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Using AI for Improved Contract Analytics

Changing global mandates, particularly SR 14-1 and IFRS 16, mean banks and financial institutions must understand new regulations and implement appropriate changes to avoid penalties, fines or worse. They must also figure out how to comply with new rules and deal with audits without adding too much cost and disruption to the organization. Application of AI-driven contract analytics provides a means of achieving this.

After a career as a licensed attorney, practicing law at a top national firm for more than 10 years before moving in-house at Bank of America and, most recently, Seal Software, I have seen up close the collateral requirements of regulations in banking and finance. As a result, I see oversight for governance and management of contracts as central to compliance in banking and financial institutions.

It’s no surprise then that there has been a lot of buzz about the impact of machine learning and artificial intelligence (AI) on the future of the contracting process. Firms that are able to find and capture all of the obligations, risk, liabilities and opportunities buried in thousands of contracts – in hours rather than days – have a clear competitive advantage.

A great deal of emphasis has been placed on what technological disruption might mean for specific regulatory mandates and the reasons behind demand for this type of automation. The need for cost savings and business intelligence around recovery and resolution preparedness under SR 14-1 and the International Financial Reporting Standard known as IFRS 16 are requirements we often hear about.

Getting a Handle on SR 14-1 and IFRS 16 Compliance

One of the more consistent reasons organizations are interested in getting a handle on their contract corpus is to better manage SR 14-1 and IFRS 16 compliance initiatives. They present a clear, present and real issue for many banks, and the penalties for noncompliance are significant, with fines, shutdowns and takeovers remaining bona fide threats.

The challenge stems from the changing regulatory landscape. The continued roll out of Dodd-Frank, as well as the addition of new regulations, is keeping large banking institutions on their toes. Reporting requirements are not limited to IFRS 16 and SR 14-1, and certainly the benefits and applications of AI can be similar across the global regulatory environment. Whether dealing with any number of other mandates – Dodd-Frank 165 “Stress Test” compliance (ISDAs and CSAs), “living wills” reporting for financial services, European Banking Authority “Write Down” Rules (BRRD), GDPR and U.K. Modern Slavery and Anti-Money Laundering laws – organizations are largely operating under the principle that failing to comply is not an option.

All of these regulatory and reporting requirements have something in common. Access to automation is virtually a requisite to achieve compliance. This of course, is especially true with SR 14-1 and IFRS 16. The alternative (time-consuming, manual review of contractual documents) is not only costly and prone to human error and bias, but also disruptive by its very nature.

Automating SR 14-1 Contract Review

SR 14-1 requires the large SIFI banks (systemically important financial institutions) to report to the federal government (FRB, FDIC and FSOC) on their “recovery and resolution preparedness” plans. The report describes operational adjustments in case of an economic downturn as a means of avoiding a repeat of extraordinary remedies undertaken in 2008 to contain the financial crisis.

The first phase of SR 14-1 reporting was required in 2017, and direction from the Fed requests full disclosures into many aspects of a bank’s operations, including collateral management, payment, clearing and settlement (PCS) activities, liquidity and funding, management information systems and shared and outsourced services. The amount of information requested is significant.

Why does a bank working on SR 14-1 compliance need AI-powered contract analytics, discovery and data extraction? The answer is that comprehensive review of material terms and provisions is essential in ISDA and CSA contracts for triggers that may be breached as a result of market conditions. It’s also crucial to document all customers and counterparties for PCS activities, including values and volumes of various transaction types and capacities for lines of credit.

Guarantees, cross holdings, financial commitments and other transactions between material entities must be identified and remediated, as with key third-party contracts, including the provider, location, services provided, entities that are a party or beneficiary of the contracts and key terms such as contractual rights and termination or change of control clauses. Moreover, legal agreement information, including parties, key terms, interdependencies and service-level agreements between affiliates and other parties all contain clauses that need examined.

IFRS 16 and AI-Driven Lease Analysis

IFRS 16, enacted by the International Accounting Standards Board and supported by GAAP, is designed to foster consistency and transparency in financial reporting of lease agreements. It transitions most operating leases to finance leases such that they will be on-balance sheet transactions by the turn of next year. The impact to organizations that lease assets is significant, with estimates of the global value coming back onto balance sheets approaching $2.86 trillion.

Why can’t organizations just make the change in their accounting systems and be compliant? They need to find all their leases, across departments, business units, lines of business within newly acquired companies and get them centralized and categorized. They then need to determine if they contain services, maintenance components or renewable supplies and extract this data, potentially repapering those elements. This requires that they should model and assess the impact of the new on-balance sheet transactions to financial statements before they make the changes.

The result may be strategies for nonrenewal of leases, restructuring leases or purchasing assets to manage the impact. With these steps, including the ability to make significant commercial decisions prior to the compliance date, the process becomes extremely difficult and costly without the use of automated tools.

Future-Proofing an Organization Starts with AI

Many regulations impact the way organizations make commitments or conduct transactions with partners or customers. SR 14-1 and IFRS 16 are certainly no exception. This means that regulatory changes, no matter how often or how many, require in every instance that firms find relevant contracts, review the affected language and make business decisions to revise, innovate, renegotiate terms or terminate to avoid noncompliance. This is necessary across all affected paper, a figure that typically reaches into the tens of thousands or more.

Whether it is a part of any one of the new or changing mandates that continue to come our way, contract discovery and analysis is likely a key part of an organization’s compliance initiative.  When compared to the process of manual reviews, AI dramatically lowers the cost and shortens the time for getting into compliance and staying there.


Stuart Brock

Stuart Brock is a Director at Seal Software, where he helps lead Seal’s financial services programs. He is a licensed attorney who practiced law at a top national firm for some 10 years before moving in-house at Bank of America. Stuart’s roles at BofA included oversight for governance and management of third-party contracts, including maintenance and technology, to support BofA’s arsenal of contract templates across more than 60 countries.

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