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Leveraging Master Data Management to Enhance Risk Management in Financial Services

Photo by janilson furtado on Unsplash

Your risk exposure is far worse than you think it is.

By Katie Joll

As corporate finance leaders remain focused on digital transformation as a key priority, high-quality data is a requirement for successful transformation and mitigation of risk.

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Talk to anyone in financial services risk management, compliance, and data management roles, and you’ll hear some common threads. Most agree that digital transformation remains a priority in order to address key risks such as inflation, recession, and talent shortages. In fact, 75% of companies in the financial sector have a major initiative to address digital transformation.

Another common thread is that financial institutions are drowning in a plethora of data, and sometimes it’s poor management of that data that is holding them back from true digital transformation.

Low-quality data is a big issue, estimated to cost the US GDP $3 trillion. In the financial sector, bad data leads to financial, regulatory, and compliance risks. Financial services need to modernize how they manage data to achieve true digital transformation and mitigate risk.

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This is where Master Data Management (MDM) comes in. MDM helps financial services create a collaborative data management approach that provides a single source of truth across business units. Master data refers to domain categories such as customer, product, and assets.

How Master Data Management enhances risk management

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The financial sector is rife with inherent risks. Depending on which segments the institution specializes in, data is used to inform key decisions so that the organization can take a risk management approach to them. For example, consider these scenarios:

  • Client credit decisions. These are always based on data, and poor data can result in a credit assessment that mistakenly either approves or rejects credit.
  • Compliance issues. Compliance takes many shapes and forms in the financial sector, from internal processes to requirements to follow court orders to requirements to ensure that the right people or organizations have received the right disclosures. If we take a bank branch as an example, staff needs to deal with clients and their representatives face-to-face. It’s imperative that they have the right information regarding powers of attorney and other legalities.
  • Regulatory issues. Financial institutions must comply with various regulations, including anti-money laundering laws. They need accurate, up-to-date data on those regulations to remain compliant.

When data is siloed across different departments, it’s easy for mistakes or poor decisions to occur. Perhaps a new client with the potential to be a big one gets denied credit due to poor data, or a bank teller doesn’t know that the person standing in front of them should have been removed from an account.

Master Data Management helps to improve data quality and accuracy by creating a centralized “source of truth.” For example, a MDM system can pull together complete profiles on clients, ensuring that whichever department needs them can access up-to-date information.

MDM can ensure that decisions are made based on the best possible information available. From a client services perspective, this can also help financial institutions provide a better experience and reduce the risk of losing clients. From a risk perspective, it helps them to ensure they’ve done everything possible toward due diligence. 

In terms of regulatory risk, it comes back to the need for all team members to have up-to-date information at their fingertips. MDM can help financial institutions centralize this information and implement processes to ensure compliance – for example, by putting system alerts in place where a regulatory check is needed.

Many large banks must comply with BCBS 239, a set of principles for effective risk data aggregation and reporting. On data architecture and IT infrastructure, BCBS 239 states: “The banks’ data architecture and overall IT infrastructure must ensure permanent and continuous support to the entire set of risk data aggregation resources and reporting practices while still meeting the other established principles.” MDM helps financial institutions have the right data architecture to comply with BCBS 239.

Best practices for implementing MDM for risk management

Risk management and Master Data Management are both critical functions for financial services, although risk isn’t the only function in the organization that MDM can benefit. For the purposes of this particular post, we’re honing in on the risk-MDM relationship and best practices for MDM implementation. Here are some key points:

  1. Define your scope. There are many use cases for MDM in financial services and the risk management function. A move to MDM tends to be a large and ongoing project for most institutions, so careful scope is imperative. A good place to start could be with the most pressing risk concerns impacting the organization’s day-to-day management.
  2. Establish your MDM project leads. Risk impacts every business unit; you’ll need a cross-functional team of business owners, data stewards, and software architects. Stakeholder engagement is critical for successful MDM implementation. With so many business units impacted, you don’t want any remaining siloed.
  3. Create an MDM roadmap that prioritizes your risk management goals. Your roadmap could: assess the current state, define the desired state, find any gaps between the current and desired state, define how MDM needs to improve data management to meet those goals, and prioritize meeting key regulatory and compliance requirements. For example: Basel III, OFAC, FACTA, HMDA, and Dodd-Frank.
  4. Select the right technology stack for MDM. Successful MDM requires the right tools in place. Look at your business cases for MDM and define the must-have features of MDM technology to manage those business cases.

Case studies: Financial services data management

Here are some examples of financial institutions that have improved their risk management practices with the aid of Master Data Management:


Master Data Management can be critical in improving financial institutions’ risk management outcomes. Risk covers anything from decisions about individual clients to overall policies and practices in the organization. Meeting compliance targets and regulatory requirements is crucial, but is often encumbered by poor-quality data.

Financial institutions can reap the benefits of MDM and finance data management software for risk management, including eliminating data silos and creating a single source of truth. MDM helps organizations to better inform their decision-making with quality data. It also helps them to provide a better client experience, helping to reduce the risk of attrition.

The future of MDM will see more capabilities developed for financial services. Key issues such as data security, financial risk, and customer service are being improved over time. Getting started with MDM now will help financial services get ahead of the game.