Blog Post

The impact of COVID-19 on artificial intelligence in banking

COVID-19 has not dampened the appetite of European banks for machine learning and data science, but may in the short term have limited their artificial-intelligence investment capacity.

By: , , and Date: April 15, 2021 Topic: Banking and capital markets

Before COVID-19, banks were keen adopters of artificial intelligence (AI), including machine learning and other advanced data-science techniques. After the technology sector, the financial services sector was the biggest spender on AI services in 2018. Thanks to such massive investment, AI now powers a wide range of tasks. Machine-learning systems trade, detect fraud, engage with customers and help banks comply with regulatory requirements.

On the face of it, the pandemic should reinforce banks’ adoption of AI. Accelerated digitalisation generates new data processing needs, while ultra-low interest rates and weakened revenues call for cost savings. But the crisis weakens the business case for AI in at least two respects. Machine-learning models trained on historical data are less useful when the present looks nothing like the past – 2019 data is little help in predicting whether Spanish hotels will survive 2021. Weak profitability may also drain banks’ R&D budgets and executive patience to invest in fundamental transformation. Rather than speeding up AI adoption, could the pandemic therefore impede the banking sector’s use of, and spend on, AI?

COVID-19 and the banking business case for AI

Early evidence suggests that banks’ interest in adopting machine learning and data science has continued during the COVID-19 crisis, and may have increased. Half of banks polled in a summer 2020 Bank of England survey said the COVID-19 crisis has made machine learning and data science more important for the future[1]. Over a third reported an increase in the number of their planned use-cases, with the business areas directly affected by the pandemic, such as customer engagement, expected to grow the most. One explanation for this is that machine learning and data science are part of a wider digitalisation of banking services, which has accelerated as a result of COVID-19. The first wave of the pandemic triggered a 10 to 20 percent rise in online and mobile banking across Europe. The trend towards increasingly digital banking services appears to have continued throughout 2020.

[1] The survey was sent to 26 banks in August 2020 that collectively account for roughly 90% of UK banking sector assets. Survey respondents included UK headquartered banks and European, North American and Japanese banks operating in the UK.

Figure 1: Impact of COVID-19 on banks’ plan to invest in machine learning and data science by use case

Source: Bank of England.

But a significant proportion of the banks surveyed by the Bank of England are not spending more on AI. Even though half of banks consider AI more important for their future operations, less than a quarter plan to increase funding and resourcing for planned applications. Moreover, 12% of banks plan to reduce funding for future applications. Some corroborating evidence for this can be found in hiring data, which shows that banks hired less AI talent in 2020 compared to previous years (Figure 2). So why the discrepancy?

The COVID-19 crisis partly explains banks’ budgetary reticence. The net income of European banks has fallen substantially during the crisis (although most of the decrease is down to provisions, which could be written back if loan losses do not materialise on the scale anticipated). Benoit Cœuré, who heads the Bank for International Settlement’s Innovation Hub, has warned of a possible technological divide between underperforming European banks and their more profitable American counterparts.

In addition to tighter budgets, the crisis has affected the performance of banks’ models (both machine learning and non-machine learning) and this may explain their reluctance to invest in new projects. Machine learning is only as good as the past data used to train it. Given the sudden, severe and unpredictable nature of recent epidemiological events, the performance of banks’ machine-learning models has suffered. Over a third of banks surveyed by the Bank of England reported their models had been negatively impacted by COVID-19 (Figure 3).

Figure 3: Opportunities and risks encountered by banking machine-learning and data-science applications as a result of COVID-19

Source: Bank of England. 

What next? The outlook for banks’ use of AI in a post-COVID world

The impact of COVID-19 will likely be felt for years. Nevertheless, despite the pandemic, general interest in AI has been resilient. Worldwide Google searches on the topic of AI remained largely unchanged in 2020 and spiked in the first months of 2021. Similarly, academic output on AI stayed on course (in terms of academic publications, with either ‘machine learning’ or ‘artificial intelligence’ as key words, in the EBSCO and Scopus databases).

Interest in and application of AI in Europe’s banking sector has also been resilient. In the immediate post-pandemic world, many banks may seek to improve their profitability through cost-containment strategies. For AI, this could mean a reallocation of resources away from development of new trading models towards replacement of existing manual processes with automated routines, such as mortgage assessments. JP Morgan in 2016 reduced the time to review commercial loan contracts from 360,000 man-hours to a few machine-seconds. More such use cases will likely be explored by banks.

Banks may also seek to retrain machine-learning models to better perform under conditions of sustained instability, for example through an increased reliance on fast economic indicators and advanced simulation techniques that use reinforcement learning.

Some long-term pre-COVID-19 trends will likely persist. The digitalisation of society (accelerated under lockdown) and banking will continue to generate more data for banks to use. And as a new generation of workers with data-science skills joins the workforce, AI capabilities may become more affordable.

Regulatory clarity could also further boost AI adoption. Central banks and regulators, keen adopters of AI themselves, are engaging in dialogue with firms to support safe adoption and understand how existing policy frameworks affect and encompass AI. The French and German prudential regulators have already published discussion papers that outline some of the considerations for supervising banks’ use of AI. The European Commission is set to propose a regulatory framework for trustworthy AI this year, which will address uncertainties around liability and provide safeguards against algorithmic bias.

