AI Takes on Role of Contract Management and Negotiator

man signing a contract

Odds are if you’re reading this you’ve had to deal with a contract at some point in your career. The odds are also in favor of that contract requiring some level of negotiation. With the continuing deployment of artificial intelligence (AI) from the data science department to the rest of the company, new technology is available help manage contract origination and revision giving birth to a new category called contract lifecycle management (CLM).

“I believe we’re seeing the evolution of work, particularly in financial services where there are so many operational roles that are data heavy as we move toward more straight-through processing,” CRO Abrar Huq said. “It’s indicative of a new process efficiency perspective and a new data efficiency perspective. We’re focused on helping companies avoid redundancy of tasks. In some cases, changing how people do things that they had done in the past and in some cases, removing them entirely.”

All of which may be music to the ears of anyone who has had to navigate the archaic language and endless back-and-forth of some contracts and contract negotiations, whether it’s as complex as a merger or acquisition or as relatively simple as a commercial loan application.

While some in the industry have tabbed this new process as CLM, Arteria bills itself as “building modern documentation infrastructure, focused for the present on the financial services industry. It claims Citi as well as other global Tier One banks as clients in its quest to bring the power of AI to improve operational efficiency and enhance client experience in areas such as trading, lending and asset management, among others. After launching in 2020, Arteria has pulled down $50 million in finding and has tripled annual recurring revenue from 2022 to 2023.

“Documentation is at the center of client experience, and there is significant value in getting it right,” said Fernando Dammert, COO of Financial Institutions Sales and Solutions at Citi. “Arteria enables us to collaborate more efficiently across functions and drive value for our clients.”

It does that by using AI to learn, analyze and manage revisions from the beginning of the contract process, which can be as simple as a bullet-point term sheet through the complex process of negotiations and then a final document. First, the Arteria model enables clients to digitize its contracts and create access points to downstream systems and personnel. Then it applies predictive analytics and machine learning to remove friction in the negotiation process. Huq says the goal with each client is to take the knowledge encased in negotiation playbooks and improve on it through data and content analytics. Arteria takes existing unstructured documents and then parses it for the key recurring elements and creates structured data. That knowledge is then incorporated into a more automated workflow.

The new process is part manual and part automated. Huq doesn’t see a day when the process can be totally automated, but it can be dramatically improved. The vision for the company is that AI would be used on both sides of a negotiation to interpret markup languages and use AI to create consensus. One of the activities that Huq says has been a welcome surprise to many users comes with the data analytics that populate every financial service contract. Unstructured data is mostly manipulated manually. Structured data is easier to analyze and revise.

Banking and Beyond

While financial services has proven to be the sweet spot for Arteria, Huq said the solution is category agnostic.

“The reason why we found a home in financial services and in banking in particular, was because our value proposition tends to be richer for them,” he said. “These organizations that are more reliant on data have complex data architectures, and the flow of data is more critical. From a maturity perspective, financial services is most receptive to this type of product. So that’s really what drives us toward banking and finance.”

Outside of Citi, one of Arteria’s showcase clients is Goldman Sachs. According to a use case laid out by Babson College Professor of Information Technology and Management Tom Davenport, Goldman has been on a mission for the past 18 months to automate contractual processes, in which a single contract generation, negotiation and revision can take months. It is using Arteria to redesign its contract process by improving the amount of time it takes to research document templates and focus their legal professionals on efficiently extracting the right data from the right document. As Davenport notes, changing the way contracts are created and negotiated is as much about change management as it is about new technology.

“Change management is certainly one of the things that we focus on in our implementations as we work with partners along their journey,” Huq said. “We help our clients think through their processes and make sure that they’re just not taking a bad or broken process and simply embed it into new technology. We help them think critically about their process and evolve the changes they need to make. We ask the hard questions. What are the processes that are adjacent to this particular documentation problem? How does it impact them? What do you need to focus on for the future?  It’s a critical factor in how we how we operate and how we implement our solution.”

Although Huq’s remit is focused on generating revenue at Arteria, he’s most excited about potential growth and improvements in its AI-driven technology.

“We love having clients that challenging us to think about how our product can be applied in different ways,” he said. “And there’s so many different areas within financial services and banking specifically that that have an opportunity for transformation that just haven’t been conceptualized yet for a variety of different reasons. That’s one of the things that’s most exciting to us. Over the last couple of years, we’ve seen ourselves evolve from, from contracts to documents writ large, which is really opening the minds of our clients to think about and conceptualize how this technology can be applied in different ways in different areas.”