AI tool calculates value of bank bailouts during financial crises

Researchers have developed an AI tool designed to help governments decide whether or not to bail out a bank in crisis by predicting if the intervention will save money for taxpayers in the long term.

Developed by a team at UCL and Queen Mary University of London, the tool assesses not only if a bailout is the best strategy for taxpayers, but also 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 using data from the European Banking Authority on a network of 35 European financial institutions judged to be the most important to the global financial system.

Dr Neofytos Rodosthenous, corresponding author of the paper, said: “Government bank bailouts 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 assess specifically financial implications – this means checking if a bailout is in the best interest of taxpayers, or whether it would be better value for money to let the bank fail. Our techniques are freely available for banking authorities to use as tools in their decision-making process.”

In a bank bailout, the government invests in a bank to increase its equity and reduce the risk of defaulting. This cost in the short term may be justified to the taxpayer if it leads to lower taxpayer losses in the long term by preventing bank defaults that are more damaging to government finances.

The researchers created a mathematical framework for comparing different bailout strategies in terms of predicted losses to taxpayers. Considered factors include how long the financial crisis is expected to last, the likelihood of each bank defaulting and the effect of a default on other banks in the network, as well as taxpayers’ stakes in the banks.

They then incorporated into this framework the effect of a government intervention and developed a bespoke AI algorithm to assess optimal bailout strategies.

These strategy options include comparing no intervention to different types of intervention, such as varying levels of investment in one bank or many banks, at different time points during a crisis. An AI technique is needed as modelling such a system is highly complex.

In their case study they demonstrated that a bailout would be optimal only if the taxpayers’ stakes in the banks were greater than some critical threshold value, determined via the model. This threshold helped to determine how governments should respond during a financial crisis.

Government bailouts tended to be more favourable the greater the network’s distress, the longer the crisis lasted and the bigger the banks’ exposures to other banks were – for example, how much money they had lent other banks.

The researchers also found that, once a bank had received a bailout, the best strategy for taxpayers was if the government continued to invest in that bank to prevent default.

Lead author Dr Daniele Petrone said: “Banks have so far weathered the current economic storm triggered by the Covid-19 pandemic.

“Their resilience has been bolstered by regulatory measures introduced following the global financial crisis of 2007-9 and by accommodating central banks’ monetary policies that have avoided bankruptcies across industries.

“However, no one can predict the effect on the financial system as central banks reverse previous policies, such as increasing interest rates due to inflation concerns, and so bailouts are still a possibility.”

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