Data is and will always remain the utmost priority for financial institutions and banks as it is the key to everything — making more informed decisions, elevating customer experience/service, innovation, and successful digital transformation. While data stands at the heart of the financial services industry (FSI), they are still struggling to govern and manage their data.
As discussed in my previous article, building a strong data governance model helps transform your existing data infrastructure into an actionable, secure, and reusable architecture. Now let’s understand the value and gravity of data governance across financial services and how to improve it.
What is Data Governance?
Governance of enterprise data is defined as the process of establishing and managing the availability, accessibility, integrity, and safeguarding of data in the underlying systems. It comprises roles, policies, processes, metrics, and internal standards to ensure the controlled, efficient, and effective usage of data across the organization, enabling them to achieve the end goals.
A robust and well-designed data governance program not only establishes organization-wide processes, roles, and responsibilities of respective stakeholders but also ensures data quality, consistency, and security such that business-critical information is not misused in any form.
However, don’t confuse the term “data governance” with the concept of “data management,” as it is a core element of data management. Data management is the backbone of the entire lifecycle of information, connecting all the other segments of data disciplines.
Why is Data Governance so Important for the Banking Industry?
Compliance has been and still continues to be one of the top challenges across the entire banking industry as the compliance policies and regulatory requirements are ever-evolving.
For example, banks in Australia must adhere to the Australian Prudential Regulation Authority (APRA) standards and guidelines, such as the Australian financial services license (AFSL), quantifying compliance risk, measuring credit risk, Data Collection Act, etc., to carry on their “banking business.”
The financial services industry, including insurance companies, mortgage firms, banks, and credit card companies, has witnessed significant data overload and an exponential increase in data leaks and breaches over the last few years.
As a result, financial institutions stand at a greater risk of being compromised if the governance of their enterprise data is not done right.
Read more on how Complete Credit Solutions implemented a cloud-based data foundation to overcome compliance requirements in the financial industry
Benefits of Implementing A Data Governance Model
The following are some of the key benefits of putting the concept of data governance in practice:
1) Driving Innovation Through Data Quality
Accelerated digital transformation and advancing technologies (e.g., cloud solutions) have liberated data and enabled financial institutions to put “innovation” in focus.
Gartner predicts that “2022 will require CIOs to enhance key digital capabilities in innovative ways to address changing customer needs, values, and economic conditions.”
Banks are prioritizing customer experience and transforming their ways to:
- better connect with consumers,
- launch new offers & products,
- upgrade how they function, or
- expand its business by opening up new branches or acquiring another bank
Such educated decisions cannot be made in silos and require the leadership team, including the chief financial officer (CFO), and chief data officer (CDO), to collect/access the right sets of data and embrace innovation in their decision-making strategy. Enhancing the quality and value of data has now become the new imperative.
Effective data governance plans – (i) ensure that your enterprise data meets all the quality standards; (ii) help eliminate obsolete, incorrect, or duplicate data; (iii) and empower you to deliver and use only trustworthy, reliable data.
2) Establishment of Policies and Processes
Incorporating a well-defined data governance model helps build a culture of data privacy, making everyone feel responsible for how the data is accessed, used, and managed. With data governance comes a set of procedures, commitments, and responsibilities toward data quality, security, and management across the business.
It illustrates and specifies who is eligible to take what action, on what kind of data, in what scenarios or circumstances, and using what techniques. Adopting a continuous governance cycle enables you to monitor your current policies, enforce new ones, or upgrade the legacy processes for streamlined data management and higher data quality.
3) Achieving Regulatory Data Compliance
With compliance policies changing constantly and new regulatory requirements emerging, the implementation of solid data management and governance procedures is the key to achieving regulatory, legal, and industry compliance. It also helps you properly use and manage personally identifiable information (PII), confidential data, and data retention. Usually, banks and financial services companies have to retain information for 7 to 10 years for audits and quality control.
Therefore, putting a data governance program at the center of your financial business not only reduces compliance risks but also ensures that your internal policies are compliant with external regulations.
More importantly, regulatory administration representatives or auditors are more concerned about how the data is generated and inspect the processes used to manage and protect that data instead of looking at the data stored or collected.
4) Maintaining Data Security
Data security is a core component of a data governance program as the most critical and sensitive data of an organization cannot be 100% secure if there are no governance policies in place to manage new data privacy regulations.
Banks and financial institutions need to design and implement a strong data governance model with a risk-based approach for:
- strengthening their existing cybersecurity measures,
- safeguarding data from cybercriminals in the ever-evolving threat landscape, and
- achieving compliance with data protection regulations and laws.
Financial services companies should leverage cloud security solutions, such as Azure Active Directory (Azure AD) for a customer identity and access management and Azure role-based access control (Azure RBAC) to fine-grain and manage access to resources.
Final Words: Implementing Azure Purview for Unified Data Governance
You need a robust data governance solution to govern and manage your entire data ecosystem, including your software-as-a-service (SaaS), multi-cloud, and on-premise data. Azure Purview enables you to establish the foundation of effective data governance. Besides, Azure Purview Data Catalog helps your data consumers easily discover reliable, valuable data.
Therefore, with automated data discovery, classification of sensitive data, and end-to-end data lineage tracking & visualization, you can build a holistic, up-to-date map of your current data landscape.
Get started with Azure Purview for comprehensive data governance.
- Enterprise Governance on Data Lake with Unity Catalog & Databricks Implementation with R Jobs Migration Use Case - July 20, 2022
- Data-Driven recognised as the 2022 Microsoft Partner of the Year Finalist - July 6, 2022
- Azure Governance — The Importance of Azure Role-Based Access Control (RBAC) - May 25, 2022