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:
- Legacy systems hindering business performance.
- Duplication of effort and high cost in managing multiple systems with manual data entry.
- Increasing data volume leading to data governance issues.
- Managing and maintaining compliance with growing data privacy and security concerns.
This is where Master Data Management software comes in – a tool that bring 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”.
MDM and reference data management software 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
Although every bank’s MDM strategy is unique, the first place to start is with the anticipated context and scope of your project. Will you start small and eventually increase your MDM use cases for banking? Will your MDM solution need to be global, or in one location? What range of data domains will you need to meet your functional requirements?
The right bank master data management strategy should enable your bank’s efficiency, and connections with customers, third-party vendors, and business partners to improve your performance and business continuity.
2. Establish Your MDM Project Leaders, Goals, and Outcomes
In most banks, top-level executives, such as CEOs, CFOs, COOs, department heads, and various business managers, help drive the overall vision for the data strategy. Data & Analytics, Enterprise Architecture, Applications, and PM teams can help build the applications that provide the most immediate value to the business. An appropriate MDM approach will improve your business outcomes, create operational efficiency, and reduce costs. Be sure you consider projects and teams that serve your current business use cases, and support additional use cases for other projects down the road.
3. Ensure MDM Data Quality Requirements
Ensuring data quality is often the main reason for implementing a Master Data Management (MDM) solution since many banks struggle with legacy systems that don’t integrate.
The right bank master data management strategy enables banks to reduce risk and ensure data quality with complete control over all data, who has access, and under what conditions. With a single software platform for data governance, master data, reference data, data quality, enrichment, and workflows, you can implement data quality best practices across the enterprise.
4. Address Compliance Head On
It is vital that your MDM in banking solution meets current requirements regarding personal data and privacy, yet be flexible enough for future needs. To prevent costly change management programs and embrace intelligent, informed growth and expansion, the right MDM strategy enables you to improve regulatory compliance with industry standards (FDIC, CEBA, FIRREA, IMLA, FATA (Title III), Sarbanes-Oxley Act, FACT, etc.), and reduce legal and IP risk while proactively managing privacy, fraud detection, and enhanced security.
5. Research Deployment Options for Master Data Management in Banking
Do you need a solution installed on-prem, in the cloud, or a hybrid between the two?
Optimizing resources and costs is key. You don’t want to purchase a solution that you can’t support internally for the foreseeable future.
The most effective MDM strategy will enable you to rapidly generate and deploy custom, data-rich apps as your bank’s needs grow, adapting to changing business or technical requirements without disruption.
6. Set Clear Goals for Data Governance in MDM Use Cases in Banking
A single, consolidated 360-view of customers is key to delivering personalized experiences that ensure customer loyalty. A well-defined MDM approach, coupled with enhanced data management systems, provides a comprehensive understanding of the customer, establishing strong partnerships that drive agile and prosperous business outcomes. Associating reference data with hierarchies and classifications also provides strong portfolio management, supports risk reporting and submissions, as provides data for critical trading and investment activities.
Make sure you establish clear goals for data governance to address current issues and look for a data governance platform that offers built-in flexibility as your data governance needs change – for the lifetime of your business.
7. Increase Operational Efficiencies and Reduce TCO
Remaining compliant while meeting competitive demands requires banks to drive innovation while improving internal operational efficiencies.
With an improved MDM strategy, banks can improve business process outcomes and overall agility to manage the ever-changing landscape of regulations, compliance, security, and risk; and reduce time to market for banking products while improving customer experiences and reducing TCO. It will also positively impact business activities like product innovations and launches, mergers and acquisitions, and AI and IoT applications development.
Today’s finance data management software and technologies are agile, adaptable, and easy to deploy.
Start today and see measurable value in just a few weeks.
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