The information value of past losses in operational risk

“We show that past #operationalrisk losses are informative of future losses, even after controlling for a wide range of financial characteristics. We propose that the information provided by past losses results from their capturing hard-to-quantify factors such as the quality of operational risk controls, the #riskculture and the #riskappetite of the #bank.” Lire

Work-from-Home and the Risk of Securities Misconduct

#operationalrisk #oprisk #fraud #marketabuse #riskmanagement“Our DD analysis reveals that #workingfromhome lowers the likelihood of securities #misconduct; ultimately those working from home exhibit fewer misconduct alerts.” Lire

Operational Risk: A Global Examination Based on Bibliometric Analysis

Effective #riskmanagement, including #operationalriskmanagement, is crucial for minimizing #financialrisks posed by #operationalrisk. Risk evaluation, which includes assessing potential risks and their #probabilities, is also vital. #bibliometric analysis using #metrics such as citations, networks, co-authorship, and region-based #publications can provide insights into the quality of #research on operational risk and identify gaps. Such analysis reveals a growing interest in the study of operational risk, but also highlights research gaps that […]

Measuring Tail Operational Risk in Univariate and Multivariate Models with Extreme Losses

“This paper considers some univariate and multivariate #operationalrisk #models , in which the #loss severities are modeled by some weakly tail dependent and heavy-tailed positive random variables, and the loss frequency processes are some general counting processes. … The methodology is based on #capitalapproximation within the #baseliii framework (the so-called loss distribution approach).” Lire

Regulation of Cyber Risk in the Banking Sector: A Canadian Case Study

The current #canadian regime, which draws on the #basel #operationalrisk framework, is not equipped to handle the unique challenges of #cyberrisk. Cyber incidents differ from traditional operational disruptions in terms of their dynamism and impact, and traditional risk-based #supervision is not suitable for the rapidly changing cyber profile of #regulated #financialinstitutions. Lire

Operational Risk and the New Caremark Liability for Boards of Directors

In #corporategovernance, where boards are being held liable for #misconduct based on #operationalrisk. Operational misconduct is a critical source of #director #liability and should be given the same attention as #financial #mismanagement. Operational risk marks a fundamental shift in the way boards monitor the firm. Judicial doctrine is changing the way boards manage operational risk, avoid liability, and protect stakeholders’ lives and the society […]

Bankers Trust and the Birth of Modern Risk Management

This paper discusses the origins of modern #riskmanagement concepts and applications in the #financialindustry, which were developed at Bankers Trust in the 1970s. The bank’s “Resources Management” group applied #probability theory to measure #marketrisk, #creditrisk, #liquidityrisk, and #operationalrisk, which were later brought together in a metric called Risk Adjusted Return On Capital (RAROC). RAROC was used to evaluate profitability, guide strategic planning, capital allocation, […]

Reinventing Operational Risk Regulation for a World of Climate Change, Cyberattacks, and Tech Glitches

Proposes a new framework for regulating operational threats such as damage to physical assets, business disruption, and system failures. It suggests replacing rwa regulation with simple buffers of equity and outlines what a “macro-operational” approach to banking supervision might look like. It also acknowledges the limitations of macro-operational supervision and considers what new types of […]

Is Bank CEO Pay Sensitive to Operational Risk Event Announcements?

This study reveals how operational risk events affect US bank CEO compensation from 1992-2016. Results indicate that compensation committees take operational risk into account & that recent regulations have enhanced this process. Additionally, operational risk events have a detrimental effect on options-based compensation. Lire

The Information Value of Past Losses in Operational Risk

“We show that past operational losses are informative of future losses, even after controlling for a wide range of financial characteristics. We propose that the information provided by past losses results from them capturing hard to quantify factors such as the quality of operational risk controls, the risk culture, and the risk appetite of the bank.” Lire

The Bayesian approach to analysis of financial operational risk

“The article provides a short overview of methods for constructing mathematical models in the form of Bayesian Networks for modeling operational risks under conditions of uncertainty. Let’s provide the sequence of actions necessary for creating a model in the form of the network, methods for computing a probabilistic output in BN, and give examples of […]

Imbalanced Data Issues in Machine Learning Classifiers: A Case Study

“… the methods discussed in this paper can apply to general machine learning classifiers in applications with imbalanced data issues, by using a case study in credit card fraud detection this paper calls practitioners’ attention to the imbalanced data problems therein, where class imbalance is often mistreated and lacks theoretical discussion.” Lire

Modeling Very Large Losses.

“… we propose an approach to estimate very large losses similar to that used by Fermi and Drake to estimate the existence of extraterrestrial life. It consists of supposing the event of interest is the result of a concatenation of independent factors and estimating the probability of each factor. The problem is that the events […]

Machine Learning for Categorization of Operational Risk Events Using Textual Description

“…  an overview of how machine learning can help in categorizing textual descriptions of operational loss events into Basel II event types. We apply PYTHON implementations of support vector machine and multinomial naive Bayes algorithms to precategorized Öffentliche Schadenfälle OpRisk (ÖffSchOR) data to demonstrate that operational loss events can be automatically assigned to one of […]

A Text Analysis for Operational Risk Loss Descriptions

“… we have applied text analysis methodologies to extract information from descriptions in the OpRisk database. After delicate tasks like data cleaning, text vectorization, and semantic adjustment, we apply methods of dimensionality reduction and several clustering models and algorithms to develop a comparison of their performances and weaknesses. Our results improve retrospective knowledge of loss […]