The emergence of Covid-19 in Wuhan, China last December began a prolonged assault on the most important areas of our lives – our health and our financial wellbeing. Both are intrinsically linked, as we appreciate all too well these days having to endure
social isolation as we start to make plans for the transition and recovery periods. Health services across the world have been tested to their limits, heroically fighting the impact of this novel coronavirus. At the same time, banks and financial service providers
have been fighting to keep the economy afloat and keep, more specifically, the SME sector, the engine of the economy, running.
The challenge to keeping millions of SMEs afloat is based on the ability of the financial services sector to provide vast amounts of liquidity to these businesses – efficiently and effectively. This is not easy when the time window to deliver this cash
is an absolute maximum of 3-4 months, even less for many SMEs. Naturally, there has been concern that this may not be possible. Many in the sector have questioned whether the software and algorithms used to calculate pricing and valuations of collateral and
ultimately, loans and mortgages, is up to the task.
The answer is in part dependent on the capabilities of the financial sector’s risk management functions. Risk and rating systems underpin the decisioning process used by lenders. All the banks use tools to calculate the credit risk of borrowers. These tools
and systems were not designed to take into consideration “Acts of God” on the scale of this pandemic when originating loans, mortgages or overdrafts.
Covid-19 has weakened the value of the data used in rating systems – making them unreliable. For example, all the data relied upon to test an SME’s credit risk is outdated due the immediate economic shock caused by the pandemic. Rating SMEs with data from
before the crisis - from 18 months ago (balance sheets) to 2-3 months ago (Credit Registries) - is no longer relevant as it fails to provide an accurate assessment of a business’ current situation. We know that in most cases SMEs have generally been prioritising
salaries or paying their key suppliers and delaying all the other payments. The traditional scoring systems would interpret this negatively and provide these businesses with automatic downgrades, increased cost of funding and reduced access to new credit.
Consequently, it would soon become difficult to distinguish the viable businesses from the Zombie-SMEs and this “inaccurate” scoring would negatively impact plans for economic recovery.
However, we are fortunate that there is a solution offered by new technologies such as open banking. Open banking enables real-time, more personalised data on which to base risk and credit scoring. Open banking data can provide risk management teams with
the ability to score a company on its capacity to generate revenue. A business’ liquidity and transaction data can be measured by the transactions in its bank account. It is this data that is the most relevant and important now.
Financial transaction data, provided by open banking, makes it possible to check, in real time, the presence of liquidity in a bank account and its evolution up to the present time. Indeed, the account balance data is just the tip of the iceberg. With algorithms
categorising data across a number of areas – salary, utilities, rent, etc.. – it is then possible to analyse expenses and cash outflows. This would produce a ‘super score’ that could look at high frequency data points as well as lower frequency ones such as
credit behaviour or balance sheets scores.
Open banking is already enabling these changes and the credit risk management function is being transformed as a result. The pandemic is speeding up the pace of this change as the need for more comprehensive, open data, scoring models becomes increasingly
apparent. As we head towards transition and recovery, it is clear that traditional risk management and scoring models will improve through open banking enabled solutions that will benefit us all.