Model validation
Humans struggle to keep pace with machine learning
Banks and regulators grapple with ‘XAI’ challenge
Compliance preparations amid uncertain rules
A forum of industry leaders discusses how banks will define individual trading desks under FRTB, whether BCBS 239 compliance projects can help banks meet FRTB risk data challenges, which model validation obstacles banks still face and other key topics
Quant drought hits banks and funds in Asia
Limited pool of talent hindering expansion of sophisticated strategies across buy and sell side
A call to arms – How machine intelligence can help banks beat financial crime
The revolution in artificial intelligence promises new leads in banks’ fight against dirty money. Alexander Campbell of Risk.net hosted a live online forum, in association with NICE Actimize, to investigate the applications of this emergent technology
Optimal allocation of model risk appetite and validation threshold in the Solvency II framework
In this paper, the authors derive an analytical solution for sub-SCR VTs starting with a model risk appetite (MRA) that defines acceptable errors for an insurer’s total SCR.
French regulator voices doubts on Europe’s FRTB timeline
Federal Reserve warns EU delay would force US to reconsider 2022 implementation
Evaluating the risk performance of online peer-to-peer lending platforms in China
The objective of this paper is to select effective risk indicators and thus establish a risk index system of P2P platforms so as to evaluate the risk performance of these platforms in China.
Banks should quantify loan-loss model risk – academic
Models such as those used for IFRS 9, CECL or CCAR are prone to errors, and should be accounted for
BoE: UK banks falling short on stress-test model risk
Recent guidance on stress-test models could be expanded, says BoE exec
AI models prompt banks to strengthen governance
Risk managers want ‘transparency and clarity’ around AI-based models
Underperforming performance measures? A review of measures for loss given default models
This paper reviews the ways of measuring the performance of LGD models that have been previously used in the literature and also suggests some new measures.
A central limit theorem formulation for empirical bootstrap value-at-risk
In this paper, the importance of the empirical bootstrap (EB) in assessing minimal operational risk capital is discussed, and an alternative way of estimating minimal operational risk capital using a central limit theorem (CLT) formulation is presented.
Deutsche adds senior quant to risk methodology team
Theis leaves role as head of market models at Standard Chartered to join German bank
Banks apply machine learning to CCAR models
ML models benchmarked against traditional iterations to avoid ‘black box’ perception
The three lines of defence: a Sisyphean labour?
Banks have revised Basel’s model to suit their risk profile, but some remain sceptical of its impact on risk culture
Model validators squeezed by stress test deadlines
CCAR cycle frustrates compliance with Fed model risk guidance
Banks tout machine learning amid regulatory concerns
Machine learning being used to build challenger models for model validation
Bayesian analysis in an aggregate loss model: validation of the structure functions
This paper considers the empirical evaluation of a collective risk model with the geometric as the primary distribution and the exponential as the secondary distribution.
The use of the triangular approximation for some complicated risk measurement calculations
The author introduces the triangular approximation to the normal distribution in order to extract closed- and semi-closed-form solutions that are useful in risk measurement calculations.
A practical maturity assessment method for model risk management in banks
This paper proposes a qualitative method to assess the maturity of model risk management practices within banks.
Banks warned off machine learning for model risk
Banks acknowledge they “cannot hide behind a complex tool” to assess interconnectedness
Model risk managers grapple with interconnectedness
US regulators ask banks to assess cross-dependencies of models – prompting some to employ network theory