Journal of Economics & Management Research

Financial institutions are using data in a myriad of different ways, from know-your-customer (KYC) compliance to marketing insights and channel optimization, from risk assessment and fraud detection to innovative AI and machine learning initiatives. Data Integrity checks and best practices support data management as both strategic and tactical processes that enable companies to improve compliance, reduce costs, transform their customer relationships, and stay on the leading edge of innovation. It’s all too easy for financial institutions to lose sight of the gaps in their overall data strategy. Poor data quality is one component of this, but lack of context and poor integration are equally to blame for the underperformance of data assets. This research article examines the practical implications of poor data integrity. It explores the benefits of investing in a proactive approach toward improving data integrity checks, along with some real-world examples that illustrate the business value of such an approach.