Artificial intelligence
Quant of the year: Alexei Kondratyev
Risk Awards 2019: A glimpse of the future? Quant uses ML to model term structure and crunch margin costs
Anticipating change – How GRC teams can empower the first line of defence
Financial firms are increasingly adopting the three lines of defence framework to manage risk. But how has the model evolved to date and what does the future look like for this key risk management tool?
Fed’s Brainard wary of black box AI models in consumer credit
Speech raises explainability issue; says existing model risk guidelines are “a good place to start” in regulating AI
AI data could be tainted even as it’s being cleaned
Risk USA: Expert says even touching raw data could lead to loss of context
BlackRock shelves unexplainable AI liquidity models
Risk USA: Neural nets beat other models in tests, but results could not be explained
Banks split on human oversight of AI models
Risk USA: Most firms supervise their models, but one expert says they can be trusted to make decisions
Humans struggle to keep pace with machine learning
Banks and regulators grapple with ‘XAI’ challenge
Obstacles and opportunities in adopting cloud computing
Sponsored Q&A
Machine learning hits explainability barrier
Banks hire AI industry experts in face of growing regulatory scrutiny
Why Dario Villani trusts machine learning
Duality Group CEO says people should abandon ‘top-down, godlike model’ and their need to understand
Trading costs versus arrival price – An intuitive and comprehensive methodology
Craig Niven, managing director, cash equity execution at Societe Generale Prime Services explores how a five‑month study allowed the organisation to develop a market impact model using historical data, and why it is key for clients in the long term to…
At BlackRock’s West Coast AI lab
The firm is handing its ‘most vexing problems’ to artificial intelligence
Banks scan chat and web for trading intel
Market-makers seek new signals on volatility and direction via natural language processing
Big funds muzzle their AI machines
Fears over interpretability, crowding and overfitting have put a damper on efforts to unleash AI for asset management
Hackathon finds pre-trade gold in Isda’s post-trade project
Dealers’ derivatives trade processing costs could be cut by at least $3 billion per year
Do or die – asset managers take up data science
Firms are scanning an ocean of text and images, as well as big number sets, to grab an edge
A call to arms – How machine intelligence can help banks beat financial crime
The revolution in artificial intelligence promises new leads in banks’ fight against dirty money. Alexander Campbell of Risk.net hosted a live online forum, in association with NICE Actimize, to investigate the applications of this emergent technology
Disruptive change in US power markets: Identifying risks and embracing opportunities in the new world of digital
Power markets worldwide are experiencing disruptive changes on a bigger scale and with greater speed than many had anticipated. Now, more than ever, it is essential to understand opportunities and risks associated with these changes
How machine intelligence can help banks beat financial crime
Faced with massive financial crime challenges, many banks have responded by scaling up their functions. However, these investigations take way too much time and require unending growth in person-power
Risktech start-ups struggle to clinch big-bank contracts
Light on cash, risk management fintechs face an extended gauntlet most won’t survive
UBS’s CRO on the hunt for hidden risks
Swiss bank has rung the changes in its attempt to catch hard-to-measure risks, but “you are never safe”, warns Christian Bluhm
Why robo-advisers need artificial stupidity
Smarter algorithms can’t stop us making bad investment decisions – yet, writes Andrew Lo
‘People who bought this swap also bought Apple’
Dealers hope personalisation algos will help them cut sales costs, but data gaps could be a problem