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Disruption of the legal vertical and how to deploy technology

The C-19 pandemic has had an unprecedented impact on all industries and sectors, forcing organisations to quickly adjust from corporate offices to long-term remote working set-ups for all employees.  

Looking specifically at the impacts on the legal tech sector, we speak to Partha Mudgil, former COO at Nakhoda, who offers expert insights on how the crisis has transformed the sector and what we can expect in a COVID future.  

How will the current crisis affect the emerging legal tech sector and clients’ appetite for change?

  • Legal tech sector has grown exponentially over the past few years and covers a huge variety of business models and client sectors, so it is difficult to make generalisations, especially given the unprecedented nature of this crisis. However, crises usually prompt organisations to change their habits and, broadly speaking, there are no indications that automation that drives efficiencies and optimises resource allocation will slow down. If anything, it might accelerate as organisations cut costs while trying to bounce back over the next few months. Therefore, for those who can keep their head above water and constructively work towards a better product-market fit, this is a unique opportunity to expand their footprint.
  • This crisis will certainly lead investors to ask harder questions around true utility of some products and resilience of business models. The tolerance for “fluff” around innovation and tech as marketing gimmicks will probably decline, and we may see the emergence of stronger businesses with genuinely useful products at the right price point. In the B2B SaaS space, legal tech businesses that focus on simplifying contractual processes and creating data/content for business insights will emerge better positioned to expand their user base and consolidate the market in the medium-term.
  • With respect to law firms, the friction between client retention and hourly rates, particularly for standardised work, will likely worsen in a cost-cutting environment. So, again, genuinely deploying automation (instead of just marketing about it) and smarter use of cheaper resources will be critical to keep those relationships and maintaining margins – expect in-house teams to become increasingly tech-enabled to do more with less.

What are the most critical legal process and data challenges faced by organisations today?

Organisations continue to face two major challenges: (1) inefficient bespoke processes exacerbated by information silos; and (2) lack of structured legal data that interferes with better decision-making on critical issues, particularly during market dislocations, regulatory change or unexpected crises like the present one (eg. the scramble to understand Force Majeure clauses).

Inefficient processes; information silos

  •  Any process to create, negotiate and execute legal documentation today sits across multiple platforms, usually a combination of Word for drafting, Outlook for transmission and communication, and good old signing and scanning for execution. Even products like DocuSign are not as ubiquitous as you would expect, creating significant transactional bottlenecks in times of WFH.
  •  This results in not only a lack of valuable management information (who, when, what, why), but is also significant roadblocks in any documentation exercise at scale. Any process of creating and negotiating legal documents is just painful and costly, with huge amounts of wasted effort.
  • These problems are not just a result of some innate inability of lawyers to work with technology, but institutional inertia, lack of investment in what is often a middle office risk function and lack of incentives for law firms to automate in a time-based charging model.

Lack of structured legal data

  • Beyond management information, most commercially-relevant legal information actually in the document, often created at considerable cost, is lost once the document is created.
  • While quantitative data is utilised extensively to make informed decisions (with increasing use of AI/ML in this space), linguistic contractual data is grossly under-represented, depriving decision-makers of key insights and correlations.
  • The “short-cut” that large organisations, particularly banks, have sought to deploy is extraction products combining pattern recognition, NLP and lots of training. However, due to this technology still being new and immature, costs are high, results fall short of expectations and products are not scalable across use cases.

Is that not a result of legal documentation being complex, requiring human analysis and bespoke solutions?

Partly yes, legal concepts, documentation and processes can be complex and should often by informed by expert views. However, in most organisations and for most transactions, BAU legal documentation is largely standardised and can be streamlined to drive faster sales cycles, compliance and strategic non-legal decision-making. Once streamlined and automated, valuable human expertise can be focussed on setting risk parameters and gauging where exceptions should apply, rather than data creation and management. Technology is an enabler for what will continue to be a critical function as organisations become more complex and regulatory environments continue to evolve at increasing pace.

In the absence of a one-stop-shop for automated legal services, how do organisations think about addressing these challenges?

The market is too young and yet to see a consolidation where some providers will be able to meet an organisation’s legal needs (eg. Salesforce) – it may never even happen.

Further, the market participants with most domain expertise (law firms) are simply not designed to meet this challenge. Therefore, for now, organisations will need to think about their most pressing needs and implement a system that works for them, and recognise that it will evolve like any other technology. This is likely to be a combination of (i) domain experts (private practitioners/law firms), as required; (ii) creation/negotiation product + contract review product that streamline contractual processes and produces valuable structured legal data. This combination could be complemented by point solutions for specific tasks, such as an extraction software for historic documentation as and when required eg. for regulatory compliance.

How do organisations leverage the power of AI/ML for linguistic data?

Fundamentally, organisations must consider better ways of structuring data at the outset as it is being created. This is critical to enable organisations to leverage new technologies like AI/ML for linguistic data – without high-quality data, it is impossible to level the playing field with tech giants who are militant about data quality and pipelines. Technology can now be deployed to structure legal data using automated legal logic. This approach can indeed help plug the what is a massive data leak when it comes to valuable contractual documents. It does require some upfront thought and planning on how to structure and digitise documents, but there are now some products that address this problem, though not as well as they could.

The trick to leveraging technology in this space is to have a broad perspective and long-term view, focus on data (not just efficiency) and have a smart investment strategy that caters for building your own data flows between products in what is still a fragmented product space. Some of the larger banks and tech companies have already begun to solve this problem behind the scenes, thus increasing the gap vs. rest of the market. Having said that, parts of the market, eg. challenger banks and fintechs, are in an enviable position of building more dynamic systems today that could ensure easier, faster compliance, risk management and generate insights that more established institutions struggle with. Needless to say, any organisation above a certain size needs to be thinking about how to create better data pipelines, including for critical contractual data, and more automated legal processes for increased sales velocity.

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