Modelling
Modelling cyber losses could get easier – study
Cyber losses behaved much like non-cyber losses when grouped by severity, so perhaps less data is needed
Basel NMRF changes don’t solve Asian data challenges
Isda AGM: Asian regulators may still need to soften FRTB standards locally, warn bankers
The future of operational risk management
As the efficiency of operational risk management remains a top priority and pressure to maximise value increases, emerging technology could prove crucial. Nitish Idnani, leader of oprisk management services at Deloitte, explores how the oprisk management…
Fed preps draft white paper on cyber risk
US regulator seeks industry input for initiative on classifying and modelling threats
FRTB: Singapore’s banks eye internal models for forex desks
New market risk regime dangles capital savings for own-models approach
Cyber modelling masks scale of potential losses, study finds
Different statistical approaches produce big variations in future loss estimates, says Esma researcher
Revised Basel output floor to bind 41% of European banks
Cap on modelled capital will also constrain 6% of Americas banks and 34% of banks from the rest of the world
Japan regulator: new FRTB will help uniform Asian uptake
Relaxation of non-modellable risk factors, among other revisions, welcomed by FSA
At US G-Sibs, 11 VAR breaches in 2018
The final quarter of 2018 saw a record number of VAR breaches at the biggest US banks
Model risk chiefs warn on machine learning bias
ML model outputs open to “potential bias sitting in your datasets”, says RBS model risk head
Valuation model risk on the rise at EU banks
Over two-thirds of fair value assets priced using banks' models
HSBC hires new head of model validation
Bank appoints Credit Suisse veteran to key role
BNPP, Credit Suisse, State Street incur VAR breaches
BNP Paribas capital multiplier increases on seventh breach in nine months
The disputed terrain of model risk scoring
There is no concord on how banks should police their model risk. But two Fed economists have an idea
How to apply Python to complex financial markets
The unprecedented proliferation of data in derivatives markets has led to a rise in popularity of Python, a multipurpose programming language known for its versatility and flexibility. Undoubtedly, the increased adoption of Python has helped enable…
Humans struggle to keep pace with machine learning
Banks and regulators grapple with ‘XAI’ challenge
Trading costs versus arrival price – An intuitive and comprehensive methodology
Craig Niven, managing director, cash equity execution at Societe Generale Prime Services explores how a five‑month study allowed the organisation to develop a market impact model using historical data, and why it is key for clients in the long term to…
Python – Is the buzz justified?
Python is rapidly becoming the world’s most popular programming language and its versatility and ease of use has enabled it to achieve widespread adoption in finance, becoming the multipurpose tool of choice for quantitative analysts and other financial…
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
Risk.net podcast: DTCC’s Lind on FRTB, data pooling and NMRFs
As many as 70 banks globally could adopt internal model approach for market risk capital
Ibor transition valuation and risk management considerations
The impending move from interbank offered rates to alternate reference rates will require important changes to many valuation and risk management processes and infrastructure. EY Financial Services’ Shankar Mukherjee, Michael Sheptin and John Boyle…