Master Data Management in Banking: 7 best practices

By Scott Moore, Director of Presales, Semarchy

With the growing number of interactions, observations, and regulations that banking enterprises manage through various data acquisition points, it is critical to govern these core data elements in an agile and measurable environment for a single version of the truth. In other words, strong Master Data Management in banking is crucial to the industry’s success. 

Current challenges

Data management in banking involves intricate processes dealing with diverse datasets and applying complex business rules. This situation compels banks to continually collate and retrieve vast volumes of past data, traversing a range of structured and unstructured formats. Financial institutions also utilize external data sources for credit scoring and marketing purposes. 

Some of the most significant banking data management challenges include: 

1. Legacy systems hindering business performance.
2. Duplication of effort and high cost in managing multiple systems with manual data entry.
3. Increasing data volume leading to data governance issues.
4. Managing and maintaining compliance with growing data privacy and security concerns.

This is where Master Data Management software comes in – a tool that brings together information across different applications to manage, leverage, and integrate across the enterprise, without the burden and expense of managing multiple, siloed systems. MDM software creates and oversees master data as the organization’s system of record. It guarantees a unified version of information across all departments, often referred to as the “golden record”.  

Master and reference data lie at the core of every mission-critical banking activity. Transactional systems demand consistent information, analytics rely on accurate dimensions and hierarchies, and compliance efforts need dependable data. However, selecting a solution that specifically addresses MDM in banking use cases that will fit the scope, context, and unique business requirements can be challenging. 

Here are some best practices when planning your MDM use cases and implementation strategies for banking: 

1. Define context and scope: Master Data Management in banking

2. Establish your MDM project leaders, goals, and outcomes 

3. Ensure MDM data quality requirements 

4. Address compliance head on

5. Research deployment options for Master Data Management in banking 

6. Set clear goals for data governance in MDM use cases in banking

7. Increase operational efficiencies and reduce TCO 

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What are your data challenges? 

The Semarchy Unified Data Platform is your integrated data management platform. It’s the one-stop shop for business-centric data management, powerful data integration, and intelligent data governance. With Semarchy, any-sized business can build trust in a single source of truth. 

Want to learn more? Contact us today for a demo.