Case study > We Executed Strategic Enterprise Data Program for One of the Largest Investments Company > We Enabled a Large Global Bank to Re-imagine its Billing Program

We Enabled a Large Global Bank to Re-imagine its Billing Program

Data Solutions Case Study Largest Investments Company BNYM 1.3


The client was in search of a strategic partner to help them in the billing re-imagination initiative. This included: 

  • To rebuild the complete billing process focusing on the client experience, foundational data builds, operating model optimization & revenue integrity for various LoBs in the bank.
  • To migrate multiple billing platforms and their respective sources data and bring them over to the new billing platform using master data management & enterprise data lake architecture which will strengthen the integrity of data.


  • Worked with the chief data office (CDO) & billing team (RBE) to understand the future state vision, order of priority, and data requirements.
  • Conducted workshops with different LOBs operation teams and data owners to understand and document the underlying data, systems, controls, and various processes & procedures.
  • Scanned the billing data to identify data anomalies & possible attributes leading to revenue leakage.
  • Identified manual activities involved as part of the billing process & identified ways to perform smart automation.
  • Re-imagined the operating model to meet CDO & RBE requirements.
  • Presented the artifacts to CDO & RBE teams to plan the next steps. 


  • Invoice Facilitator (IF) Identification: Identified appropriate IF through data standardization and fuzzy match from across 50M + parties.
  • Address Standardization: Using Spatial and address parsing tools, parsed, de-duped, and standardized invoice addresses into ISO 20022 format.
  • Billing UDT migration: Automated several manual UDTs into ETL pipelines to reduce errors.


  • Helped the client in optimizing their operating model across 19+ LOBs.
  • Helped reduce aged debt from 25% to 8%. 


  • Defined and codified business rules/transformation/ standardization rules.
  • Built dashboards and reports on underlying data quality & usability, data usage, data hydration, etc.

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