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.

Continue reading “Quantifying culture and its implications for bank riskiness”

What matters to firms? New insights from survey text comments

Ivan Yotzov, Nick Bloom, Philip Bunn, Paul Mizen, Pawel Smietanka and Greg Thwaites

Text data is often raw and unstructured, and yet it is the key means of human communication. Textual analysis techniques are increasingly being used in economic and financial research in a variety of different ways. In this post we apply these techniques to a new setting: the text comments left by respondents to the Decision Maker Panel (DMP) Survey, a UK-wide monthly business survey. Using over 20,000 comments, we show that: (i) these comments are a rich and unexplored data source, (ii) Brexit has been the dominant topic of comments since 2016, (iii) text-based indices match existing uncertainty measures from the DMP at both the aggregate and firm level, and (iii) sentiment among UK firms has been declining since 2016.

Continue reading “What matters to firms? New insights from survey text comments”

It’s windy when it’s wet: why UK insurers may need to reassess their modelling assumptions

Giorgis Hadzilacos, Ryan Li, Paul Harrington, Shane Latchman, John Hillier, Richard Dixon, Charlie New, Alex Alabaster and Tanya Tsapko

The 2015/16 storms caused the most extreme flooding on record, with parts of the UK impacted by heavy precipitation and extreme wind over a four-month period. These extreme weather events occurred in quick succession, hindering relief efforts and accruing £1.3 billion in insured losses. Without adequate mitigation, such events may result in claims handling strain and capital risk for insurers. Recent research finds that above-average windstorm seasons are typically accompanied by above-average inland flooding. That raises a challenge for insurers: should they have adequate risk mitigation measures in place for periods that are both windy and wet? We argue that insurers need to reassess their model assumptions, especially as climate change might make wet years more frequent than in the past.

Continue reading “It’s windy when it’s wet: why UK insurers may need to reassess their modelling assumptions”

Uncertainty and voting in monetary policy committees

Alastair Firrell and Kate Reinold

The right stance for monetary policy is highly uncertain, and so it is no surprise that members of monetary policy committees – like the Bank of England’s Monetary Policy Committee (MPC) – regularly disagree about the best course of action. Asking a committee to decide allows different opinions to be aired and challenged, with a majority vote needed to determine policy. But how should we expect those disagreements and votes to change in periods of higher uncertainty? Should we expect more 9–0 unanimous votes? Or more 5–4 close contests? We address these questions in this post and find that the degree of disagreement is little changed in periods of high uncertainty, and nor are dissenting votes. There is, however, some difference in how voting decisions are formed when uncertain, with both individual and committee-wide views having less explanatory power for votes.

Continue reading “Uncertainty and voting in monetary policy committees”

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.

Continue reading “Do banks need belts and braces?”

Planes, boats and automobiles: a discussion of machine learning with telematics data

Ali Soliman

Data plays a central role in all technical aspects of insurance and actuarial work. However, utilisation is often still confined to aggregate premium and claims data. Not so in the case of telematics. Say the phrase ‘black box’ and most people will think of flight recorders fitted to aircraft. But Motor insurers also use the millions of data points generated by black boxes, fitted to more than a million cars in the UK, to price risks. What’s more Marine insurers are getting in on the act. In this post we take an actuarial vantage to explore the use of telematics data and consider whether insurers could be using this ‘gold mine’ of information even more widely.  

Continue reading “Planes, boats and automobiles: a discussion of machine learning with telematics data”

Machine learning the news for better macroeconomic forecasting

Arthur Turrell, Eleni Kalamara, Chris Redl, George Kapetanios and Sujit Kapadia

Every day, journalists collate information about the world and, with nimble keystrokes, re-express it succinctly as newspaper copy. Events about the macroeconomy are no exception. So could there be additional valuable information about the economy contained in the news? In a recent research paper, we ask whether newspaper stories could help to predict future macroeconomic developments. We find that news can be used to enhance statistical economic forecasts of growth, inflation and unemployment — but only by using supervised machine learning techniques. We also find that the biggest forecast improvements occur when it matters most — during stressed periods.

Continue reading “Machine learning the news for better macroeconomic forecasting”

Wir sind die Roboter: can we predict financial crises?

Kristina Bluwstein, Marcus Buckmann, Andreas Joseph, Miao Kang, Sujit Kapadia and Özgür Şimşek

Financial crises are recurrent events in economic history. But they are as rare as a Kraftwerk album, making their prediction challenging. In a recent study, we apply robots — in the form of machine learning — to a long-run dataset spanning 140 years, 17 countries and almost 50 crises, successfully predicting almost all crises up to two years ahead. We identify the key economic drivers of our models using Shapley values. The most important predictors are credit growth and the yield curve slope, both domestically and globally. A flat or inverted yield curve is of most concern when interest rates are low and credit growth is high. In such zones of heightened crisis vulnerability, it may be valuable to deploy macroprudential policies.

Continue reading “Wir sind die Roboter: can we predict financial crises?”

The language of rules: textual complexity in banking reforms

Zahid Amadxarif, James Brookes, Nicola Garbarino, Rajan Patel and Eryk Walczak

The banking reforms that followed the financial crisis of 2007-08 led to an increase in UK banking regulation from almost 400,000 to over 720,000 words. Did the increase in the length of regulation lead to an increase in complexity?

Continue reading “The language of rules: textual complexity in banking reforms”

Covid-19 briefing: epi-macro 101

Cristiano Cantore, Federico Di Pace, Riccardo M Masolo, Silvia Miranda-Agrippino and Arthur Turrell

The Covid-19 crisis has led to a swift shift in the emphasis of macroeconomic research. At the centre of this is a new field of inquiry called ‘epi-macro’ that combines epidemiological models with macroeconomic models. In this post, we give a brief introduction to some of the earliest papers in this fast-growing literature.

Continue reading “Covid-19 briefing: epi-macro 101”