The bank is one-third of the way through a three-year project to re-engineer its data management processes to become a more data-driven business.
There is a movement underway to establish universal standards and the semantic ontologies that make them sing. As the industry approaches semantic utopia, questions remain about what steps need to be taken to get there and whether all the work will be…
WatersTechnology speaks with data specialists from all parts of the capital markets in an in-depth examination of deep learning's impact in finance.
To a hammer, every problem looks like a nail. Similarly, many in the financial industry think the growing data science space will solve all problems. But firms should be more critical of their needs before using data science as a hammer.
A new study finds that while large asset managers are investing in big data analytics and alternative data, it’s a fraught process.
Its portfolio of ‘ready-made POCs’ assist financial services, banking and insurance firms in proving the return on investment issue.
Banks are looking to cash in on the alternative data boom, but an in-depth investigation of the alternative data market shows that they may be in for an uphill battle to claim territory.
Equity Kinetics provides an overview of the US equities market for buy-side and sell-side trading and investment decision support operations.
Firms are using machine learning and natural-language processing tools—no longer to grab an edge, but merely to remain competitive.
The use of biometrics and identification technologies has skyrocketed within retail banking and has become an intrinsic part of the latest technology devices. But now the financial-markets industry is latching on to the potential of these technologies,…
As they deploy automation to solve regulatory problems, Asian firms are paying closer attention to data’s journey.
During his keynote address at EFIS, Virgin Atlantic’s head of data and insight revealed the airline’s approach to data management and innovation.
Waters examines some of the most important events in financial technology of the past 25 years.
How much time do data scientists, analysts and quants spend doing the jobs they're employed to do? In the vast majority of cases, not enough
Maranca will be responsible for executing a global data strategy at Schneider Electric.
Charles Randell says data and technology usage by firms should "liberate" not "disenfranchize" consumers, and regulation is "central to defining" ethical practices.
The bank’s asset management arm believes that trawling its home waters for data will land a valuable catch. Risk.net’s Faye Kilburn speaks to the data scientist at its helm.
To solve the old needle-in-a-haystack problem, Digital Reasoning is developing a tool dubbed Cognition to improve the training process for machine-learning models.
IMD/IRD Awards 2018
The relatively nascent alternative data industry is creating challenges for asset managers, specifically when it comes to a lack of historical data and a lack of talent that can interrogate the data.
Partnership with European Space Agency will apply machine learning to financial markets.
In response to client demand, FactSet is making "alternative" datasets from a select range of partners available via its datafeeds, alongside its proprietary data.
AI is experiencing a renaissance, but some are concerned that it could carry hidden risks.
Afshar, a former academic and Goldman Sachs exec, will be responsible for building a proprietary AI platform and supporting team of data scientists.