Just as there’s always money to be made from doing dirty jobs, there are opportunities around dirty data—especially in industries that are only now beginning to appreciate the value of being data-driven.
Anthony explores some of the questions raised by Refinitiv's plan to move away from Eikon and Thomson One. He also looks at data governance trends, and asks why the FIGI is having such a tough time gaining acceptance.
Hans delves into machine learning, moonshot projects, technical debt, and what has been learned during the pandemic.
Young firms, using machine-learning methods to scrape consumer info, challenge established agency model.
The asset manager has adopted materiality tools, industry handbooks, and NLP techniques to help navigate ESG data limitations.
ABN, ING and Rabobank are exploring quantum for regulatory stress tests. In the US, Zapata Computing is seeking a patent for the same.
After the route toward accreditation via the ISO petered out, Bloomberg is vying to establish its reference data standard as a system of record in the US, following a win in Brazil.
Quant funds are striving to adjust their ESG models to take into account changes in corporate behavior during the pandemic.
This year's inductee to the Inside Market Data Hall of Fame is Mike Meriton, co-founder and COO of the EDM Council.
The new platform is first being targeted at advisors and wealth managers, and will eventually be available for traders, analysts, portfolio managers, quants, and developers.
The two banks outline their ambitious data governance programs, which make business professionals culpable for their organization's data decisions.
Anthony looks at an interesting project using causal inference by IBM and Refinitiv, and what this latest evolution of machine learning could mean for innovation in the capital markets in the future.
Senior execs from Citizens Bank, Commerzbank, and Deutsche Bank discuss lessons learned during the pandemic.
The two companies are in the early stages of using causal inference to help firms build machine learning models that are better able to handle disruption from events like the Covid-19 pandemic.
In the era of big data, standards take too long to adopt, say industry participants.
The fund administrator’s clients can now access multiple datasets from one data lake.
Inside Market Data & Inside Reference Data Awards 2020
Meaningful data analysis is critical to the future of socially responsible investing, writes Antonia Lim of Schroders.
Experts from IBM and Bank of China say they're on the lookout for this emerging threat, as machine learning gains in popularity.
As CFTC commissioner Rostin Behnam’s report on climate risk to the financial system is published, WatersTechnology speaks to Behnam about data, greenwashing, and gaining support in Washington.
Instead of waiting for data quality to be sufficient to power AI models, those at the cutting edge are building models to bridge the gaps in the data, and apply it to more sophisticated use cases.
Anthony Malakian looks at the industry’s digital rights project and new tech platforms that aim to revolutionize the capital markets.
An assortment of AI experts talk about various machine learning and NLP opportunities and challenges.
Banks are focused on making work-from-home life more secure, but how can these projects be used to improve the customer experience going forward?