Arbitral Analytics: How Moneyball Based Litigation/Judicial Analytics Can Be Used to Predict Arbitration Claims and Outcomes

This paper reviews, discusses, and advances the field of artificial intelligence in the field of litigation analytics and its application to arbitrations. To better explain the weight an attorney, judge, arbitrator, or the public should have towards artificial intelligence and its utilization in the legal field, this paper reviews current AI publications in the litigation analytics field, historical examples, ethical considerations for analytics, and issues surrounding the accumulation of litigation data. Thereafter, this combined knowledge and experience is applied to Federal Industry Regulatory Authority (FINRA) arbitration awards with a novel AI program designed to scrape, index, and analyze these awards to discover insights into which words provide the best chance denying or winning a case for a party. Additionally, the AI was able to extract the award amounts to determine if Benford’s law applied and if any variations worth investigating were found.