There have been extreme economic shocks in Europe and across the world caused by the outbreak of Covid-19 and there is real uncertainty about timing of recovery.
The high risk of bankruptcy facing many SMEs clearly exposes their employees to potential unemployment and the risk of financial difficulties in meeting their credit obligations. However, with the economy contracting generally, the prospect of employees who have been made unemployed finding alternative employment may be limited. Therefore, at this current time, business risk is particularly highly correlated with individual consumers’ credit risk.
The transition to the “new normal” therefore creates multiple challenges in taking a credit-related decision due to uncertainty over:
- Will the business customer and the individual customer face difficulties after the moratorium?
- Will individual customer’s jobs be at risk?
- Will individual customers face a reduction in salary?
These uncertainties therefore raise doubts about whether risk models will be able to fully predict these increased risks.
On the other hand the pandemic created also opportunities: new habits have become instilled in consumers which will undoubtedly remain when recovery returns.
This is good news for the digital transformation programmes many financial institutions have been working on in recent years. They are creating real value for customers and the pace of development in this area is only likely to increase.
Consumer on-line service expectations have been raised by their “one click” interactions with global internet giants and they are looking for comparable experiences in their dealings with banks and financial institutions.
In terms of new customer credit applications, these expectations mean that any form of friction or delay within digital journeys will risk customers abandoning the process and going to a competitor.
Automation to increase the speed of decisioning is therefore critical to securing new customer revenues.
Meeting these new risks, whilst simultaneously meeting consumers’ digital expectations, requires action to be taken in the following areas:
- Update credit risk models and strategies to adapt to current circumstances
- Use all available existing data sources to ensure as comprehensive a view of risk as possible
- Gain new data to improve risk assessment
- Use data in an optimal way with stable and accurate predictive models to achieve high levels of automation
- Automate customer treatment strategies to meet customer expectations