Improving Data Quality at a Regional Bank | A Case Study
A?regional US bank used OvalEdge to tackle data quality issues that were leading to inaccurate liquidity risk and credit risk predictions, and potential compliance violations.
Client Context
The customer was a mid-sized, US-based bank with nearly five billion dollars in assets. From a services perspective, the bank focused on lending and supported deposits. Consequently, much of the bank's IT infrastructure was centered on risk assessment.
From a business technology perspective, the bank had a series of systems in place to aid the day-to-day running of operations. Beyond these technologies were the critical financial and compliance-related analytics tasks that the bank's analytics team carried out using data funneled through the applications. They included an analysis of:
The bank had a robust technology stack with dedicated tools to support its core analysis and risk mitigation strategy. However, data issues impacted its ability to manage credit and liquidity risk and adhere to the various financial compliance laws that governed it.
Key Pain Points
The bank's data issues affected both business users and analytics teams. For business users, poor data quality was the primary pain point. They could not retrieve high-quality data to carry out accurate credit and liquidity risk assessments, and these data quality issues manifested at various levels.
This issue with data quality had a profound impact on credit risk assessment.
Read the complete case study here -> Improving Data Quality at a Regional Bank