i. Data is sourced from different financial data providers, trading venues/ exchanges, rating agencies etc.
ii. This data is then processed in raw form (cleansed, and uploaded)
iii. Business rules and validations are applied to the raw data including data enrichment, multiple vendor hierarchies, etc. to prepare a single 'GOLDEN COPY' of data for a client.
iv. The offering comprises an IT application, underlying hardware/ software platform, a highly competent IT team and very strong Data Management Operations team.
v. Sustainable solution for clients: once the "golden template" is in place, only maintenance cost will incur.
UBS Fund Services - based in Luxembourg - is the first international FI to adopt this service. The initial contract is for five years.
How did TM develop its data-as-a-service platform? What need did your company see for this kind of service in the financial industry?
Over the years our BFSI clients have been telling us about this nagging problem. We saw this as an opportunity to develop a solution which could be disruptive - solving problems across the industry in an innovative manner which saves time, costs and offers a new paradigm.
MDS has been developed, enhanced or matured over a span of 12 years by a strong technology and operations team at UBS. As a System Integration company, Tech Mahindra did not see that as merely an opportunity to offer outsourcing/ offshoring service for cost arbitrage benefits. Instead, we "platformised" the application into a hosted solution and BPaaS offering for our BFSI customers. We expect that as more BFSI clients use this service, the overall cost per client can be lowered even further as the economies of scale start coming into play.
What are the main tech trends in the financial services sector and how is TM tailoring its services keeping those trends in mind?
i) Financial transactions are becoming faster and more connected. Trading now takes place at the speed of light. In the age of "dark pools" and algorithmic trading across borders, time zones and asset classes, the investment strategy formations/ decisions are getting increasingly automated. The correctness of reference data has never been more important to existence of a financial institution.
ii) The transactions are becoming more complicated. Advanced computers and mathematical formulae mean that new permutations - cutting across difference instruments and factoring even weather and political risk - now have to be calculated instantaneously. Faster and easier to access harmonised data is required.
iii) Banks need flexibility to do what they want with their data. One size no longer fits all.
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