How legal tech enables highly scalable business channels
By Tianlu Qu
Lawyers are artisans. Most of the value they deliver stems from their human capital: decades of experience with a sharp and analytical mind. However, if one leverages almost entirely on human capital, one can only grow new businesses proportionately with expertise and, more likely, time.
Engineers learned a long time ago that by designing easily duplicated machines to take over part of their human capital, they could scale production exponentially while saving time. That saved time could then be set aside for creative work, such as improving those machines (assembly lines, computer program, etc.)
Lawyers certainly also rely on “capital machinery” to make their jobs more efficient: computers, digital assistants and contract management tools. However, this misses an important point: lawyers do not leverage on their skills in typing contracts or managing portfolios to make money. Lawyers rely on legal thinking. Can lawyers then leverage on some technology to do some of this “legal thinking” for them?
The problem with contracts
One of the most time-consuming activities a lawyer performs is document review. Advances in technology such as Natural Language Processing and Machine Learning have certainly precipitated efficiency-driving Artificial Intelligence (AI) tools that can speed up the process. However, many lawyers are still struggling to derive further value from these tools beyond relatively generous time savings. After all, cutting contract review time by half can only double your revenue at most. Herein lies a more fundamental issue in how contractual documents are designed.
The fundamental essence of a contract is still a story-telling narrative. Every contract ever agreed performs the same basic task: it asserts the rights and duties of the parties in a way that can be enforceable should the need arise. However, every lawyer approaches the task of drafting and structuring such contracts in a different manner. The same meaning can be asserted in hundreds of different ways, simply by using different words to say the same thing. This lack of standardisation makes it challenging, even for AI tools, to inter-operate between contract types and is limiting their potential.
The solution with standards
The solution lies in a standard digital contract language: a meanings-based framework that is designed to describe any contract without dictating methods of drafting. This means that drafting differences become irrelevant because the framework is focused on the meaning of the words, and the models infer from different drafting possibilities. One such example is ThoughtRiver’s Lexible framework, which is developed by experienced lawyers and leading-edge computational linguists. The framework consists of thousands of data-points that are logically structured much like how a human lawyer would approach contract review. In practice, this framework underpins ThoughtRiver’s AI capabilities, which extract critical information from contracts based on the Lexible framework. On top of this, the platform then applies user-customised playbooks to apply a risk interpretation.
Benefits of digital contract language
The ability to develop automated tools against a universal contract language has unlocked exciting new opportunities for lawyers. They are no longer working with tools that benefit only the immediate client project and having to re-invent the wheel each time. They can now simply extend their own module (think specialised contract area), keeping it updated from time to time, and that can be sold on to not only their own client base, but anybody in the community using the same standard. Lawyers would then effectively be codifying their accumulated expertise and building an infinitely replicable machine that delivers value on their behalf. A veritable robotic legal factory.
The market significance of this new channel of delivering legal expertise is phenomenal. Lawyers are creating a predictable and recurring new revenue stream. The technical infrastructure can also be designed such that automated expertise is delivered without giving away any of the lawyer’s proprietary design of their “automated review modules”. Because any user within the community has access to these modules, law firms can potentially increase their penetration far beyond the industrial and geographical reach that their scale may suggest. It also establishes the law firm as an expert in specific subject matters and serves to entrench an existing market position, as well as open new doors.
Example: Lexible partners
Partners either provide services via the ThoughtRiver platform directly to end-users or provide complementary services to ThoughtRiver customers to support them in configuring the ThoughtRiver platform for their needs. Currently, Taylor Vinters is developing risk playbooks within Lexible for certain contract types. All of ThoughtRiver’s users are then able to use these premium risk policies when reviewing contracts and Taylor Vinters gets commission based on usage. Another use case is how Eversheds Sutherland Ignite is creating and maintaining Lexible modules for the review of contract types that fall under its area of expertise. The firm can almost immediately deploy these modules for automated review of each new client’s contracts. It’s like having a new service centre that never sleeps.
Although latest research has shown that the legal sector has grown in the past decade, it is more than prudent for law firms to start considering these new revenue streams as alternative providers of legal services exemplified by the Big Four professional services firms’ move into the sector. GCs are also leveraging on technology tools to take back work such as contract review. These pressures are already starting to impact the bottom-line. Considerations for implementing the aforementioned new business channels are not purely defensive either. A lawyer with an expertise in any contract area can become a “winner” very quickly and “take almost all” of the market share in that area. As with other digital industries, first movers would have a significant advantage.
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