Estimating the size and incidence of bank resolution costs for selected banks in OECD countries

Abstract

This report provides estimates of the costs associated with bank resolution both in terms of the expected costs that might arise should a bank fail (i.e. as "ex-post" costs), as well as the cost associated with the likelihood that a solvent bank might fail (i.e. as "ex-ante" costs) over the next year. It finds that expected resolution costs (ex-post costs) have dropped recently due to higher average capital ratios and a lower level of bank liabilities as a percentage of GDP. The annualised value of these expected resolution costs (ex-ante costs), which increased sharply after 2008, has since subsided, but remains well above its 2008 level. Overall, the estimates produced in this report support the notion that recent financial sector reforms have had an impact on reducing the costs associated with bank failure, including the expected costs to taxpayers. However, estimates are in most cases yet to return to pre-crisis levels.

Artificial intelligence applied to bailout decisions in financial systemic risk management

“…The value of α c becomes lower as the distress of the network increases. It is evident from our analysis that the parameter alpha plays a central role in systemic risk modelling and even if there are works [9] [10] studying the impact for the taxpayers linked to a bank default, additional analysis need to be performed for its reliable estimation. Using a simplified Krackhardt kite network, we have found that the government becomes biased toward investing in a risky node if it had already invested in it in the past.…”

“…To be more precise, we first create an intermediate state s by applying the government investments relative to action a t to state s t ; hence each node i of s will have an increased capital E i (t) = E i (t) + ∆J a i (t), an increased total asset W i (t) = W i (t)+∆J a i (t), an increased government investment J i (t) = J i (t) + ∆J a i (t) and a probability of default given by (7) with inputs W i (t) and E i (t). Using the intermediate state s with updated E i (t), W i (t), J i (t) and updated P D i (t), we calculate the transition probability via (see also (9)) the following integral…”

Limiting too-big-to-fail: market reactions to policy announcements and actions

“…Another aspect of that relationship is that implicit guarantees can also have potentially adverse effects on the perceived guarantor. Perceived guarantees are seen as creating contingent fiscal liabilities for the "guarantor", which can be substantial [3,15]). Moreover, they can become real contingent liabilities if events force the conversion of the implicit guarantee into an explicit one and become actual liabilities if the bank in question fails to pay its own debt.…”

Implicit Bank Debt Guarantees: Costs, Benefits and Risks

“…An adverse feedback loop can arise as sovereign credit risk increases, given that the market value of sovereign debt that is held in large amounts by domestic banks loses value (Acharya et al, 2014). Moreover, the perceived contingent fiscal liabilities can be substantial (Snethlage, 2015;Blix Grimaldi et al, 2016;Benczur et al, 2017) and can become real contingent liabilities if events force the conversion of the implicit guarantee into an explicit one. In addition, they can become actual liabilities if the bank in question fails to pay its own debt.…”