Artificial intelligence
Privacy laws crimp bank efforts to snoop on traders
Banks want to surveil employees to prevent malfeasance. GDPR is hobbling those efforts
Business lines must answer for ML biases – OCC’s Dugan
Banks cannot blame developers or vendors for faulty machine learning models, says regulator
From memos to texts, algos fish for signals in-house
Hedge funds turn to natural language tools to pry more value out of their analysts’ internal writings
Artificial intelligence – Genuinely unintelligent without high-quality data
For over 10 years, Refinitiv has transformed unstructured content into high-quality, machine-readable data because even the smallest error can cause artificial intelligence massive problems.
Cleaning noisy data ‘almost 70%’ of machine learning labour
Quants flag signal-to-noise ratio as key to reducing overfitting risk
Check mates – AI and the future of KYC
Financial crime prevention is an increasingly complex task for financial services firms. Criminal activities such as money laundering and fraud have rocketed, and the perpetrators are getting smarter. Amid tightening regulation and the threat of…
Machine learning governance
The ability of machine learning models to read great quantities of unstructured data, spot patterns and translate it into actionable information is driving a significant uptake in the technology. David Asermely, SAS MRM global lead, highlights the need…
New applications in Asia’s financial crime analytics
Financial crime is a fast-growing problem for Asia‑Pacific financial services firms. Working with outmoded systems and patched-up processes to detect, monitor and eliminate potential threats, banks are spending millions on sophisticated new solutions to…
Apac banks call for regulatory push on AML tech
“Regulators have got to stop being okay with how things currently are,” says financial crime head
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
Burden of implementing US sanctions now firmly on energy firms
Energy firms must now screen operations of every vessel they deal with, writes maritime data expert
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…
Artificial intelligence – Genuinely unintelligent without high-quality data
For over 10 years, Refinitiv has transformed unstructured content into high-quality, machine-readable data because even the smallest error can cause artificial intelligence massive problems.
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
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…
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…
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
FCA steps up anti-money laundering spot checks
UK watchdog changes fincrime head amid speculation AML spot visits increasing because of critical FATF review
Yield curve fitting with artificial intelligence: a comparison of standard fitting methods with artificial intelligence algorithms
In this paper, the author expands standard yield curve fitting techniques to artificial intelligence methods.