Financial Services Data Modeling

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Financial Services Data Modeling

Data modeling is perhaps the single most important factor that affects the performance of financial services and analytics tools.

Having a good data model solves many of the fundamental business problems, such as:

  • Query response: With the right data model, query response becomes faster even when multiple business domains are interrelated.
  • Better analytics: Developing and deploying flexible analytics tools becomes easy. This has lasting benefits in terms of market visibility, customer insight, etc.
  • Low maintenance costs: Data complexity is reduced, which brings down costs associated with maintenance.
  • Data accuracy: The data maintained by the company becomes accurate and problems related to redundancy are eliminated.
  • Compliance: A flexible data model makes it easy to adapt the system to changing regulatory requirements easily.

An important consideration is whether businesses should develop specific data models according to their functions or aim at a universal data model. While the immediate answer lies in business requirements, experience says that most financial companies quickly outgrow their initial purposes and encompass an umbrella of offerings.

As such, the “Party and Party-roles” data model—which is used widely in financial services—should be replaced by a universal data model capable of handling accounts, loans, agreements and products, etc. One disadvantage of using a universal model is that it becomes difficult to enforce business rules on the roles and entities, which might introduce inconsistencies in data management if not used carefully.

Ramco Banking Analytics relies on its Universal Database (UDB), a prebuilt data model with a combination of meticulously organized dimensions and measures, serving as the data mart for analytics. Due to its star schema design, end users can drill through from Aggregated Report metric to fine granular data (up to account level) in just a few clicks.

What more, the UDB can serve as the Common Data Repository (CDR) as specified by Reserve Bank of India and hence, assist banks in meeting the Regulatory and Governance requirements.