Artificial intelligence
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.
Capturing alpha in Asia’s ETF market – Trends to watch in 2019
As the inclusion of China A-shares into major indexes could potentially lead to record inflows into China, 2019 is set to be an exceptional year for the Asian exchange-traded funds (ETFs) market. Meanwhile, investors in the region are increasingly eyeing…
Funds use artificial intelligence to weigh ethical investing
Quants explore links between ESG investment and outperformance
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
Active ETFs – The next step in Asia’s ETF innovation
The exchange-traded fund space has long been dominated by passively managed funds, but active ETFs are gaining popularity among investors and issuers. Although active ETFs are not yet a mainstream investment instrument, their growing investor interest is…
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
AI moves into middle office at energy firms
Energy firms explore how artificial intelligence can boost returns
Arnott, Harvey: machine learning dangerous when data thin
Experts warn ML should be used “for its correct purpose”
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