Framework of Master Data Management in Banking Using Consolidation and Jaro Winkler Algorithm

Master Data Management (MDM) is a crucial framework for ensuring the consistency, accuracy, and reliability of key data entities within banking systems. In the financial sector, where data from multiple departments and sources is constantly generated and shared, it is vital to maintain a single, unified view of critical data to prevent inconsistencies, inaccuracies, and duplication. This paper introduces a comprehensive design for implementing MDM in banks, utilizing a consolidation approach integrated with the Jaro-Winkler similarity algorithm. The consolidation approach allows the seamless integration of disparate data sources across various departments, creating a unified and centralized data repository. This is essential for maintaining a comprehensive and reliable view of data assets, thereby improving decision-making and operational efficiency. The inclusion of the Jaro-Winkler algorithm enhances data matching capabilities by identifying and resolving duplicates or near-duplicate records through name and text similarity comparisons, an essential feature given the complex nature of customer and transactional data in banking. By addressing these challenges, the proposed MDM solution significantly improves data quality, reduces redundancy, and ensures that information is accurate and accessible across all levels of the organization. This system provides a scalable, robust, and efficient data management infrastructure, crucial for meeting regulatory compliance requirements, enhancing customer service, and optimizing operational processes. The methodology presented in this paper demonstrates an effective and structured approach for large-scale data integration and verification, offering a reliable solution for managing vast amounts of data in the banking sector.