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AI-driven data insights set to improve transparency in credit markets
Trevor Headley | head of Hedge Fund Product Management, FIS and Richard Peterson | product head, Credit, Data and Analytics, Virtus from FIS
May 07, 2021
The fallout from the Greensill collapse in recent weeks has highlighted just how vital it is to have a transparent view on credit risk, whether in supply chain finance or the equity tranche of a CLO. In any investment fund, the buck stops with the portfolio manager. They are the ones making critical decisions and balancing the underlying risk.
The Greensill collapse was due to bad loans being made to a handful of companies – principally Sanjeev Gupta’s GFC Alliance. Credit Suisse, whose total funds’ exposure to Greensill was USD10 billion, estimates that USD2.3 billion in its funds are at risk because of ongoing valuation uncertainty.
This is a stark reminder of why it is so important to get transparency on credit risk, whatever the strategy may be. In credit markets, which have for so long been an opaque space, getting access to high quality data has long been a highly complex, manually intensive exercise.
FIS® is addressing this data management challenge by rolling out a new AI-driven solution: FIS Credit Intelligence powered by C3 AI.
“We worked to develop the new product in partnership with C3, an AI company that injects insights into how to think about data, ingest it and best utilize it from a contextual perspective,” explains Richard Peterson, who heads up credit data and analytics initiatives at Virtus from FIS.
“It’s a way of presenting data to help the human brain understand what it is looking at and how it links to the analysis. It’s a thinking model. It goes beyond the capabilities of standard, manual data scraping tools.”
Most credit analysis tools look for ways to understand, contextualize and benchmark data, but they tend to lack cohesion. This is what the AI-powered FIS solution will seek to address.
“When you have a lot of unstructured data related to private companies, along with different ways of contextualizing outside sources of data and how they may or may not relate to each other, that’s where this new technology solution could be really transformative,” adds Peterson.
The solution is being rolled out to buy-side firms at a propitious time, as investors continue to demand more data to better understand a manager’s performance and strategy. Having transparency on data and the decision-making process is something that every investment manager needs to focus on.
“If you’re a distressed credit manager or a CLO manager, you’re making key decisions on the data you receive. Being able to tell your investment story effectively to LPs is crucial. On the LP side, the data they have access to will inform the questions they ask managers and the way they think about evaluating performance,” says Peterson.
Virtus from FIS already ingests a lot of deal-specific credit data. What this new credit intelligence solution does is combine borrower-specific financial data with clients’ data to create an entirely new data set that is contextualized from top to bottom: from aggregated statistics on manager benchmarking all the way down to deal-specific borrower information extracted from financial data files.
“As we extend things further and build new ways of looking at data, I expect us to have a number of different dashboards and data sets that will integrate with independent third-party data sets that a client would provide,” adds Peterson.
Users of FIS Credit Intelligence will benefit from significant automation and efficiency gains, as well as improved data analytical capabilities supported by underlying AI technology. Peterson expects near real-time access to data to make a clear difference:
“Typically, in credit markets, this has been a manually intensive process involving a number of different products/systems to get the data transformed prior to analysis. That ability to automate the process and have the data transformed in near real-time will allow for quicker investment decision-making and allow analysis to begin right away.
“That has the potential to give asset managers a leg up on the competition.”
To help end users contextualize and understand the data being presented, the solution will include various ways of benchmarking and indexing to uncover insights: these could be as a result of someone’s own analysis or as a result of the AI, which will look at different trends and ways to slice and dice the data to come up with a narrative.
Either way, accessing new data and finding new ways to interpret that data should help portfolio managers make even smarter investment decisions, both at the pre-investment stage and during ongoing portfolio management.
Peterson explains that the AI will become smarter and more customized toward a client’s specific way of working overtime.
If, for example, the end user has developed a custom dashboard showing multiple credit-related metrics, these will automatically get updated on a daily basis as more data comes in, allowing the portfolio manager to consider new insights being suggested by the AI; i.e. suggesting a relationship between two data sets that a human may otherwise not have spotted.
This will allow managers to work with machines to better interpret data and push forward the next evolution of credit risk management.
“I think it’s inevitable,” states Peterson. “If you have a platform focused on credit intelligence, it will lead to greater insights and drive performance.
Managers will be able to present the data in a clear narrative. Being able to understand and contextualize the data quickly is going to become a key differentiator among managers going forward.”
Trevor Headley, head of Hedge Fund Product Management at FIS, explains that one of the first ways FIS will be utilizing their credit intelligence solution will be to integrate it with FIS Buy Side Portfolio Manager to deliver a connected front office.
“This will give portfolio managers a single source of truth, from idea creation and research all the way through trade execution. We want to drive the next level of evolution within the investment management process.”
The Greensill episode serves as a cautionary tale to credit managers and investors. Without the requisite transparency and data to assess counterparty risk, fund managers expose themselves to potentially serious write-downs in their portfolios.
“Going forward, investors are going to want a much more informed and transparent view of what the quality of the underlying constituents are, in any credit-focused strategies,” adds Headley.
This will require managers to be creative and anticipate how investors look at and scrutinize their investment decisions.
Ultimately, having the data to back up those decisions and express their reasoning will give investors greater confidence.
“Managers need to understand why they are making certain decisions, back those decisions up with the right data and analysis and be transparent with everyone. Those are the managers who are going to survive in today’s environment.
“The future of credit investing is transparency backed up with data. We aim to help managers achieve this by making the data more available and more usable in their analysis,” concludes Peterson.