Risk management
JP Morgan turns to machine learning for options hedging
New models sidestep Black-Scholes and could slash hedging costs for some derivatives by up to 80%
Royal Commission report sparks conduct risk changes at ANZ
Regulators must work with banks on conduct risk rules to avoid “box-ticking exercise”
LCH veteran Davie set to depart
Clearer looking to fill new role in head of SwapClear and listed rates
BoE makes climate risk a hot topic for banks
Financial institutions must entrust oversight of climate risk to named individual under senior managers regime
Estimation of losses due to cyber risk for financial institutions
The objective of this paper is to analyze cyber risk from an operational risk perspective and to measure cyber risk empirically.
Banks grapple with social media risk
In shadow of Metro Bank WhatsApp episode, panellists warn banks need to deftly handle social media blow-ups
Fund houses get picky over where to use machine learning
Buy-siders limit usage of deep learning techniques due to haziness over their inner workings
Korea tightens autocall oversight as local houses take on risk
Regulator sounds warning over $9 billion increase in structured product self-hedging by Korean firms
All along the watchtower – Surveillance tools against market abuse
Surveillance tools against market abuse are enjoying a technological revolution in analytics, while anxious supervisors are also closing in on market practices. Risk.net hosted a webinar in association with NICE Actimize to analyse the threats and…
The advance of analytics
Machine learning is coming to analytics but there are hurdles to overcome first, says Aiman El‑Ramly, chief operations officer at ZE PowerGroup
Making technology count in a C/ETRM world
As businesses grow, so does their need for modern, agile and cost-effective commodity/energy trading risk management (C/ETRM) solutions. Pioneer Solutions explores how its next-generation, highly configurable C/ETRM systems take advantage of the latest…
Could holding multiple safe havens improve diversification in a portfolio? The extended skew-t vine copula approach
In this paper, the authors propose a vine copula model based on a bivariate extended skew-t distribution and derive its corresponding multivariate tail dependence function.
Loss given default estimation: a two-stage model with classification tree-based boosting and support vector logistic regression
In this paper, the authors using a data set composed of five Japanese regional banks, propose an loss given default estimation model using a two-stage model, classification tree-based boosting and support vector regression (SVR).
The RPA revolution
Doug Wendler, chief executive of Machina Automation, explains the increasing popularity and uptake of robotic process automation (RPA), focusing on how it has recently evolved and how it is expected to continue this evolution, and whether RPA’s…
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…
UBS hires Finma banks chief amid risk reorg
Schoch move comes after bank carves op risk and compliance unit out of central risk function
Introducing a novel system-of-systems axiomatic risk management technique for production systems
This paper focuses on conceptual and modeling frameworks in an attempt to explore qualitative and quantitative risk management techniques for hierarchical SoS risks, exemplifying the production systems for demonstration.
Finding potential in a volatile commodities market
Macquarie is uniquely positioned to offer clients a range of products, expertise and experience across the commodities space. Nick O’Kane discusses the bank’s approach to commodity markets and what he expects next
An alternative approach for the operational risk assessment of a new product
The aim of this paper is to provide a new operational risk management framework to identify and mitigate the operational risk exposure arising from a new product.