Machine learning
Banks welcome US overhaul of AML rules
Proposals signal shift to risk-based approach to financial crime detection
Differential machine learning: the shape of things to come
A derivative pricing approximation method using neural networks and AAD speeds up calculations
How Shell integrated FX algos into its corporate treasury mix
Interview: oil giant puts up to 50% of spot flows through algos, explains FX head Michael Dawson
Podcast: CFM’s Bouchaud on agent-based models and ESG investing
Hedge fund quant, and Risk.net’s new columnist, shares his unique take on markets
The data anonymiser
Non-parametric approaches anonymise datasets while reproducing their statistical properties
Podcast: Dario Villani on managing money with ML
Duality’s CEO discusses key to machine learning success, and the influence of Renaissance’s Jim Simons
Study suggests banks may be better off with simpler VAR models
Non-parametric VAR models perform well in calm markets, but miss the mark in volatile periods
Spotting co-movement breakdowns with neural networks
Autoencoders can detect changes in relationship between assets in real time
Driving anti-money laundering efficiency gains using artificial intelligence
Anti-money laundering (AML) is expensive and labour-intensive, and artificial intelligence (AI) can offer improved efficiency gains. Could they be a match made in heaven? This Risk.net webinar, in association with NICE Actimize, took place amid the…
Consumer credit modelling software of the year – SAS
Risk Technology Awards 2020
Integrating macroeconomic variables into behavioral models for interest rate risk measurement in the banking book
This paper proposed a nonparametric approach to decompose a macroeconomic variable into an interest-rate-correlated component and a macro-specific component.
Banks race to adapt AML systems for the coronavirus age
Lenders expect regulatory lashing if controls fail to keep pace with changes in criminal behaviour
To model the real world, quants turn to synthetic data
Future financial models will be built using artificially generated data
Covid-19 tumult is testing AI fund returns
Some ML strategies have coped well, but others began to struggle as panic mounted
Covid-19 frazzles AI fraud systems
Seismic changes in customer behaviour see machine learning solutions throw out false positives
Deep learning calibration of option pricing models: some pitfalls and solutions
Addressing model calibration and the issue of no-arbitrage in a deep learning approach
Lighting up the black box: a must for investors?
Many contend you must be able to interpret machine learning in order to use it
At Numerai, real-world figures need not apply
AI hedge fund CEO sees the light in black-box technology
Factor strategies seesaw in coronavirus-hit markets
Quants struggle to second-guess ongoing effect of virus on investments