An artificial intelligence tool developed by researchers from UCL and Queen Mary University of London could help governments decide whether to bail out a bank in crisis by predicting whether the intervention will save money. money for taxpayers in the long run.
The AI tool, described in a new article in Nature Communicationnot only assesses whether a bailout is the best strategy for taxpayers, but also suggests how much should be invested in the bank and which bank or banks should be bailed out at any given time.
The algorithm was tested by the authors using data from the European Banking Authority on a network of 35 European financial institutions deemed most important to the global financial system, but it can also be used and calibrated by banks countries using detailed proprietary data not available. to the public.
Dr Neofytos Rodosthenous (UCL Mathematics), corresponding author of the paper, said: “Bailouts of public banks are complex decisions that have financial, social and political implications. We believe the AI approach we have developed can be an important tool for governments, helping officials specifically assess the financial implications – that means checking whether a bailout is in the best interests of taxpayers, or whether it would be more profitable to let the bank fail. Our techniques are freely available for banking authorities to use as tools in their decision-making process.”
Co-author Professor Vito Latora (Queen Mary University of London) added: “Governments and banking authorities can also use our approach to look back on past crises and gain valuable lessons to inform future action. One could, for example, look at the British government’s bailout plan. of the Royal Bank of Scotland (RBS) during the financial crisis of 2007-2009 and consider how this could potentially be improved (from a financial perspective) in the future to primarily benefit taxpayers.
In a bank bailout, a government investment in a bank increases the bank’s equity and reduces its risk of default. This short-term cost can be justified for the taxpayer if it results in a reduction of the taxpayer’s losses in the long term, ie it avoids bank failures which are more detrimental to public finances.
In their study, the researchers created a mathematical framework to compare different bailout strategies in terms of expected taxpayer losses. Factors taken into account include the expected duration of the financial crisis, each bank’s probability of failure and the effect of failure on other banks in the network, as well as taxpayers’ holdings in the banks.
Using a mathematical control process, called the Markov decision process, the researchers built into this framework the effect of government intervention at a given time.
They then developed a bespoke AI algorithm to assess optimal rescue strategies, comparing no intervention to different types of intervention, i.e. varying levels of investment in a bank. or in several banks, at different times of a crisis. An AI technique is needed because modeling such a system is very complex, as the future behavior of all banks in the system can be infinite.
In their case study using data from the European Banking Authority, they showed that government bailout would only be optimal if taxpayers’ stakes in banks were above a certain critical threshold value, determined via the model. The optimal policy changed drastically once the percentage loss exceeded this threshold.
In addition, government bailouts have been shown to tend to be more favorable the greater the network distress (defined in terms of the percentage reduction in bank equity), the longer the crisis lasts, and the longer the crisis. the banks’ exposures to other banks were significant (i.e. how much they had lent to other banks and therefore stood to lose if those banks failed).
The researchers also found that once a bank received a bailout, the best strategy for taxpayers was for the government to continue investing in that bank to avoid defaults. This could lead to a lack of incentive for the rescued bank to hedge against risk, which could increase risk taking.
Lead author Dr Daniele Petrone said: “So far, banks have weathered the current economic storm unleashed by the COVID-19 pandemic. Their resilience has been strengthened by the regulatory measures introduced following the global financial crisis of 2007-2009 and by accommodating central banks. monetary policies that have avoided bankruptcies in all sectors. However, no one can predict the effect on the financial system as central banks undo previous policies, such as raising interest rates due to inflation concerns, and therefore bailouts are still possible.
An AI approach to managing financial systemic risk via taxpayer bailouts of banks, Nature Communication (2022). DOI: 10.1038/s41467-022-34102-1
Provided by University College London
Quote: AI tool predicts when a bank should be bailed out (November 17, 2022) Retrieved November 17, 2022 from https://phys.org/news/2022-11-ai-tool-bank-bailed.html
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