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Data governance is the framework an organization follows to protect its valuable information and use data effectively. Every industry faces unique challenges in terms of data security and regulatory compliance. This guide can help your organization understand and follow best practices for data governance in banking.
Data governance involves creating policies for your organization’s data processing activities, designing processes to meet internal and external standards, and monitoring compliance. Data governance frameworks for the banking industry cover six main pillars:
Put simply, the definition of data governance in banking covers the entire information lifecycle: payment processing, customer relationship analytics, information storage platforms, and disposal policies.
Banks must ensure that records remain secure, confidential, accurate, and available — 24/7, 365 days a year. As information security and records management requirements get more complex, the need for data governance in banking becomes especially urgent.
Banks handle a huge volume of financial transactions every day. Just in the United States, more than 100,000 credit card transactions occur every minute, nearly 150 million each day, and approximately 4.5 billion a week. Each transaction involves creating digital data points and updating customer records.
The way customers manage their money has changed significantly over the past decade. Many modern consumers prefer banking apps. Over 50 million JPMorgan Chase clients used mobile banking in 2023, a whopping 15% of the United States population.
This shift to mobile payments and digital recordkeeping requires excellent cybersecurity. APIs must comply with the strictest industry standards.
Financial organizations tend to have dozens, hundreds, or even thousands of branches. This organizational structure complicates data security and compliance processes immensely. Without effective data governance, individual branches can make less-than-optimal decisions that threaten the financial well-being of the entire brand.
Unfortunately, data silos are all too common in national and global enterprises. Individual branches and departments can find it difficult or impossible to see data from other locations. This can result in serious mistakes, redundant efforts, and loss of productivity, not to mention increased costs throughout your organization.
During periods of financial turmoil, banks must be able to detect trends and respond quickly. Not only does this help to safeguard bank investment profiles, but it can also minimize the risks from a sudden surge in depositor withdrawals. Having accurate and available data is vital for risk analysis and up-to-date decisions by bank leadership.
On one hand, following a data governance framework in banking can help your organization streamline compliance with banking industry regulations:
The other reason data governance matters is that consumer privacy laws have become more common and complicated. Banks that have branches in the EU or overseas customers must comply with GDPR when processing user data or storing that information in other countries.
In just 10 years, the number of cyberattacks on financial institutions has more than doubled. There were more than 10,000 malicious incidents in 2023 alone. Nearly 20% of all cyberattacks target the banking and insurance industry.
Data security is a central pillar of data governance in banking. Without adequate controls, financial organizations are vulnerable to data breaches, reputational damage, and massive financial losses.
Effective data governance goes beyond general policies. It’s necessary to analyze your organization’s unique risks and challenges. Your framework needs custom solutions that adhere to regulations as efficiently as possible. In other words, your goal is to develop a holistic data management strategy.
Industry and government regulations have an outsized impact on bank operations and data processing. It makes sense to ensure your data governance framework aligns closely with applicable regulations for cybersecurity, privacy, financial disclosures, and risk management. It’s better when compliance is built into your organizational policies instead of tacked on awkwardly afterward.
Similar to the way ships have a detailed command structure — starting with the captain — banks need to assign roles and responsibilities for data governance to work. It should be clear who is responsible for oversight, policy creation, compliance, modification of standards, and other aspects of data processing. Taking an enterprise-level approach to information management is one of the best ways to avoid data silos and cybersecurity vulnerabilities.
Invest in the people and technology needed to bring your information systems into the 21st century. Eliminate conflicting or duplicate policies. Create a centralized repository for organizational policies and processing activities. Validate records for accuracy and completeness.
Wherever possible, automate records creation, validation pipelines, network monitoring, and other processes. This makes compliance more efficient while increasing oversight and lowering the risk of human error or insider threats.
Data governance isn’t limited to past or present information assets. When mapping your data inventory, connect decision-making processes, cybersecurity priorities, and compliance needs with potential information sources. Determine what type of data infrastructure and core elements you need to improve your operations, and ultimately, your bottom line.
Automated compliance tools can strengthen your organization’s data management and cybersecurity posture across the board. Compyl’s powerful features help global banks implement effective data governance and risk management frameworks. Contact us to learn how data governance in banking can enhance your operations.
