Insight: The Future of Financial Transactions: Automation and Structured Data in Legal Practice

December 17th 2020

General Counsel, Nivaura

The full version of this article first appeared in the June issue of Butterworths Journal of International Banking and Financial Law and is available here. The full version includes further discussion on how data can be effectively captured for use and the legal implications of doing so.

Increasing use of technology is a key theme among legal practices focusing on banking and capital markets transactions, but such transactions continue to be conducted very manually. Although new technology can drive efficiency and help cut costs, the most valuable opportunity for legal service providers lies in the use of structured data gleaned from deploying an automated process. This article will identify how this has been successfully accomplished in the e-commerce space and how that might apply to legal practice on large financial transactions.

Current Transaction Processes

Although there is increasing interest in using automation technologies in finance transactions, most first drafts of finance contracts are prepared manually. A lawyer will take a precedent and manually make changes to reflect the deal they’re working on. Contract negotiation and transaction management is conducted through physical meetings, on conference calls or over e-mail. Indeed, the method in which finance transactions are conducted has not significantly changed in 40 years and has not really changed at all since the adoption of email and the Microsoft Office suite in the 1990s. The process is labour-intensive, time-consuming, unnecessarily expensive and risky.

The approach taken to running very large and significant financial transactions in our professional lives stands in stark contrast to how we run our personal lives, where the use of technology is ubiquitous. Over the last few months, if we weren’t before, we’ve all become very used to shopping online, where not only will the app or website provide access to a digital electronic supply chain that will deliver goods to the door, but will also use the data obtained from that series of actions to predict consumer behaviour and drive further commercial success.

Technology Use in Financial Transactions and Legal Practice

Though the use of technology platforms that automate transaction management, document drafting, review and negotiation is still nascent, it is worth noting that when the legal and finance profession look at such technologies they are not looking at anything novel or different to what most people already use in their daily lives. Instead, it is the application of existing and established technologies to an area that has not seen it before. So what can be learnt from that existing technology and the use of it in other industries? There are really two key areas to focus on. The first is the application of automation to financial transactions and how that can make processes easier, quicker, more cost-effective and less risky. The second, looking slightly further ahead, is how the use of data that can be gleaned from following a digital automated process can be used to drive not only further improvements in process but also better decision-making by participants and commercial success for practitioners that serve the financial markets.

There has been a revolution in the retail space through e-commerce, with Amazon being the most well-known example. Rather than having to physically purchase goods it is now possible to search for them on an app, purchase them through a simple swipe and they will appear at your door the next (or even same) day. This provides the best example of an electronic supply chain. These principles are now being applied to financial transactions and the legal processes that underpin them. There are an increasing number of platforms that will automate the drafting of contracts, assist with transaction management or allow for the quick extraction of data in large scale disclosure or due diligence exercises. The use of such technology will undoubtedly save time, reduce cost and make the provision of financial services and legal advice more efficient.

In the increasingly commoditised and competitive banking and capital markets it provides service providers with part of the answer to the ever increasing downward pressure on costs that has been experienced since the global financial crisis and which may well intensify as companies seek to manage, and recover from, the economic crisis caused by Covid-19. While automation undoubtedly brings great benefits, it is more helpful on the cost side of the P&L than the revenue side. The more exciting commercial opportunity that technology brings to financial services and legal practice is in the use of the structured data that can be gleaned from following an automated, digital workflow.

The effective use of structured data

At a high level, structured data has a framework that makes it:

  1. machine readable; and,
  2. machine interpretable.

If data has these two attributes, then a computer can process this information in novel ways.

An astonishing amount of human labour is expended on transforming unstructured data into structured data. It is far better to structure the data at source, allowing downstream tasks that were previously performed by humans to be automated, and the source of data of any finance transaction are the legal contracts that underpin it.

Furthermore, if sufficient quantities of structured data exist, a computer can be ‘trained’ to recognise patterns and derive insights that would otherwise take humans years of experience to discover. Amazon, Ocado and Google, to name a few, all automate, in different ways, processes that used to be very manual. However, it is the use of the data that is collected when using their application, rather than the use of the application itself, which drives commercial success. It is this ability which unlocks the real value of structured data.

A typical Amazon customer may own a Kindle, a voice-activated Echo speaker and also use the Amazon app to buy various goods. Amazon captures every single interaction with its software, records it as structured data and amalgamates and assesses it with all the other data it receives from other customers.  All of this information is arranged in a format that a machine can understand and identify patterns in. Such patterns tell a story about each individual Amazon customer and entire demographics of Amazon’s customers. The company’s founder and CEO, Jeff Bezos, frames this in terms of being a “customer obsession”, saying his priority is to “figure out what they want [and] what’s important to them”. Having done that, Amazon can then place products and services in front of people that they are likely to buy and give them the service they want. As we know, Amazon does this with tremendous success. Indeed, Amazon has become so confident in its ability to predict a customer’s future purchasing habits, that it believes it can now ship a product in anticipation of a user purchasing it.

Why is any of this applicable to the world of financial transactions and legal practice? For the same reasons that it is relevant to Amazon, because everything a client does on a transaction tells a story about what is important to them. How much time they spend on a particular provision, which provisions they comment on, which things come up repeatedly with particular clients or even in relation to specific individuals at particular clients. These behaviours are capable of showing, scientifically and in an easily analysable way, what clients care about and spend their time on. All of this data currently exists, but it is not being captured in a structured way that can be interpreted by a computer, it merely rests in the experience set of particular practitioners. However, if the data were captured in a structured form, financial or legal service providers could identify patterns in their clients’ behaviour and devise or tailor products or services that are more suited to that client. The system could start to predict, reasonably accurately, what certain clients are likely to do on certain transactions. Transactions and documentation could be customised automatically without the client having to remake the same points it had on a similar deal the week before.

Such systems would also allow lawyers to price more effectively, as they could see precisely which parts of a transaction, right down to negotiations on particular clauses, were profitable and which were not. Together with data about what their clients were focussing and commenting on, lawyers could tailor their offerings in a way that adds more client value while also being more profitable. Most significantly, the ability to identify patterns in client behaviour and make predictions from such patterns will provide service providers with a previously unattainable level of client insight and understanding. Ultimately, it facilitates the provision of the strategic advice that is appreciably more valuable to clients than the commoditised and mechanical execution of a transaction. This intelligence is the exciting revenue growth opportunity that technology extends to financial service firms and lawyers; over and above the cost-cutting enabled by automation.

All of this is possible now, and none of this is new technology. These are the same ideas, concepts and technologies that Amazon use when people buy a packet of screws or that Spotify use in suggesting a playlist to a user, it could be used for the much more significant action of advising clients on benchmark financial transactions.