Learn how our leading Banking Customer realized their vision of Improving their Data Quality & Compliance with Regulatory Requirements.
- To integrate data from different data sources into one common platform, silos data center.
- To implement data quality checks for the provision of precise data considering the key DQ dimensions like correctness, completeness, integrity, and consistency.
- To implement DG for trust index score, in- return, identify the good data, and rejected data.
- To implement compliance for the fulfillment of regulatory requirements
- Create an MDM implementation to maintain Consumer (individual) and Customer (Business) records.
- Integration of different source data.
- Cleansing the data with given business validation data quality rules.
- Defining the data management strategy to master current and future consumers and customer data.
- Created data governance process as per regulatory policies that will operationalize data governance workflows.
- Created new critical data elements related to customer onboarding as per business requirements.
- Created and customized the data quality monitoring rules and Data Governance process as per the business standards.
- Provided process flow to easily fixing the data quality issues for new and existing bank customers which will increase customer retention thereby growth in bank revenue.
- Generated prescriptive/actionable insights better compliance with policy engine across the organization by enabling to implement of right data policies and controls.
- Supported in Identifying the Unique and robust Customer Reference from multiple sources.
- Reduced the time taken to view the complete customer view with a compilation of multiple source data.
- Key metric information was provided in near real-time to business executives.
- Related operational Dashboard updated.
- Business is found reliable on future data to improve the customer experience.
- Improved business resource optimization.
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