Artificial intelligence
HSBC and the risk-advisory robot
Bank has amassed 10-petabyte pool of client data to spot hedging, financing and payments needs
Credit risk quants are hitting the tech gap
An appetite to cut the costs of IRB is constrained by tougher regulatory scrutiny
Broadening horizons – Expanding global presence to explore technological opportunities
As institutions increasingly focus on streamlining their operations within markets in which they are comfortable and established, BNP Paribas Securities Services is breaking the mould, investing in innovative technologies and making itself seen and heard…
Taking the lead on financial crime regulatory compliance
Increased scrutiny of anti-money laundering and customer due-diligence procedures means banks must create more efficient and effective systems. A recent webinar conducted by Risk.net and IBM discussed how leading banks are utilising artificial…
Global perspectives on operational risk management and practice: a survey by the Institute of Operational Risk (IOR) and the Center for Financial Professionals (CeFPro)
This paper presents survey results which represent comprehensive perspectives on operational risk practice, obtained from practitioners in a wide range of countries and sectors.
The machine shines in Hong Kong A-share fund
Strategy run by ChinaAMC (HK) combines machine learning with human judgement to outdo rivals
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