Technology

Time Machines: Using AI To Track Regulatory Change

Once these tools have been adopted, legal professionals are empowered to leverage these efficiencies in a way that benefits their department or law firm fully.

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Last month, we covered the potential for AI to play a role in predicting outcomes for transactional law and inform strategy around future regulatory changes. So the next logical question is: “What role does AI play once a new regulation goes into effect?”

Just as it is a labor-intensive and time-consuming task to predict outcomes, tracking and determining the impact of regulatory changes once they have taken place is a challenging — yet necessary — task for transactional law professionals. And it requires more than subject matter expertise.  In order to monitor changes, interpret their meaning, and determine impact, lawyers need to have all of the relevant information available, the ability to easily move back and forth between documents, and a full comprehension of these insights in order to apply them to a client’s business.

Let’s look at the passage of the Tax Cuts and Jobs Act of 2017 as an example. Although the legislation has already been signed into law, it contains a number of technical issues and matters that have yet to be fully clarified. As a result, tax attorneys must constantly monitor these matters for updates. For instance, a couple of months ago the President signed into law a Consolidated Appropriations Act which included a section to fix the “grain glitch” (a provision within the Tax Cuts and Jobs Act that provided significantly higher tax deductions to parties that sold commodities to cooperatives rather than to non-cooperatives).

In order to understand the impact each time an update or clarification such as this is made, one needs the following:

  • A copy of the newly updated language;
  • A copy of the relevant section within the Tax Cuts and Jobs Act (which, itself, is hundreds of pages long); and
  • A copy of the relevant section of the tax law that existed prior to the Act’s passage.

As one can see, effectively tracking changes requires legal professionals to sift through several versions of the same section of a law and — in the present day — do so as quickly as possible.

This becomes even clearer in the face of a client inquiry. I’ve heard from multiple law firm partners that providing clients with updates in real time is a constant challenge. Ten or so years ago, it was common for a lawyer to receive a call from a client in the morning with a question, take the time to research it, and give the client a call back with an answer in the afternoon. In the current environment, it seems that lawyers are expected to provide answers much more quickly. This is indicative of a larger challenge across the practice of law — keeping pace with heightened expectations while delivering accurate, timely, and value-adding analysis to best advise clients.

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So now let’s look at the application of AI in this area. Application of AI technology requires many of the same assets we’ve discussed here in the past, namely sufficient and consistent data (in this case, different versions of a law), and an algorithm to train with this data. Different versions of a document could be fed into the algorithm, which could be trained to identify text changes in different versions of the same section of a document. The algorithm could then review the different versions of a document, identify the changes in each, and then highlight those changes for you — whether language is added, removed, or edited.

This process would save the time of not only locating the relevant sections within the documents, but also reading through both versions to draw out the language that is different in each. If a machine can do this piece of the work for you, you’re left with the (comparably value-adding) task of determining what these changes mean for your client. As an example, Wolters Kluwer premiered a solution called Standard Fed Plus last year, and users have reported more than 45 minutes of saved time per issue when using the tool.

Rule checking is another area in which this use case applies nicely. Securities lawyers keep close track of changes that the Securities and Exchange Commission (SEC) make to rules and regulations — but doing so can be difficult if you’re not a full-time Commission watcher. The SEC will typically make very specific updates or changes to a part of a rule or regulation. The task of sifting through a rule to identify what has changed and what hasn’t — and then determining the impact — can take hours of work.  To identify changes to a rule that impact disclosures, a securities attorney typically takes the following steps:

  • Identify the SEC-mandated change that has taken effect;
  • Locate any sections of a client’s disclosure package that are impacted by this change; and
  • Determine what changes should be implemented in a client’s disclosure package in order to comply with the SEC-mandated change.

A similar application of AI would make it easier to complete this work quickly and efficiently. Providing an algorithm with all the relevant information and training needed to identify changes within rules would allow for a more comprehensive and accurate work flow when filing disclosures.

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Once these tools have been adopted, legal professionals are empowered to leverage these efficiencies in a way that benefits their department or law firm fully. The time and money-saving aspects are apparent — but beyond that, these tools provide opportunities to add significant value for clients as well as for the firm. That will be the focus of next month’s article — how does one measure the value of a technology solution?

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Dean Sonderegger is Vice President & General Manager, Legal Markets and Innovation at Wolters Kluwer Legal & Regulatory U.S., a leading provider of information, business intelligence, regulatory and legal workflow solutions. Dean has more than two decades of experience at the cutting edge of technology across industries. He can be reached at Dean.Sonderegger@wolterskluwer.com.

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