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ADOPTING AI TO REPAPER LIBOR CONTRACTS MAKES BUSINESS SENSE

01/08/2019

By Peter Wallqvist, Global Practice Director, iManage RAVN

 

At a recent event, both the President of the New York Federal Research and the Chief Executive of the UK’s Financial Conduct Authority (FCA) urged the sector to speed up the move away from contracts linked to LIBOR. The ‘death’ of LIBOR and the move away from this world’s most widely used interest rate benchmark to alternative reference rates by the end of 2021 is an enormous undertaking for financial institutions.

 

Challenge of unstructured data

To this end, foremost, financial institutions need to identify the contracts that need to be transitioned from LIBOR to alternative reference rates – within the existing remit of these documents.  Herein lies the challenge – institutions lack visibility of their contract estate. Typically, nearly 80 per cent of information is unstructured and sealed in documents. As unstructured data has no useful metadata, these documents are not searchable for LIBOR relevant information.

Peter Wallqvist

Consequently, determining the volume of contracts that requires repapering across the portfolio for LIBOR is proving to be problematic. Also, only once the problem is quantified, can financial institutions then identify the relationships that are impacted. For instance, which of those contracts have fall-back provisions, which agreements will require renegotiations and, if so, what the amendment process will be, and such. There are substantial financial risks to institutions if contracts are not accurately amended, not to mention the regulatory implications.

 

Manual exercise = staggering legal cost

The traditional approach towards this repapering project would be to hire a law firm to undertake the entire exercise manually – from identifying the contracts that need repapering to undertaking the individual tasks for successful completion. Given the volume of contracts that exist in financial institutions, it is an unrealistic option. Even conservatively, financial institutions would be looking at legal costs in the region of millions of Pounds. Aside from the staggering legal fees, completing the transition in time is almost impossible due to the vast expanse of the contracts landscape in financial institutions.

 

Human-supported AI adoption

While the task is immense, with the aid of technology such as artificial intelligence (AI), it is achievable – safely, accurately, cost-effectively and crucially, in a timely manner.

Prior to applying AI, digitising contracts is essential. By making the data machine readable, instantly important information becomes searchable and ready for the application of machine learning techniques, to automate the identification and extraction of key data. The information can then be triaged and interpreted, as appropriate.

AI can help deliver a structured methodology to manage the process, end to end. Financial institutions or their service provider can use ready-made, standard extraction models and further train their application to extract the contractual information relevant to them in a format that is machine readable and easily consumable through existing reporting tools.

This scenario represents the ideal human – machine partnership. The technology will automate the tedious and time-consuming manual cognitive processes that are economically unfeasible or even impossible to complete in the current timescale – all the while supported and guided via human intervention and oversight.

To elaborate, financial institutions can use different data points to determine the scope of their repapering exercise. A search for contracts using the ‘termination date’ data point, within minutes, lists all the contracts expiring before 2021, which the institution can disregard, and focus on the remaining contracts that require attention.

For the contracts continuing past 2021, AI technology can be taught by humans to read, extract and interpret other critical business information and apply ‘decision tree’ logic to support the repapering effort. This will result in automation where needed.

 

Many scenarios demand repapering

Repapering isn’t required only for LIBOR contracts. Due to a continuously changing regulatory, economic and legal environment, there are many situations where repapering exercises will likely be required. Brexit is a good example. Deal or no-deal, financial institutions will eventually need to amend reams of agreements to comply with business requirements.

Hence, digitising and teaching a machine learning system to extract many of the data points for LIBOR will also prepare financial institutions to efficiently manage similar projects in the future too.  They will be able to re-use the same machine learning models for new purposes.

A human-supported adoption of AI technology to amend LIBOR contracts to meet the 2021 deadline makes business sense. It represents a realistic approach to AI adoption, to deliver real and tangible benefits of efficiency, accuracy and cost savings. It is a worthy investment for financial institutions.

 

About the Author

Peter Wallqvist is Global Practice Director at iManage RAVN, where he is responsible for positioning new and enhanced practical AI solutions that empower professionals to increase efficiency, improve productivity, and mitigate risk. Peter was co-founder of the AI company RAVN Systems, which iManage acquired in 2017.

 

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Finance Derivative is a global financial and business analysis magazine, published by FM.Publishing. It is a yearly print and online magazine providing broad coverage and analysis of the financial industry, international business and the global economy.

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