Data Security for Financial Services & Insurance

Financial services and fintech firms trust Immuta as a core component of their data control environments, so they can safely gain business insights and value from even their most sensitive data.


Trusted by Leading Financial Services & Insurance Companies

Data Access Control

Empower data teams to securely discover, share, and collaborate on data across applications. Ensure data scientists and data analysts have the right level of access to the right data, without unintentional data leaks.

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Fine-Grained Auditing & Reporting

Data teams can gather real-time insights with detailed auditable reports to prove compliant data use. Provide automated, policy-based table-, column-, row-, and cell-level access to data.

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Dynamic Data Masking

Immuta’s plain language policy builder removes the guesswork from data protection techniques such as dynamic data masking and differential privacy, thereby increasing collaboration and data stewardship between data and regulatory compliance teams.

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“This strategic decision is enabling us to drive business innovation, improve data-driven decision making, reduce costs, and enhance the customer experience, while mitigating risk and adhering to compliance and regulatory standards.”

Vineeth Menon Head of Data Lake Engineering, Swedbank

Typical Financial Industry Use Cases

Immuta is the modern data access control solution for cloud-based and on-premises data ecosystems. Automated data access and privacy controls help reduce risk and enable more data use across platforms, so you can compete with data.

Banking & Payments

Enable financial data for use in applications such as

  • Customer 360
  • Trading Analytics
Wealth & Asset Management

Leverage troves of financial nuggets for predictive analytics

  • Customer Churn
  • Product Recommendation
  • Risk Management

Reduce financial risk and enable personalize service

  • Fraudulent Claims
  • Claims Optimization
  • Personalized Offers
Data Sharing

Access control for sharing data with third parties, such as

  • Credit Agencies
  • Financial Aggregators
  • Personalized Financial Wellness

Frequently Asked Questions

What are the best practices for data security in the banking industry?

Best practices for data security in the banking industry include:
-Implementing an identity access management system that verifies user identities and authorizations
-Creating a data security framework that enables scalable policy implementation and advanced privacy controls
-Designating a leadership role, such as a chief information security officer (CISO) to oversee data security
-Dynamically restricting access to data based on the principle of least privilege
-Performing regular risk assessments and audits on data use

What are the most prominent financial services compliance regulations?

The most prominent financial services compliance regulations include General Data Protection Regulation (GDPR), The Payment Card Industry Data Security Standard (PCI DSS), The Sarbanes-Oxley Act (SOX), The Gramm-Leach-Bliley Act (GLBA), and The Payment Services Directive (PSD2).

What are sensitive data examples in financial services?

Within the financial services industry, sensitive data can include names, addresses, and social security numbers, as well as credit card, debit card, and bank account numbers. Each of these is considered sensitive because it can directly or indirectly identify an individual and, in the wrong hands, could be used to compromise that individual’s well-being, such as through fraudulent use of funds.

Who is responsible for data governance in banking?

In the banking industry, a variety of stakeholders across functions are responsible for data governance. However, the data governance standards and objectives should come from the individual(s) accountable for data security. Depending on the organization, this may be the chief data officer (CDO) or data platform owner. The data platform owner and/or data architect is responsible for ensuring those standards are reflected in the data security and access control strategy, which is implemented by the data engineering team. Finally, governance, risk, and compliance (GRC) stakeholders are responsible for verifying that the data governance strategy and tactics are compliant and working as intended, so as to avoid potential leaks, breaches, or penalties.

What do you need to achieve financial data compliance?

To achieve financial data compliance, you must build guidelines from relevant regulations, such as PCI DSS and GDPR, into all data practices; implement data encryption or tokenization to limit who can access regulated information, for both storage and transmission; ensure data can be backed up or retrieved in the event of a data loss or system failure; appoint and involve compliance officers with industry knowledge; and regularly monitor and audit data use to prove compliance.

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