Given the disruptive effect of big data on nearly every industry, it may surprise some that it is only beginning to make inroads into the legal industry. The legal profession, however, is different from others in several key ways. First and foremost, it is a naturally conservative line of work. There is also the (slowly changing) stereotype of lawyers being averse to math and perhaps more inclined to use a legal pad than an iPad.

Law firms are also rather unlike traditional enterprises, as they are partnerships more than they are businesses. A partnership doesn’t put enough emphasis on business efficiency – try and think of another example of a consulting service in which project management isn’t standard.

Perhaps most crucially, there are often legal restrictions on how data can be handled, says Isabel Parker, director of legal services innovation at Freshfields Bruckhaus Deringer. “The reason it’s been difficult with law firms so far is that we have such tight client confidentiality and security rules which make it very difficult to use cloud solutions to solve these problems,” explains Parker.

“Much of the data that lawyers handle is extremely confidential,” notes Zac Kriegman, senior data scientist at Thomson Reuters Labs’ new Singapore lab. “This can make developing models more challenging because it can be hard to construct large datasets. It can also complicate the permissible architecture of computer systems handling legal data.”

With a global team of data scientists and a lean, startup approach, Thomson Reuters Labs aims “to work with the firms and with in-house counsels to help them address the problems they face and tackle client needs, together,” says director Brian Zubert, who is based in Waterloo, Canada.

“By combining their internal data sets with TR’s industry data, there are powerful insights and analysis that can create unfair advantage for first movers.”

PAPER TO DIGITAL

Andrew Fletcher, head of the London lab, says one of the main challenges in bringing legal into the big data era lies in the traditional legal data storage methods catching up to the digital present.

“Lots of startups are focused on getting unstructured data from paper documents into a structured form,” Fletcher says.  “That’s really the first step to building systems that are able to then make the connection between change and the implication of that change.”

That change is already arriving, says Mini vandePol, global head of Baker & McKenzie’s compliance and investigations practice. “We are seeing a radical change in how document review during investigations, litigation and transactional due diligence is carried out, with technology-assisted review quickly becoming a norm for our unstructured data reviews,” shares vandePol. “This includes techniques such as predictive coding and also greater efficiency in deduplication and document threading in email conversations to greatly reduce the number of reviewers and task time.”

Baker & McKenzie is also able to leverage analytics solutions like concept mapping to better understand themes and irregularities, particularly in investigations involving anti-bribery and corruption issues, she adds. For structured data, the firm partners with data analytics experts to identify potential issues and risks, which allows them to better advise during risk assessments.

JUST THE BEGINNING

Big data and machine learning are introducing new degrees of speed to the practice of law, observes Kriegman, and the biggest changes are yet to come. “Much of what lawyers spend their time on can be dramatically accelerated with machine learning and big data techniques,” he says. “This is particularly apparent in e-discovery, or even just the sophisticated WestLaw searches that lawyers have taken for granted for years.”

However, big data is now making big changes to other areas. Intelligent processing of huge volumes of case data is allowing lawyers to make more informed decisions about how different courts and judges tend to rule, the size of the awards, etc. Courts are also leveraging data accumulated by their case management system to look for ways to predict caseloads so they can optimise staffing decisions.

NEW FRONTIERS

As innovation pushes big data forward, new applications and areas of relevance will open up. “We are now seeing the first hints of software capable of doing some more intelligent law-related activities,” Kriegman says. “In the case law search space for instance, I expect that we will soon see systems capable of searching for similar cases, and even identifying candidate legal theories, based on descriptions of the fact patterns in a case.”

Freshfields’ Parker noted that given how late the legal profession is to the big data and machine thinking party, initial moves are likely to be more stopgap in nature. But once things move beyond that stage, the ramifications become very interesting.

“The first thing we have to do is have a data strategy that respects our ethical walls and confidentiality. We have to organise that data, and once that’s in place, the long-term solution would be to apply machine learning or even deep learning technology to that data to see what insights we can gain,” she says.

“If you think about it, lawyers have been recording their time since time immemorial, in blocks of six minutes, with a narrative,” Parker says. “If you think about the wealth that’s there, if you can unlock that and start to mine it effectively, then you’ll know how best to resource, how best to manage. Then you can serve the client better because you’ll have much better price predictability.”

Databases don’t talk to each other, therefore firms have to create a framework to find data points that you can search across disparate knowledge bases.

“You have your knowledge database, you have your document management system, you have your partners’ heads spread around the globe — we are very focused at the moment on how to effectively mine those data points,” says Parker. “Any law firm that’s going to be successful in the coming 10 years is going to have to have a well-thought-out strategy for mining that know-how.”

Freshfields is already making moves in this space, she says, citing its collaboration with the computer science faculty of the University of Manchester to explore semantic web technologies.

COST-EFFECTIVE SOLUTIONS

Price predictability and price reduction are expected to be major themes as legal and big data collide, says Baker & McKenzie’s vandePol.

“The traditional model of conducting document review, involving significant numbers of lawyers reviewing hundreds of thousands, or even millions of documents, is now considered ‘old school’ legal practice,” she says. “Clients increasingly appreciate that it is inefficient, costly and doesn’t allow law firms to put true subject-matter and language experts in front of the facts until late in the review process.”

As legal costs decrease, she says, clients will be able to consider utilising firms for the things that really matter: legal expertise, industry and business knowledge, practical and tailored risk management, risk mitigation and strategic input, which all provide effective solutions for business to move forward and prosper.

“From a compliance investigation perspective, we see risk assessment being a prime area for the deployment of data analytics across big data,” vandePol says. “While effective risk assessment is already a regulator expectation in multiple jurisdictions, using analytics to identify and proactively address them in timely manner could be a differentiating factor to win the confidence of regulators and stakeholders alike.”

WINNERS AND LOSERS

So how is big data likely to reshape how firms and in-house counsel operate in the coming years? As with the advent of any disruptive technology, there will be winners and losers.

“Entry-level legal positions are vulnerable,” says Thomson Reuters Labs director Zubert. “With big data, machine learning, and [artificial intelligence] AI, one junior associate will be able to do the work of four,” he explains. Moreover, he observes that firms “are being run like a business” instead of a partnership and “in-house counsel are making investments in tech”.

These factors could help “in-house counsel to wean themselves off from more and more of legal services offered by firms “if [they] aren’t able to adjust with better cost control and predictability in project timelines.” 

How fast these changes come, of course, depends on how fast businesses with in-house counsel and law firms implement these new approaches to a very traditional field. But one thing is certain: those who adapt the fastest will be the least likely to be caught off-guard.