Does regulation bite only the less profitable? Evidence from the too big to fail reforms

Tirupam Goel, Ulf Lewrick and Aakriti Mathur

Reforms following the 2008 financial crisis have led to significant increases in banks’ capital requirements. A large literature since then has focused on understanding how banks respond to these changes. Our new paper shows that pre-reform profitability is a vital, but often overlooked, driver of banks’ responses. Profitability determines the opportunity cost of shrinking assets, and underpins the ability to generate capital. We develop a stylised model which predicts that a more profitable bank would choose to shrink by less (or grow by more) compared to a less profitable bank in response to higher capital requirements. Combining textual analysis of banks’ annual reports with the assessment of a key too big to fail (TBTF) reform, we show that this prediction holds in practice.

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The structure of regulatory revolutions

Austen Saunders and Rajan Patel

What can the history and philosophy of science teach us about regulatory reform? In this post, we borrow Thomas Kuhn’s idea of ‘scientific revolutions’ to argue that radical overhauls of regulation often occur after crises but that, once major reforms have been completed, it’s normal to have periods when rules do not change so much. For instance, major reforms made to banking regulations after the Global Financial Crisis of 2007–08 are now coming to an end with future change likely to be more incremental. This post is about why different circumstances call for these different approaches to regulatory change.

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Impact of the UK QE on banks’ balance sheets

Mahmoud Fatouh

Quantitative easing (QE) involves creating new central bank reserves to fund asset purchases. Deposited in the reserves account of the seller’s bank, these reserves can have implications for banks’ asset mixes. In our paper, we use balance sheet data for 118 UK banks to empirically investigate whether the asset compositions of banks involved in the UK QE operations reacted differently in comparison to banks not involved in the initial rounds of QE between March 2009 and July 2012.

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From Pillar 2 to post: is it time for a change in concentration risk methodology?

Chris Leaney

The Herfindahl-Hirschman Index (HHI) is a measure of diversification, commonly used as an indicator to calculate banks’ credit concentration risk capital requirements (where credit concentration risk is potential losses from undiversified portfolios). According to BCBS (2019) HHI is employed by c. 50% of regulators, including the Prudential Regulation Authority (PRA) since 2016. However, despite some evidence that the data-light, easy-to-implement HHI produces broadly comparable outcomes with formal models (eg Bundesbank (2006)), such evidence is limited to large banks or theoretical datasets. In this post I examine the relationship between HHI and a formal model of sector and geographical concentration risk. I show that, for a wide sample of bank sizes, HHI is poorly correlated with the model outputs for both risk types.

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Quantifying culture and its implications for bank riskiness

Joel Suss, David Bholat, Alex Gillespie and Tom Reader

‘Bad cultures’ at banks are often blamed for scandals and crises, from the global financial crisis to the mis-selling of payment protection insurance (PPI) in the UK. Yet surprisingly little research has tested this claim. This is because quantifying culture is difficult to do. Our working paper gives it a go. Leveraging unique access to data available to regulators, we diagnose the cultural health of the UK banking sector. We find that banks with organisational cultures two standard deviations below the sector average are associated with a 50% increased risk of failure.

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Do banks need belts and braces?

Marcus Buckmann, Paula Gallego Marquez, Mariana Gimpelewicz and Sujit Kapadia

Bank failures are very costly for society. Following the 2007/2008 global financial crisis, international regulators introduced a package of new banking regulations, known as Basel III. This includes a wider range of capital and liquidity requirements to protect banks from different risks. But could the additional complexity be unnecessary or even increase risks, as some have argued? In a recent staff working paper, we assess the value of multiple regulatory requirements by examining how different combinations of metrics might have helped prior to the 2007/2008 crisis in gauging banks that subsequently failed. Our results generally support the case for a small portfolio of different regulatory metrics: having belts and braces (or suspenders) can strengthen the resilience of the banking system.

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How competitive are UK insurance markets?

Fraser Drew, David Humphry, Michael Straughan and Eleanor Watson

For most of us buying insurance nowadays, price comparison websites offer plenty of choice. But how much competition in insurance markets is there? There are very few studies that address this question (see here for a summary), unlike for banking where there is a wide literature. We take an exploratory approach to address the question, applying benchmarks used in competition research to a unique set of reporting data across multiple UK insurance regulatory regimes, with the hope of stimulating further work. We find competition generally works well in UK life and non-life insurance markets, despite increases in life market concentration over the past 25 years. However, competition regulators have found practices in specific markets that harm consumers.

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The leverage ratio: a balance between risk and safety

Jonathan Smith

What was the root cause of the financial crisis? Ask any economist or banker and undoubtedly they will at some point mention leverage (see e.g. here, here and here). Yet when a capital requirement based on leverage — the leverage ratio requirement — was introduced, fierce criticism followed (see e.g. here and here). Drawing on the insights from a working paper, and thinking about the main criticism — that a leverage ratio requirement could cause excessive risk-taking — this seems not to have been the case.

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Setting boundaries: finding thresholds in bank regulation

Zahid Amadxarif, Paula Gallego Marquez and Nic Garbarino

“We’ve done a lot to lower prudential barriers to entry into the banking sector […] but have we done enough to lower the equivalent barriers to growth?” asked PRA CEO Sam Woods in a recent speech. To make regulation proportionate, policymakers adapt regulatory requirements to the risks posed by each firm. But regulators face a trade-off between addressing systemic risks in a proportionate way and limiting regulatory complexity. New thresholds can create complexity and cliff-edge effects that can discourage healthy firms from growing. We identify regulatory thresholds for UK banks and building societies using textual analysis on a new dataset that contains the universe of prudential rules.

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How to see it coming: predicting bank distress with machine learning

Joel Suss and Henry Treitel

The need to see it coming

The great American baseball sage, Yogi Berra, is thought to have once remarked: ‘It’s tough to make predictions, especially about the future’. That is certainly true, but thankfully the accelerating development and deployment of machine learning methodologies in recent years is making prediction easier and easier. That is good news for many sectors and activities, including microprudential regulation. In this post, we show how machine learning can be applied to help regulators. In particular, we outline our recent research that develops an early warning system of bank distress, demonstrating the improved performance of machine learning techniques relative to traditional approaches.

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