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.
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.
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.
The financial crisis exposed banks’ vulnerability to a type of risk associated with derivatives: credit valuation adjustment (CVA) risk. Despite being a major driver of losses – around $43 billion across 10 banks according to one estimate – there had been no capital requirement to cushion banks against these losses. New rules in 2014 changed this.
Qun Harris, Analise Mercieca, Emma Soane and Misa Tanaka.
The bonus regulations were introduced based on the consensus amongst financial regulators that compensation practices were a contributing factor to the 2008-9 financial crisis. But little is known about how they affect behaviour in practice. So we conducted a lab experiment to examine how different bonus structures affect individuals’ risk and effort choices. We find that restrictions on bonuses, such as a bonus cap, can incentivise people to take less risk. But their risk-mitigating effects weaken or disappear once bonus payment is made conditional on hitting a high performance target. We also find some evidence that bonus cap discourages effort to search for better projects.
Sebastian de-Ramon, Bill Francis and Michael Straughan.
There is a debate in the regulatory and academic community about whether competition is good or bad for bank stability, particularly following the financial crisis (see Chapter 6 of the Independent Commission on Banking final report). The debate tends to be seen as a head-to-head argument between two camps: those that see competition as bad for stability (competition-fragility) versus those that see competition as good (competition-stability). In new research, we look at how competition affects the stability of banks in the UK. We find that competition affects less stable firms differently than more stable firms and that focussing on what happens to the average firm may not be sufficient.
Last May, the Bank organised an economic history workshop at the St Clere Estate, home of former governor Montagu Norman. In this guest post, one of the speakers David Kynaston, visiting Professor at Kingston University, reflects on more than three centuries of Bank history…
It was a huge honour to be asked by Mervyn King to write a history of the Bank. The eventual book, Till Time’s Last Sand, was published last autumn. It covers 1694 to 2013 and is based heavily on the Bank’s own archive. Fitting more than 300 years of history into a single volume was a difficult task, and condensing that into a short blog post is harder still. Here I will try to bring out a handful of key lessons from my research into the Bank’s history that might be useful for the policymakers, economists and other interested observers of today – and their successors…
Imagine you have just passed your driving test. After many hours of careful instruction, you are keen to put your good driving habits to the test on the open road. You phone up your insurance company but discover that your insurance premiums will cost you hundreds of pounds more than you can afford because “newly-qualified drivers are worse than average”. This post is about how developments in the car insurance market have the potential to revolutionise the way we drive and how we guard against the risks of bangs, scrapes and scratches. The increased use of telematics (also known as black boxes) has important implications for anyone who might consider driving, policymakers and for society as a whole.
A well-insulated house reduces heat loss during cold winter periods and it keeps outdoor heat from entering during hot summer conditions. Hence, effective insulation can reduce the need for households to use cooling and heating systems. While this can lower greenhouse gas emissions by households, it also reduces homeowners’ energy bills, which can free up available income. This can protect households from unexpected decreases in income (e.g. reduced overtime payments) or increases in expenses (e.g. healthcare costs). It could also help homeowners to make their mortgage payments even if such shocks occurred. But does this also imply that mortgages against energy-efficient properties are less credit-risky?