Date: 16 July 2020
Author: Vasilis Tsolis
“The hats never change, but hanging them in different patterns (…) or in different hat racks can affect what we know about them” wrote the architect Saul Wurman in the 1989 issue of Design Quarterly called… Hats.
In fact, he was not talking about hats. He was talking about categories, and their strong power in fashioning the way we look at the objects they contain.
Once a concept falls within a certain category is difficult to consider it part of any other category.
LegalTech is understood as the use of technology to provide legal services – to lawyers, legal institutions or consumers of legal information. A LegalTech product is a product for the legal market. While FinTech is a different category per se, that contains all technology created for financial institutions or consumers of financial services.
We rarely think of these categories as overlapping.
We rarely consider LegalTech and FinTech as being similar.
Law is about words, finance about numbers
Perhaps the divide is embedded in our minds – I don’t know: we tend to think that the legal world has to do mainly with words, while the financial world deals primarily with numbers. Words versus numbers, like mind versus body in a sort of Cartesian congenital dualism.
Anyway, as for every dichotomy, it’s useful until it’s not.
Truth is, legal information can be treated as if words were numbers – as legal data.
For instance, using XML for marking up legal text basically consists of turning words into machine-readable data, irrespective of their meaning.
And the National Archives’ Big Data for Law is a pioneering attempt at treating legal text like streams of numbers.
I think this might be true of methods and technologies as well – we tend to think of legal technology as created solely for the legal sector. But is it?
Can LegalTech solutions be used in the financial sector?
They can and indeed they have been.
The whole concept of robotic business automation (RPA), which is a topic dear to Fintech and to the financial sector, relies partly on technologies that have been used first in the legal sector before moving to finance.
Robotic process automation is based on the premise that all tasks that are repetitive in nature, apt to be template-driven and subject to a high chance of human error, can be successfully automated.
According to Gartner, 89% of general accounting operations and 72% of financial controlling and external reporting operations could be highly automatable. For EY, RPA can include areas like Sales Ordering and Invoicing, Financial and External Reporting, Payables Management and Receivables Management.
Leveraging LegalTech in Finance
Document automation technologies, which were born in the legal sector to simplify and streamline the creation of contracts and other legal documents, have started to be used in the financial sector as part of the RBA model.
In 2017, a venture between law firm Allen & Overy and Deloitte was probably one of the first of its kind in applying document automation capabilities to the banking sector, for drafting banking agreements at scale. Similarly, document automation can be used -and has started to be used- for any kind of document which can be standardized, like invoices, reports and orders.
AI-enhanced document review is another technology that was born in the LegalTech sector and developed specifically for the legal market, but can be successfully translated into the financial area.
The impact of regulations on the financial sector is growing and in case of new regulatory frameworks, financial agreements may need to be screened and amended in the light of new guidelines, for instance with regard to changing interest rate provisions, borrowing base provisions and other sector-specific clauses and covenants.
Take the upcoming changes to LIBOR, which is embedded into a large number of financial contracts that have a variable interest rate component. The necessity of reviewing and amending all contracts carrying instances of LIBOR – aka repapering – has kept financial institutions busy since 2017, when FCA announced it would have been discontinued. Using machine learning document automation technology has dramatically helped reduce the time and costs involved in this activity.
The same is true for impending – and more global- changes, like Brexit, likely to impact the market infrastructure and the connected financial agreements even more pervasively.
Perhaps forgetting silos and cross-leveraging AI technology into both the legal and financial sectors would be mutually beneficial for both sectors and could produce some interesting results.
Vasilis Tsolis is the CEO of Cognitiv+, a machine learning platform that empowers companies with deeper insights on their legal data.
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