Machine learning
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
Podcast: Princeton’s Carmona on the future of quant education
Course director discusses machine learning explainability and reclaiming game theory from economists
Natixis creates model to ‘learn’ how factors interact
Random forest technique sheds light on flux in how factors mix, manager says
Banks use machine learning to ‘augment’ corporate sales
Big banks are embarking on massive projects to tie up machine learning and big data to sell better to clients
Machine learning enters battle against financial crime
Standard Chartered and Barclays using AI to detect money laundering violations
Honesty is key to machine learning’s future – Roberts
Oxford-Man Institute director on why tomorrow’s models will gracefully admit defeat
Quants ‘running into walls’ with AI interpretability
Some firms “stumbling” with new technology, conference hears
Quants say big data is all buzz, no alpha
Efforts to extract alpha from alternative data have been “really unsuccessful”, says Domeyard’s Qi
Quants use AI to cut through murk of ‘sustainability’
Separating the wheat from the chaff is fundamental to ESG investing. Machine learning can do that
Model risk chiefs warn on machine learning bias
ML model outputs open to “potential bias sitting in your datasets”, says RBS model risk head