Machine learning
PanAgora uses NLP to cut through Chinese cyber speak
Fund builds Mandarin-reading algo to gauge sentiment of retail investors
Risk Technology Awards 2019: Making machines more helpful
Machine learning can be too efficient; now, vendors are looking for ways to make it more accurate. Clive Davidson looks at the stories behind this year’s Risk Technology Awards
Can robots learn to manage risk?
Will machine learning transform risk management or give birth to a new breed of model risk? Probably both
How AI could tear up risk modelling canon
BlackRock, MSCI, La Française among firms looking to replace traditional, linear risk models
A tech-driven transformation
A panel of experts explores how greater collaboration between risk and finance teams can garner significant benefits and add value, how technological innovation is making the regulatory landscape more complicated to navigate and produce transformative…
Model risk management transformation
Financial institutions have been maturing their approaches to MRM and – as models become more complex and pervasive, and regulatory expectations continue to increase – leading financial institutions seek faster and further movement. Ashutosh Nawani, head…
JP Morgan’s Hudson: innovation stuck in trading web
Risk Live: Digital head floats shared platform, rather than “point solutions”
BoE probes banks on machine learning use
Risk Live: watchdog wants to know “how prevalent” ML models are, say execs
Model risk managers: banking’s future VIPs
Risk Live: Machine learning models are changing the risk profile of banks, says UBS CRO
One size does not fit all – Adapting to meet investment goals
Guillaume Arnaud, global head of quantitative investment strategies (QIS), and Sandrine Ungari, head of cross-asset quantitative research at Societe Generale, explore the benefits of QIS for investors, why flexibility is crucial for investors to meet…
Risk premia strategies – Lessons learned for the future
After a difficult 2018, investors are increasingly wary of risk premia, concerned that factors leading to underperformance might be a recurring problem. Imene Moussa, executive director at UBS, clarifies this issue
UBS unleashes Orca for rates clients
Machine learning algo trawls liquidity pools to slash US Treasury trading costs
Privacy laws crimp bank efforts to snoop on traders
Banks want to surveil employees to prevent malfeasance. GDPR is hobbling those efforts
Fund builds virtual analyst to do ‘grunt work’
Equities unit at Principal Global Investors wants its analysts analysing, not rooting through email and research reports
Keeping the robots honest
Human overseers are in short supply in an arena where losses can be crippling in minutes
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
Cleaning noisy data ‘almost 70%’ of machine learning labour
Quants flag signal-to-noise ratio as key to reducing overfitting risk
From DNA to DHA – Preparing for a new era of digital human augmentation
As technology increasingly permeates societies, cultures and everyday activities, its integration into people’s lives is having a profound impact on what is expected of people in the workplace. Deloitte examines this evolution of today’s workforce, the…
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…