Machine learning
Systematic manager puts up guardrails for AI
Boston-based Acadian aims to limit risks from complex, machine learning algorithms
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
Not random, and not a forest: black-box ML turns white
Bayesian analysis can replace forest with a single, powerful tree, writes UBS’s Giuseppe Nuti
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…
Start-up uses AI to zero in on US property deals
Team including former cyber intelligence agents builds model to target real estate transactions
Analytics become top priority at energy firms, poll finds
Middle office still grappling with use of blockchain and artificial intelligence
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…
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…
Baselines for applying machine learning to investing
Techniques that worked in the natural sciences may not translate well to financial markets
Smart weaponry aids bank fight against money laundering
Advanced algos and machine learning gain credence as regulators encourage innovation
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…
Robo traders not so different from us, says Man AHL risk chief
Watching over machine learning algorithms is similar to monitoring human portfolio managers
Making machine learning work for AML
Banks’ anti-money laundering teams are starting to utilise machine learning to combat financial criminals. Risk hosted a webinar in association with NICE Actimize to explore whether these bots can be trusted
Portfolio traders turn to tech – A new generation of strategies
Chris Bruner, head of US credit product at Tradeweb, explores the products that can help managers express portfolio views and how they can maximise the benefits they can reap by evaluating and understanding the price, risk and relative value of each…
FCA steps up anti-money laundering spot checks
UK watchdog changes fincrime head amid speculation AML spot visits increasing because of critical FATF review
Buy-side quant says Brexit a ‘test’ of new AI
Natural language processing can give “more insight” into possible market shudders, says Simonian
Top 10 operational risks for 2019
The biggest op risks for 2019, as chosen by industry practitioners
Funds use artificial intelligence to weigh ethical investing
Quants explore links between ESG investment and outperformance
Could machine learning improve CVA and IM calculations?
Banks have built ways to calculate CVA more quickly, but neural networks could offer more accurate method
CVA and IM: welcome to the machine
Henry-Labordere proposes a neural networks-based technique to price counterparty risk and initial margin
Quants clash: machine learning or linear models?
Some studies say the algorithms beat the common models; other studies say the opposite