Financial services companies have a wealth of customer data distributed across many systems, lines of businesses, and national boundaries. Unifying customer data to support growth, cost-savings, and regulatory requirements is imperative.
For the past 15 years, IT teams have been applying master data management (MDM) technologies in an attempt to unify customer data.
In this paper, we explain:
- Why traditional MDM systems do not scale to meet the needs of large, multinational financial companies
- A new MDM reference architecture that applies machine learning algorithms to the problem
- How this new MDM approach reduces IT overhead and decreases time to master new source systems