When Is Credit Data Not Credit Data? When It’s Liquidity Data

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Credit Benchmark’s primary focus is the creation of a unique credit dataset. Our clients, both banking and non-banking, use this credit dataset in a myriad of ways to help inform their decision making processes when assessing the creditworthiness of their counterparts and obligors. We are increasingly aware that the data contains another distinct and powerful use case specific to liquidity. Liquidity information is a valuable complement to credit risk information and is proving to be of increasing interest to our clients, especially in times of market volatility and stress.

To understand the power of liquidity data, it is important to understand where the information is sourced. Credit Benchmark collects and aggregates credit risk data from a growing number of leading financial institutions around the globe; institutions who have “skin in the game” – whether lending capital to obligors or selecting counterparts.

These banks conduct detailed in-house credit analysis for a number of reasons. It is essential to management of economic capital in the day-to-day conduct of their businesses; but there is also a regulatory push to reduce dependency on the traditional credit rating agencies. Effectively, banks have created their own internal, highly regulated and independent rating agencies.

Credit risk analysis essentially aims to answer these questions:

  • Should we lend money to or deal with this potential client or counterpart? And if yes:
  • Should we lend to them in size or not?
  • Should we lend to them on open or for term? If for term, for how long?
  • Should we lend at low or high margins?

This is the core business of banks globally – making credit and liquidity decisions that are often inextricably linked. These decisions are based on the outputs of highly regulated models and years of banking experience. They inevitably differ from bank to bank, and Credit Benchmark’s role is to collect these views and help our clients understand how their own outputs compare to the consensus of their peers – hence the “Benchmark.”

While the views we collect are grounded in core credit, they offer an additional insight into counterpart and collateral liquidity that has proven to be of increasing importance across the past decade. In this time period, the global financial system has been in recovery mode as a result of the 2009/10 financial crisis. Mark Carney, Governor of the Bank of England recently told The Financial Times “the global economy is heading towards a “liquidity trap” that would undermine central banks’ efforts to avoid a future recession“. As we collectively brace for another looming crisis, liquidity and access to liquidity is at the forefront on everyone’s mind.

In the face of a major global credit and liquidity transition, governments, central banks and policy makers are taking coordinated action, the likes of which have not been seen since the last financial crisis. They are injecting huge amounts of liquidity into the system and reducing rates to historic lows, recognizing that liquidity and confidence need boosting to ensure that the world does not face an unprecedented solvency challenge. During the COVID-19 crisis, the critical question is whether the liquidity and cash flow that all companies need to survive – especially small and medium sized companies – will find its way to the necessary places quickly enough to ensure their survival.

The Credit Benchmark dataset can help clients understand how this credit transition is happening. It is now evident that sometimes credit data is not just credit data – it can also provide valuable liquidity and solvency insight too.

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Credit Benchmark brings together internal credit risk views from over 40 leading global financial institutions. The contributions are anonymized, aggregated, and published in the form of consensus ratings and aggregate analytics to provide an independent, real-world perspective of credit risk. Risk and investment professionals at banks, insurance companies, asset managers and other financial firms use the data for insights into the unrated, monitoring and alerting within their portfolios, benchmarking, assessing and analyzing trends, and fulfilling regulatory requirements and capital.