How can we use data to manage the impact of a pandemic on corporate credit risk?
The growing impact of a pandemic is having damaging consequences on our global economy. It is crucial for businesses and financial institutions to harness the value of data to have strong visibility as the situation unfolds and reduce the impact of risk of an economic crises.
Cases of covid-19, more commonly known as coronavirus, have crept up into the hundreds of thousands, with new cases reported every day from different cities around the globe. But, what are the implications on our economy?
The stock market is currently facing historic losses, with analysts describing the market reaction as “utter carnage”. The declines continue to set panic into the market, with global shares plunging to one of its lowest days on March 9th 2020 since the financial crisis, being dubbed as ‘Black Monday’. With so many unknowns surrounding the trajectory of this epidemic, market professionals are increasingly beginning to question what the full impact will be.
As the virus continues to spread globally, we can see similarities in the corporate environment and contagion risk as credit shocks sweep across economies and regions. While governments are attempting to search for ‘super spreaders’, banks with corporate lending exposures are trying to understand the material impact on borrowers. Knowing this, banks will be able to effectively manage relationships closely and tailor their finances directly to support affected entities, alleviating risks for citizens, employees and businesses.
Is data the answer to mitigating the risks of a financial crisis?
Data-intensive financial institutions are sitting on mountains of data but are struggling to realize the true value of all this information. A fundamental rethink is required to go beyond the silos that financial institutions operate in today. Ongoing streams of profit warnings, company announcements, non-traditional metrics and news flows of unstructured data are making credit analysts jobs increasingly difficult and time-consuming. Disparate data is making these decisions even harder.
However, by effectively utilizing internal and external data, plus account-transaction data – one of the financial institutions’ most valuable data sources – you can create a single view of customers and supply chains and understand the relationships between people, organizations and locations. This context empowers credit analysts to make more valuable and effective decisions.
It is crucial for credit analysts to view all businesses as part of a connected network. Collecting intelligence, from all relevant data sources and consolidating this, to generate a unified view of the entire network will help us assess risks and pre-define response processes. More specifically, a comprehensive view of all available data and risk scores will enable us to visualize network risks in the borrower’s system.
None of us can predict the future as the nature of the situation continues to unfold, but for businesses, having strong visibility on what is happening and being able to anticipate the potential impact is crucial to mitigate a negative outcome.
Since the start of 2020, we have seen:
- News surrounding fears of a global pandemic and market events have accelerated, highlighting the threat of damage caused to global trade, the world economy and weakened supply chains.
- With China being a key growth market and having a number of supply chains originating there, the economic damage linked with several large companies did not come as a surprise.
- Airlines and travel companies have seen their stocks plummet as governments impose travel restrictions and quarantines.
- It’s clear that shortages and reduced production are taking their toll on the automotive industry, particularly those home to China. Other manufacturers closer to Europe are at risk if employees of largely affected areas of the outbreak are unable to return to work.
How can we harness the power of technology and data to reduce credit risk?
In an attempt to form a rapid response to the changing nature of the outbreak, Chief Risk Officers will need to provide an assessment of impacted businesses. More specifically, credit analysts, credit oversight and appetite teams will likely need to answer questions such as:
- How many of our borrowers have Chinese revenues over 5%?
- What borrowers have recently been identified to have profit warnings? Once known, aggregate the exposure to understand; lending limit, utilisation, maturity and risk rating.
- What is the potential supply chain effects across the commercial portfolio? How many SMEs and Mid-Market customers are at risk from potential insolvencies as a direct result of supply chain failures in global manufactures?
There is no straightforward solution to any of these questions, particularly when financial institutions do not have a single view of customers or cannot integrate transactions to understand the ecosystem they sit within. But, using the right tools, it’s possible to make sense of huge volumes of data and visualize the risks on your network.
By using transaction data to adopt a real-time view of clients’ activity, this reduces the need for intensive manual processes from both relationship managers and credit analysts. Taking large volumes of data and building networks to harness insights can be further enriched by third-party data. If a credit-analyst can see a customers’ complete ecosystem through transactions and non-financial data, they can make more informed credit decisions. Enabled by this single entity view across multiple internal and external data sources, you will be able to build networks and connect the dots within the data to gain a greater understanding of your customers.
This technology could help us answer the following questions:
- By creating a single customer view and scoring documents for risk, we can identify how many borrowers have Chinese revenues over 5% and could present a risk.
- Which SME customers are likely to require immediate financial support (increased lending) given exposures to impacted sectors, reliance on customers or are weakly positioned within a deteriorating ecosystem.
- Viewing concentration risks connected to a major manufacturing customer across the commercial portfolio, for both corporate exposure and manufacturer employees, we can estimate supply chain impacts such as Global manufacturer insolvencies.
The importance of maximizing the value of your data
Financial institutions and banks of the future must harness the true value of data. The growing impact of the coronavirus outbreak is causing damaging consequences for society, business and the world economy. However, by embracing data-driven decision making, banks will be able to assess and reduce the impact of contagion risk and help avoid economic crises.
In order to harness the value of your data, you need the right technology in place to enable contextual decision-making possible. Empowered by context, the process of bringing together customer data into a single view, understanding their connections and, utilizing advanced network analytics will help you improve the effectiveness and efficiency of uncovering hidden risks in your data.