Best Practices For Data Governance In The Financial Sector

People create over 2.5 billion quintillion bytes of data every day. Do banks have measures in place to leverage this data to make their services more efficient? More importantly, do they have what it takes to keep customer data safe?

In today’s data-driven economic landscape, any financial institution that wants to provide a good customer experience and maintain a competitive edge must collect and use customer data. However, most of the data that financial institutions collect and manage is highly sensitive – name and address, social security numbers, financial status, transactions, assets, and so on. Managing such data requires a well-thought-out data governance framework.

Good data governance helps organizations ensure the privacy and security of customer data. According to the 2020 Experian Global Data Management Report, a good data governance strategy can also help institutions become more efficient, boost customer trust, improve customer satisfaction, enhance decision-making, and increase cost savings.

Source: Experian Global Data Management Report 2020

Despite its huge benefits, prioritizing data governance is not an easy undertaking. Below, we’ll explore some essential best practices for financial institutions that want to design and implement an effective data governance framework.

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Think Big, Start Small

One mistake many financial institutions make is huge investments in technology without setting a proper foundation. Unfortunately, this often fails because a solid data governance framework is not just about technology. Good data governance involves a seamless interaction between people, processes, and technology.

To build a practical data governance framework, banks and financial institutions need to focus on building capacity in each of people, process, and technology individually and then let these factors build upon each other. Without the right people, the right process and technology mean little. Financial institutions should start by educating and training their people on the importance of proper data governance. Sometimes, this might even mean hiring data experts.

Once they have the right people, they can then focus on building processes that allow them to collect the correct data and properly manage it. For instance, you can switch from manual processes to services provided through apps, which allow you to collect and track data about all customer transactions.

Finally, financial institutions can invest in the right technology to help automate processes and make data management more effective and efficient. For instance, they can invest in role-based access control (RBAC) to control how different people access customer data. By building capacity for each of these components individually and then bringing them all together, they eventually end up with a well-rounded data governance framework.

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Understand Regulations and Compliance

A proper data governance framework doesn’t just benefit financial institutions. It also protects their customers. Considering the sensitive nature of the data financial institutions collect a data breach can have grave consequences for customers. Therefore, when designing a data governance framework, banks must be aware of all the crucial regulations governing data management in the financial services sector.

Some of the most important regulations financial institutions need to be compliant with include:

  • General Data Protection Regulation (GDPR): Any institutions or businesses that collect or process data from EU citizens need to be GDPR compliant. This applies even to organizations outside the EU. A PwC survey reports that GDPR compliance is a top priority for 92% of US organizations. GDPR non-compliance can lead to penalties of up to $23 million or 4% of an institution’s annual turnover, whichever is higher.
  • ISO/IEC 27001: This is an internationally recognized set of policies to protect information systems and improve data security. While this is not mandatory, it is highly recommended for financial institutions since it provides an advanced framework for protecting sensitive data.
  • Payment Card Industry Data Security Standards (PCI DSS): This is a mandatory regulation for any organization that collects and processes customer credit card data. PCI DSS aims to protect customer information and reduce credit card fraud. Failure to comply with this regulation can result in penalties of up to $100,000 per month.

There are several other regulations that might apply to your institution depending on the nature of your business and it is important to be conversant with all of them. In addition, it is advisable to carry out regular self-audits of your data governance framework to ensure that you’re always compliant with all necessary regulations.

Build a Business Case for Data Governance

Many financial institutions leave the design and implementation of the data governance framework to the Chief Information Officer (CIO). However, if you want to successfully implement the framework throughout the entire organization, you need the buy-in and support of not only the CIO, but also all C-Suite executives.

There is one problem, however. It is highly common for C-suite decision makers to overlook do not care much about data during decision-making cycles. According to the CMMI Institute, over half of C-Level executives have disregarded the importance of data because they could not understand it.

The key here is to build a business case for your data governance framework. Show how implementing the framework will lead to tangible benefits for the business. These benefits could be increased revenue, higher productivity, increased customer retention, better customer experience, and so on. When executives know how exactly a data governance framework influences the business, they are more likely to spearhead its implementation.

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Pin Down Distinct Use Cases

Most financial institutions collect user data, but most don’t have a clear use case for this data. According to Webinarcare, 73% of the data organizations collect never gets utilized for any strategic purposes. In other words, organizations are investing resources into collecting data they don’t end up using.

When developing a data governance framework, you need to consider the specific use case for the data you intend to collect. For instance, if you collect data about your customers’ transactions, an example of a distinct use case would be using the data to study consumer behavior and flag potentially fraudulent transactions. Another example is using this data to recommend products tailored to a specific customer’s needs.

The point here is that you need to get very specific. Simply saying you’ll use the data to improve customer experience is not a use case, and it’s highly likely you won’t achieve this goal. Instead, drill it down and describe how exactly you’ll improve customer experience using the specific data.

Improve Data Capabilities

For your data governance strategy to be effective, you must ensure that your financial institution has in place all the capabilities and processes you need to get the most out of the data you’re collecting.

For example, customer data is usually collected from multiple touchpoints, such as your mobile banking app, your online customer service portal, and your physical service counters in banking halls.

To use this data to improve customer experience across the entire customer journey map, you need to share it with multiple departments. However, this won’t be possible if different departments operate in silos. Therefore, improving capabilities, in this case, would involve breaking down the silos and enhancing collaboration between departments.

Invest in Suitable Data Governance Technology

Acquiring the right technology is crucial to an effective data governance framework because it makes it easier for financial institutions to collect, manage, and process customer data.

To manage the highly sensitive data collected by financial institutions, a reliable data governance platform should have the following features:

  • Automated data discovery, capturing, and cataloging
  • Providing temporary access to sensitive data, to limit risk of data exposure
  • Automated identification, classification, and tagging of sensitive data
  • Data and metadata management
  • Data access control to keep financial data safe and secure
  • Dynamic data masking
  • Clean and intuitive data visualization
  • Support for data democratization and self-service
  • Workflow automation
  • Data auditing and reporting
  • Compatibility with existing business systems.

Regularly Track Key Metrics

As the popular phrase goes: if you don’t measure it, you can’t manage it. Once you implement your data governance framework, the only way to know if it’s working or not is to track key metrics regularly. This lets you know whether you’re headed in the right direction and allows you to identify areas that need improvement.

Some of the key metrics that you can track to gauge the success of your data governance framework include:

  • Data quality and accuracy scores
  • Changes in data rectification costs
  • Adherence to data governance processes and standards
  • Increase in data literacy
  • Business value gained from the data governance initiative.

Data Governance is a Marathon

Finally, you must understand that data governance isn’t a one-time project with a definite conclusion. As the financial sector keeps evolving, you’ll probably change the amount and type of data you collect, which could, in turn, call for a change in your data governance framework. Therefore, you’ll never get to a point where your data governance framework is complete.

Instead, you should treat it as a live framework and regularly review your data, track metrics, collect feedback, and then use those insights to update the framework constantly.

Develop and Implement a Successful Data Governance Program with Stefanini

Every business in the financial sector needs to implement a proper data governance program. This will help make your business more efficient and, at the same time, protect your customers’ data from ever-increasing cases of data breaches.

Developing and implementing a data governance framework is an immense undertaking, but applying the best practices we’ve shared here will help you get there.

Let Stefanini serve as your partner in building successful Data Governance program.

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