It is of no surprise to anyone reading this that the creation of data, in recent history, has been exponential and previously unfathomable. One major creators of such data is law firms, particularly those referred to as Big Law. Big Law is the industry nickname for the largest law firms, without qualitative definition, it generally refers to the largest nationwide and international firms.
Law firms generally hold large amounts of data spanning at least the statutorily required 7 years, often longer. This data includes the client’s final outcomes like executed contracts, court orders, due diligence reports, as well as the behind the scenes deliberations, drafts, legal research, disclosure documents, matter management, bills and much more. Big Law and Big Data are in fact the perfect partners in automation and analytics.
Set out below are five key areas in which Big Law and Big Data can unite.
One of the low hanging fruit for Big Data and Big Law is the improvement of predictive coding and data analytics to support the document review processes. In law firms, document review is conducted across teams to include disclosure/discovery in litigious matters, due diligence for commercial transactions, regulatory investigations and legal advice work. In all of those work streams, it is becoming increasingly voluminous in nature.
In Australia, this was particularly emphasised in the recent Banking Royal Commission involved the production of documents on a scale leaving banks and lawyers equally scrambling to keep up. The burden of document review is felt most heavily by junior lawyers, engaging in a time consuming task which many are increasingly aware could be completed (or at least assisted) by algorithms trained on previous document review data.
In 2015, the decision Lola v Skadden, Arps, Slate, Meagher & Flom LLP 620 Fed. Appx. 37 (2nd Cir., 2015) in which the Court of Appeal found that a lawyer conducting document review was not engaged in “the practice of law” within the meaning of North Carolina law. Referring to the North Carolina State Bar Ethics Committee opinion which strongly suggested that the definition of “practice of law” requires ‘at least a modicum of independent legal judgment’, the Circuit Judges went on to say that ‘any tasks that can be performed entirely by machines cannot, by definition, involve legal judgement.’
The opportunity to use technology, trained on Big Data, for Big Law, is an opportunity to meet tight client and court time pressures while increasing law firm profits (see opportunities to test different pricing models below). Importantly, it is also an opportunity to ensure junior lawyers are given opportunities to engage in the practice of law that allows for their independent legal judgement and development of legal skills.
There are very few tools that currently exist that can serve as an alternative to legal research through traditional methods, and the current databases like Westlaw and Lexis. However, there is immense opportunity for algorithms to be derived from the research recorded in Big Law to provide insights on case arguments and litigation strategy.
The analytics powered by Big Data for legal analysis relies on “advanced tools [that] take massive volumes of data, structure it and strip out irrelevant or redundant information — then make it readily searchable. These are tasks that would take humans weeks, months or even longer to effectively complete.” The analysis of cases by AI or other machine learning powered by big data has great potential to work through thousands of cases, and previous research by lawyers to synthesis outcomes and prospects.
A white paper investigating the prospects for ROSS showed a significant reduction in research time including 30.3% over boolean alone and 22.3% over natural language alone.
These tools should not replace the “gut feel” or trusted advice of lawyers — they should enable it.
In the current regulatory environment, the onus and public pressure on banks and many other corporations has been increasingly heightened.
The outcomes of the Australian Banking Royal Commission is placing intense scrutiny on Australian financial institutions. This intensification has been felt in the financial services sector all over the world. Following 2008 and the subsequent economic upheaval including the Dodd Frank Act and FINRA regulations, banks and other financial institutions have significant reporting obligations to monitor mass amounts of data. The legal and compliance teams are attempting to manage and monitor insider trading, anti-bribery and corruption, counter terrorism financing and many other financial misconduct that has recently been brought to the fore.
There is obvious potential for algorithms trained on big data from law firms which have historically been conducting investigations for banks and other companies. The efficiency, accuracy and potential breadth for such algorithms is required to meet the increasing demands for regulatory compliance.
Many lawyers, in particular in-house counsels, struggle to efficiently manage numerous contracts. As noted in the Singapore Academy of Law 101 Problem Statements, ‘[i]ssues arise when contract renewal deadlines are forgotten or file notes recording contract negotiations are lost, especially when the lawyer-in-charge is no longer with the company’.
Contract management analytics allows for many important benefits including:
- increased contract lifecycle visibility and analytics;
- increased security and encryptions; and
- simplification of negotiation and re-negotiation for contract assignment or amendments.
With complete visibility over a contract lifecycle, companies can ‘build stronger relationships with customers, suppliers, strategic partners and investors’.
The increasing pricing pressure on in house legal teams which are being translated into pressure on Big Law firms, notably in the shape of alternative fee arrangements, means that it is increasingly important for lawyers to assess and test pricing options based on previous data. Big Law has pricing information and billable hours relating to a multiplicity of matters, clients and transaction types that would allow greater insight and predictions of various pricing arrangements. Using their existing data, law firms can conduct due diligence to find which pricing model best suits their practice and clientele.
In turn, this brings clients greater confidence in fee estimates, reducing the anxiety of bill blowouts with the billable hour and improving cost transparency; gives lawyers greater confidence in their profitability and improves pitching for work. It may in time reduce the pressures on lawyers internally to measure value through the billable hour — although that is another post in and of itself.
In summary, the benefits of big data for big law is highly valuable to lawyers and their clients. It offers:
- new opportunities for growth;
- increased profitability through new billing arrangements;
- increased time efficiency; and
- job satisfaction and opportunities for growth for junior lawyers.
As a final side note, it should be remembered that, the potential ethical considerations to challenge and potentially overcome remain an important factor for lawyers and technologists to always consider.