As the coronavirus drives trading volumes, post-trade processing is increasingly an area of operational risk, and firms should consider automation, analyst says.
Unprecedented volatility in March is leading the bank to double down on its AI systems in a big way.
DB's Stuart Gurr says past automation efforts have helped the bank weather the Covid outbreak, highlighting the need for further automation.
Some machine learning strategies have coped well, but others began to struggle as panic mounted.
The platform will use natural language processing to deliver curated research from analysts covering emerging markets.
The firm's chief scientist discusses how NLP is being used to prevent the spread of the coronavirus and how it can be applied for financial services.
Seismic changes in customer behavior are seeing machine learning solutions throw out false positives.
By benchmarking the performance of AI systems, STAC will help firms identify best-of-breed components for creating platforms with the best overall performance.
After a decade of supercharging low-latency applications, Wei-Shen Wong explores how FPGAs are pushing into new areas of the capital markets, driven by interest in AI & ML.
The information services division at the FX settlement specialist is recruiting data analysts for a special project.
Many quants contend that you must be able to interpret machine learning in order to use it.
A summary of some of the past week’s financial technology news.
The data quality and matching specialist is testing an entity resolution model for better transparency and explainability.
The evolution of natural language processing is rapidly progressing. Jo Wright takes a look at BERT, one of the more game-changing innovations that is helping to transform the field of machine learning in the capital markets.
With the growth of alternative data in the capital markets, firms are struggling to find value, and are disillusioned by the loss of time, human capital, and money. Goldman Sachs’ Matthew Rothman believes this has created a situation where vendors and…
Quants searching for ESG signals have reached very different conclusions. Mostly they blame the data.
The bank's securities services arm increased efficiency with chatbots, and is now having interactions with clients—without human involvement.
“The errors made by humans and robots are different,” says Leda Braga
The vendor is also considering including deep learning capabilities to the platform.
S&P Global Market Intelligence will offer clients new alt datasets from in-house and third parties to be used in conjunction with increased analytics offerings.
The machine learning model predicts client demand with high accuracy, giving traders an edge in pricing.
The bank is rounding out the second year in its three-year plan, which includes more than 100 new data roles.
The securities services business has embarked on an API strategy to offload its legacy tech and produce better connected products.