COVID-19 may have tempered banks’ spending appetite for expensive AI projects temporarily, but the pressure to cut costs and automate is stronger than ever. The use of AI could help banks boost revenues, reduce costs and uncover new and previously unrealised opportunities. Meanwhile, use of online and mobile banking is expected to continue at higher levels once the pandemic subsides, with between 15% and 45% of consumers expecting to cut back on branch visits following the end of the crisis. Despite their current budgetary constraints, it seems likely that banks across Europe will continue to build their AI capacity.

David Bholat is senior manager in Advanced Analytics, the Bank of England’s centre of excellence in data science, and was a Bruegel visiting scholar in 2019. Mohammed Gharbawi and Oliver Thew are senior Fintech specialists at the Bank of England’s Fintech Hub.

Recommended citation:

Anderson, J., D. Bholat, M. Gharbawi and O. Thew (2021) ‘The impact of COVID-19 on artificial intelligence in banking’, Bruegel Blog, 15 April

Republishing and referencing

Bruegel considers itself a public good and takes no institutional standpoint. Anyone is free to republish and/or quote this post without prior consent. Please provide a full reference, clearly stating Bruegel and the relevant author as the source, and include a prominent hyperlink to the original post.

Read article Download PDF

Parliamentary Testimony

European ParliamentInclusive growth

Understanding the socioeconomic effects of the COVID-19 pandemic on women

Testimony before the European Parliament's Committee on Economic and Monetary Affairs (ECON) on the consequences of the pandemic on women.

By: Maria Demertzis and Mia Hoffmann Topic: European Parliament, Inclusive growth, Macroeconomic policy Date: October 27, 2021
Read about event More on this topic

Upcoming Event


Phasing out COVID-19 emergency support programmes: effects on productivity and financial stability

How can European countries phase out the COVID-19 support measures without having a negative impact on productivity and financial stability?

Speakers: Maria Demertzis and Laurie Mayers Topic: Macroeconomic policy
Read article

Blog Post

Inclusive growth

Concentration of artificial intelligence and other frontier IT skills

Online job postings indicate that demand from top tech firms for frontier IT skills is about double their demand for other IT skills. This could indicate increasing concentration of skills in a few firms, with other firms left behind.

By: Wang Jin, Georgios Petropoulos and Sebastian Steffen Topic: Digital economy and innovation, Inclusive growth Date: October 21, 2021
Read about event

Upcoming Event


Future of work and inclusive growth: Annual conference

The inaugural conference of the the project Future of Work and Inclusive Growth in Europe.

Speakers: Janine Berg, Stijn Broecke, Mario Mariniello, Laura Nurski, Sharon Parker, Kim Van Sparrentak and Tilman Tacke Topic: Digital economy and innovation, Inclusive growth Location: Bruegel, Rue de la Charité 33, 1210 Brussels
Read article More by this author

Blog Post

European governance

Pandemic prevention: avoiding another cycle of ‘panic and neglect’

Agreement is needed at international level on mechanisms to ensure better preparedness for the next pandemic.

By: Anne Bucher Topic: European governance, Global economy and trade Date: October 7, 2021
Read article More on this topic More by this author


Letter: Declining investment may explain why rates are low

Perhaps an analysis of the causes of the declining investment rate would bring us closer to explaining why real interest rates are so low.

By: Marek Dabrowski Topic: Macroeconomic policy Date: October 1, 2021
Read article More on this topic More by this author


What Evergrande signals about China's economic future

Under Xi Jinping's new economic agenda 'common prosperity', China is cracking down on indebted real estate developers like Evergrande.

By: Alicia García-Herrero Topic: Global economy and trade Date: September 30, 2021
Read article More on this topic More by this author

Blog Post

Monetary arithmetic and inflation risk

Between 2007 and 2020, the balance sheets of the European Central Bank, the Bank of Japan, and the Fed have all increased about sevenfold. But inflation stayed low throughout the 2010s. This was possible due to decreasing money velocity and the money multiplier. However, a continuation of asset purchasing programs by central banks involves the risk of higher inflation and fiscal dominance.

By: Marek Dabrowski Topic: Macroeconomic policy Date: September 28, 2021
Read article More on this topic More by this author


The pandemic’s uncertain impact on productivity

The pandemic has certainly permanently affected our way of working. Whether this is for the better remains to be seen.

By: Maria Demertzis Topic: Macroeconomic policy Date: September 28, 2021
Read article Download PDF

External Publication

Building the Road to Greener Pastures

How the G20 can support the recovery with sustainable local infrastructure investment.

By: Mia Hoffmann, Ben McWilliams and Niclas Poitiers Topic: Global economy and trade, Testimonies Date: July 15, 2021
Read about event

Past Event

Past Event

Financing for Pandemic Preparedness and Response

How can we better prepare for future pandemics? In this event, co-hosted by the Center for Global Development and Bruegel think tanks, speakers will present "A Global Deal for Our Pandemic Age", a report of the G20 High Level Independent Panel on Financing the Global Commons for Pandemic Preparedness and Response.

Speakers: Masood Ahmed, Victor J. Dzau, Amanda Glassman and Lawrence H. Summers Topic: Banking and capital markets, Global economy and trade Location: Bruegel, Rue de la Charité 33, 1210 Brussels Date: July 14, 2021
Read article More on this topic

Blog Post

Fair vaccine access is a goal Europe cannot afford to miss – July update

European countries must do more to tackle the vaccine uptake gap. Vaccination data should be published at the maximum granularity level so researchers and local decision-makers can monitor progress.

By: Lionel Guetta-Jeanrenaud and Mario Mariniello Topic: Macroeconomic policy Date: July 14, 2021
Load more posts