for in-house counsel to craft proactive risk management strategies, armed with insights from predictive analytics, said the resource. These strategies would help companies avoid costly incidents and litigation and thus boost profitability, the guide added.

For example, if data analytics indicated a high likelihood of workplace incidents or seasonal increases in certain claims, the resource suggested that in-house lawyers advise their clients on potential exposures and suggest adjustments to policies and procedures.