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A-Team Data Management Summit Outlines Elements of Optimal Data Management
Organising for optimal data management, transformation challenges, operational models, data quality, emerging technologies, data governance and, of course, regulation were top agenda items at A-Team Group’s recent Data Management Summit in New York City. The first keynote speaker, David Luria, vice president, front office data intelligence programs at T. Rowe Price, set the scene for…
Markit Mixes Old and New to Deliver FRTB Compliance Solution
Markit is pulling together existing products and new developments to deliver a compliance solution for the market risk capital requirements of the Fundamental Review of the Trading Book (FRTB), which comes into force in 2019. The solution is based on a modular platform, allowing banks to supplement existing infrastructure and processes as needed, and is…
The Reference Data Utility: How Goldman Sachs, JPMorgan Chase & Co and Morgan Stanley are breaking the reference data mold
The Reference Data Utility (RDU) built by SmartStream and backed by Goldman Sachs, JPMorgan Chase & Co, and Morgan Stanley is up and running and ready to deliver reference data management services to the banks. The concept of multi-tenant data utilities is not new, but none have achieved buy-in at the level of the RDU,…
Data Management Summit Focuses on Blockchain and Fintech
Blockchain technology and fintech firms are high on the hype list, but their practical contribution to data management is beginning to materialise and is expected to be the subject of robust discussion at this week’s A-Team Data Management Summit in New York. Adam Bryan, an independent consultant, will moderate a panel session at the summit…
New York Data Management Summit Considers the Challenges of Transformation
Transformational change in data management is on the agenda at many financial institutions, but how best can it be achieved and what types of solutions are available to support it? These questions and more will be addressed by experts during a panel session at this week’s A-Team Data Management Summit in New York. Independent consultant…
Recorded Webinar: How to Track Data Lineage for Enterprise Data Management
Data lineage, the ability to track the source and lifecycle of your reference data, is becoming increasingly important as regulations call for greater transparency and risk managers require confidence in the data feeding their models. What regulations are driving the need for data lineage, what do you need to be able to demonstrate, and what…
A-Team Data Management Summit Discusses Hot Topics and Technologies
Data governance, operations automation, data quality, regulation, blockchain technology, Know your Customer (KYC) and client onboarding were among the hot topics discussed at this week’s A-Team Group Data Management Summit in London. The first keynote of the day, Data Governance – Winning Hearts and Minds, was presented by Kevin Ayling, head of data quality governance…
Strategic Responses to Unrelenting Regulation
Financial institutions continue to take a tactical rather than strategic approach to data management for multiple regulations, but change is on the way and will be discussed during a panel session on the challenges and opportunities of incoming regulation at this week’s A-Team Group Data Management Summit in London. Panel member Peter Warms, manager of…
Developing Best Practice for Optimal KYC and Client Onboarding Performance
Know Your Customer (KYC) and client onboarding programmes are well established in the banking sector, driven by regulatory requirements and beginning to deliver tangible benefits – but there is still much to be done to achieve best practice for optimal performance. The data management challenges presented by KYC and onboarding, as well as the opportunities…
Data Management Experts Discuss the Dilemmas of Data Quality
Data quality has become an imperative for financial institutions as they face increasing regulation and look to data for business benefits and opportunities – but it is not always easy to achieve and requires significant investment in time and resources. For many institutions, a definition of data quality is based on some or all of…