McKinsey: banking models and risk post-COVID-19

By Matt High
The global COVID-19 pandemic has affected banking models across every operation and function, according to an article by McKinsey In the article, publi...

The global COVID-19 pandemic has affected banking models across every operation and function, according to an article by McKinsey

In the article, published on 5 May, McKinsey explains that the outbreak of coronavirus and subsequent measures to contain the pandemic have revealed unexpected flaws in the business models of banks. 

The financial services industry, it says, has suffered just like countless other sectors globally. In particular, banks’ business models have broken down across their entire business. 

Reliability in doubt

This, McKinsey explains, has revealed that “The flaws have put the reliability of these models in doubt and suggest that they cannot be trusted to help banks navigate through the crisis.”

It is noted that, typically, business models employed by banks are built around stability. Naturally, the disruption brought about by the spread of COVID-19 has provided anything but. 

However, McKinsey notes, “the real failure is not that banks used models which failed in this crisis, but rather that they did not have fallback plans to manage when the crisis did come.”

Among the reasons for this failure, it cites models that were created pre-COVID-19 and that use historical data. It also notes that the infrastructure and systems upon which banking models are built are not flexible enough to incorporate the data needed to recalibrate.


With this in mind, McKinsey says that financial institutions must urgently review their model strategies. This should be based around short- and long-term resilience strategies. 

It is also noted that these failures are more widespread than a financial organisation’s processes or direct model. 

Indeed, says McKinsey, the impact on operations is widespread and includes inaccurate rating models, misleading signals on early-warning systems, liquidity models failing to predict large outflows and portfolio rebalancing, and concerns around regulatory models. 

Building the new normal

Banks should adjust their data and methodologies to reflect the post-COVID-19 world, McKinsey says.

This should involve, it explains changes so that they no longer need to rely only on the analysis and judgement of experts or those with specific market insight. 

Accordingly, it set out in more detail a two-part strategy, phase one of which is focused on short-term crisis operating modes for model-risk management (MRM). 

In this phase, says McKinsey, banks should focus on making their adjustment models fit for purpose and on mitigating the risks of poor business decisions. 

It is recommended that a dedicated task force be responsible for this, and that is should be given clear governance, a disciplined operating model and the appropriate tools or technologies. 

This taskforce should consider four actions: an inventory of model adjustments and those models that are at risk; applying model adjustments consistently; performing a rapid challenge of all model adjustments; and applying short and long term redevelopment plans. 

On the second phase - ‘moving to the next level of model-risk management’ - McKinsey says that banks should deploy MRM in a “more strategic and fundamental role, as [they] move more proactively to their portfolios of models”. 

An effective strategy, among other things, should consider an overview of the models at risk and model contagion; and a mode contingency plan. 

The latter could include such things as a remote operating model or adequate infrastructure projections.

For more information on all topics for FinTech, please take a look at the latest edition of FinTech magazine.

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