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.
The investment bank’s deputy chief digital officer says machines cannot predict markets, as the bank consolidates trading operations and builds an AI trading platform for fixed income and FX.
As the spread of false information online threatens our view of the world, Josephine Gallagher examines how this phenomenon has evolved with technology.
Oracle is using deep learning to find matching patterns for graph analytics within its compliance platform.
The bank is in the throes of a hefty transformation project within its Investor Services division, which began with machine-learning efforts last year.
The company is combining different data sources to help users spot market abuse and manipulation.
Machine learning shows promise in grouping assets better and predicting regime shifts, say fund managers.
WatersTechnology looks at 16 projects in the capital markets that involve machine learning to show where the industry is heading.
Throughout 2019, artificial intelligence (AI) has been one of the most predominant buzzwords in the financial technology space. AI has promised enhanced accuracy and improved efficiencies, allowing staff to focus on higher-value tasks—it truly has the…
As increased regulatory reporting obligations add to the pressure financial institutions are under to manage intraday liquidity, centralizing siloed legacy systems into a single automated solution can offer an enterprise-wide, real-time view of liquidity…
Vast amounts of data and processing could hinder exploitation of emerging tech, says Ravi Radhakrishnan as it partners with MIT-IBM Research lab.
The bank is looking to automation in the middle and back offices as it seeks to exploit emerging technologies.