As the global financial markets brace themselves for a major change in 2021 — the phasing out of the London Interbank Offered Rate (LIBOR) — leading financial services company are looking for an end-to-end solution for a seamless LIBOR transition.
Financial services must accelerate their efforts to transition from LIBOR to mitigate future risks, avoid uncertainties, and build actionable solutions.
Infosys BPM and EdgeVerve have come together to help financial institutions chart a new course with the discontinuation of LIBOR in 2021. We have developed LIBOR methodologies and tools in consultation with clients, former regulators, banking chief risk officers, and financial services policymakers.
Customizable for clients’ specific needs, our LIBOR transition services have three key pillars:
As the world prepares for LIBOR transition, this PoV helps answer key questions on the road ahead post-LIBOR and how our LIBOR program can help financial service providers transition seamlessly.
To enable financial institutions to manage the LIBOR transition successfully
To understand the impact of the LIBOR transition, we have built an exhaustive library of 350 questions to carry out an in-depth Impact Analysis.
A significant phase of LIBOR transition, the primary objective of Impact Assessment, is to quantify the LIBOR exposure at each product and portfolio level in terms of financial exposures.
Identifying all the contracts that carry LIBOR risk is an enormous challenge and involves:
Nia Contracts Analysis, an enterprise-grade AI offering, utilizes advanced Machine Learning techniques such as Computer Vision & NLP to enable business users to find the contracts, which have referenced LIBOR for base rate calculations, quickly and accurately. Nia Contracts Analysis also brings the speed of processing 12,500 contracts per hour and scale of processing volumes of contracts up to millions.
How Nia Contracts Analysis helped a US-based financial services company reduce the contract cycle time by 60%
Challenge | Solution | Outcome |
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A leading financial services company in the US was looking to process a historic load of over 25000 global procurement contracts along with risk scoring for all contracts, suppliers, and document types. | Nia Contracts Analysis leveraged advanced Machine Learning techniques such as NLP and Computer Vision to quickly and accurately extract terms and clauses from the historic load of procurement contracts. It also helped the client assess the risk profile of their contracts, suppliers and document types by scoring them. | 10X increase in productivity | Accuracy of over 90% | 60% reduction in contract cycle time |
Depending on the nature of contracts, i.e., standardized or customized, technology will play a significant role at this stage in terms of implanting fallback provisions and letting customers know the change, in some cases recollecting the countersigned documents to store in the document repository with an audit trail.
An automation solution for repapering contracts
AssistEdge, a cohesive RPA platform, leverages automation capabilities to generate a new contract with a new clause or generate an addendum to the existing contract. It also helps to send out automated customer communications along with redrafted contracts.
Remediating processes will be critical to eliminate potential operational risks, which may lead to unlimited financial risk/losses. Remediation comprises activities such as defining target operating models at each sub-process that may include infrastructure or systems and operations change, e.g., refreshed Standard Operating Procedures (SOPs), training materials, etc.
Our client, one of the largest bank-holding companies in the world, headquartered in Tokyo, Japan, had a challenge in identifying all the contracts that use LIBOR for base rate calculation and to find out which of those contracts are going to expire before 2021. The contracts whose due date is beyond 2021 needed to be renegotiated
The solution | Outcome |
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Nia Contracts Analysis was proposed to transform the process of analyzing and reviewing contracts by leveraging advanced Machine Learning techniques such as Computer vision, semantics, & language sequence. As some of the contracts spanned multiple paragraphs, the Nia Contracts Analysis team took a sample of those paragraphs, tagged the clauses, and built the AI model based on them. Nia Contracts Analysis trained the AI model on a sample set of 15 documents to automate the detection of all the clauses (intents), including those that had LIBOR and other base rates. Nia Contracts Analysis also detected all the contracts that had end-dates beyond 2021. This was critical as all the contracts must be redrafted to reference alternative base rates. |
Nia Contracts Analysis was able to achieve a 98% hit ratio in terms (intents) detection for all the relevant clauses, exceeding the expectations of our client. Our client’s staff used the Business User Search feature of Nia Contracts Analysis to quickly find the contracts which have referenced LIBOR for base rate calculations quickly and accurately. With the time saved by switching to automated contracts processing, the client was able to improve their negotiation posture while renegotiating the LIBOR contracts that go beyond 2021. |
To learn more about how we can help you unlock business opportunities, minimize disruption, and reduce the cost and risk of addressing the transition, download our LIBOR Transition Services brochure.
Our Whitepaper & Transition Services Brochure