Digitising Disputes

With dispute resolution being one of the more high-risk, unpredictable and (unfortunately) often costly areas of law, new technologies are being developed to manage and reduce risk and cost while also increasing the quality of the service being provided.

In this article, we explain some of the solutions being adopted by law firms for clients finding themselves in a dispute scenario.

Managing and forecasting legal spend

Funding the potential costs of a dispute represents a significant challenge for most, if not all, businesses. Rarely does a dispute involve 'straightforward' factual or legal issues and, where the parties are (by definition) working against rather than with each other, costs can be very difficult to predict at the outset.

Managing legal spend does not mean simply looking at reducing the overall cost of a dispute, but also providing clear and accurate estimates to allow a business to manage litigation by allowing appropriate provisions to be made for the likely costs involved. Early and accurate forecasting also helps a clearer strategic plan to be developed, taking account of all factors which need to be considered.

Taylor Wessing uses a variety of digital costs management and forecasting solutions to provide clients with far more accurate costs estimates at an earlier stage. Put simply, by analysing historic costs data across a range of matters, we are able estimate the potential costs involved in future disputes far more accurately. This allows us to provide tailored costs estimates depending on the nature of the dispute and the legal and procedural issues involved. With this information we are also able to propose alternate funding arrangements with a greater degree of certainty as to the potential cost and associated risks.

Technology Assisted Review (TAR) and analytics

TAR is the use of software to automatically review and classify electronic documents based on prior input from expert reviewers. TAR can be used in a range of dispute contexts from its classic deployment in giving disclosure to early case assessment and reviewing disclosure received from third parties to identify missing information. TAR software can be trained to identify issues as well as concepts and themes and, as such, has wider uses than just identifying relevant documents that must be disclosed from non-disclosable documents that are either irrelevant or protected by legal privilege.

The TAR software 'learns' by analysing the decisions made by a human reviewer when classifying a sample of the documents available. The programme then automatically creates a decision making algorithm and applies the developed logic over a much larger data set. This delivers accurate results in a timeframe, and to a level of consistency that often cannot be delivered manually, even when using a large team of trained lawyers and paralegals.

Due to the power and sophistication of the software, TAR can deliver significant costs savings to clients and reduce the risk of problems arising from a classic manual review disclosure process, such as inconsistent decisions by individual reviewers. TAR has been expressly approved by the English courts in the landmark decision of Pyrrho Investments v MWB Property (with Taylor Wessing leading the submissions on this issue) and subsequently, despite opposition from one of the parties, in Brown v BCA Trading and others.

TAR is just one of a number of powerful tools available today from the various providers of electronic review software that can be deployed to reduce the number of electronic documents that require manual review quickly, and the sophistication of these tools is increasing all the time.

Depending on the type of case at hand, and the number of electronic documents involved, creative use of the available tools can often lead to a tenfold reduction in the number of documents which require active review. These tools include: email threading (to allow a reviewer to only review the emails which include the entire conversation); clustering (by document type, custodian, or category), concept searching and near-duplication.

Artificial Intelligence (AI)

The use of AI is increasing across all areas of the legal services industry. For example, AI is now routinely being implemented in corporate transactions of all sizes to: identify risks and conduct transaction due diligence; in trademark clearance to research and identify potential anomalies; in commercial contract negotiation; and in ongoing contract management.

AI is also increasing in the dispute resolution sector. Some AI solutions have been developed to offer basic consultation and advice services by triaging responses to questions provided by clients. Others are already in existence to help individuals to make small claims automatically for certain types of compensation. In relation to more complex litigation, the potential is still to be fully exploited but existing AI solutions are being used in creative ways to analyse bodies of documents to identify 'missing' information or key information streams which might otherwise be missed due to the volume of material being handled.

The future of AI in the disputes arena is an exciting one. As developers and law firms understand the power of these solutions and the way that they can be applied, we will see new tools being developed which streamline legal research and might even be able to give a view on the potential outcome of issues or simple disputes.

Good news for clients

The increased availability and uptake of new technologies is allowing law firms to help reduce the cost and the risk of engaging in litigation for their clients. By harnessing and deploying what is already available, sometimes in novel and creative ways, law firms are able to put their clients in the most advantageous position while also keeping to a budget.

If you have any questions on this article please contact us.

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