Elevating Banking: Advanced Analytics for Superior Data Quality and Efficiency
Case Studies
Challenges & Solutions
Technical Environment
Results
Executive Summary
Client
Insurance Management Group
Industry
Banking, Financial Services, & Insurance
Business Problem
The banking administration aims to enhance business performance through improved customer retention and targeted sales by leveraging existing data assets with analytical insights. The bank seeks to implement a tool designed to assess and maintain the quality of data, ensuring its completeness, consistency, timeliness, and accuracy.
Outcome
- Improved Data Quality: Enhanced data completeness, consistency, and accuracy through automated quality management.
- Effective Data Integration: Enabled comprehensive data validation and integration from multiple sources, supporting robust model implementation.
- Advanced Insights: Provided deeper insights and analytics with advanced models and big data capabilities.
- Streamlined Reporting: Enhanced reporting efficiency and effectiveness using the SAS-based analytics platform.
Challenges
- Insufficient information was provided in the reports.
- Customer retention KPIs were poor.
- Packaged products did not reach the appropriate customers.
- Product design was time-consuming.
- Optimal cash loading in ATM machines was hindered by insufficient KPIs.
- Cash blockages occurred due to excessive cash loading in ATMs.
- Designing customer-specific products was not feasible.
- Matching customers to products was inefficient, leading to poor targeting.
Solutions
- Developed a reporting and analytics platform using SAS tools.
- Performed requirement assessments.
- Implemented a tool to aid in the quality assessment and maintenance of data completeness, consistency, timeliness, and accuracy.
- Designed a solution to connect to leading databases, identify, profile, and validate data by cross-relating identified sources to support model implementation.
- Built analytical models on training data and conducted advanced analytics in areas such as big data.
Technical Environment
- SAS data management with standard data surveyor for SAP
- SAS visual analytics (VA)
- SAS enterprise miner
- SAS enterprise guide
- 30+ analytical dashboards
