DLP in Banking: Best Software & Practices in 2025

To protect against the rising data threat, banks and financial institutions must implement effective data loss prevention software and strategies tailored to their unique banking sector needs. Here, we list the best DLP software compared with banking and finance-specific criteria, and provide some best practices to help your business protect its confidential data.

1. Leverage DLP software for banking

Banks handle a vast amount of sensitive data, including customer information, transaction records, and financial reports. Comprehensive DLP tools are crucial for monitoring, protecting, and controlling the flow of this data across digital channels. Effective solutions enforce policies that address both customer-facing operations and back-end financial systems.

Here is a list of the top DLP software on the market, compared with banking-specific capabilities:

IP: Intellectual Property

All of the vendors with the mark (*) meet the requirements to support and control these regulations:

PII: Personally Identifiable Information

GDPR: General Data Protection Regulation

PCI DSS: Payment Card Industry Data Security Standard

Kompanion Bank case study¹

Kompanion Bank needed secure data protection without intruding on personal digital space. The task was challenging because the team actively used chats, such as Telegram, for internal communication.

The bank switched to new DLP software with more granular policy control, which proved cost-effective, efficient, and smoothly enhanced Kompanion Bank’s data security capabilities.

2. Educate employees on data security

According to the World Economic Forum, 95% of cyberattacks involve human error.²  Given the sensitive nature of banking information, educating employees on data security is critical. Banks should focus on sector-specific training to mitigate risks such as:

• Assess the current landscape: Tailor training to employee skills and company culture, avoiding one-size-fits-all approaches.
• Emphasize simplicity over complexity: Keep training simple, focusing on clear, actionable guidance without jargon.
• Promote teamwork, not punishment: Foster a supportive environment, reducing fear around human error and incentivizing good practices.
• Support and train remote workers: Include remote employees in training; emphasize MFA, VPNs, and secure third-party software usage.
• Mitigate device-related risks: Educate employees to safeguard corporate devices and recognize threats like phishing.
• Establish and refine incident response plans (IRPs): Create and regularly update IRPs, incorporating detection, containment, and eradication strategies. Our 5-step incident response methodology.
• Evaluate and test training effectiveness: Measure training success, audit adherence, and conduct mock attacks to test team resilience.

Experts briefing on DLP challenges in the banking sector:

3. Implement strict data protection policies for banking operations

Banks must develop and enforce robust data protection policies to secure sensitive information. To do this effectively, they should:

• Monitor data flows: Track the movement of data within and between departments to pinpoint vulnerabilities.
• Implement policies: Develop rules tailored to each department’s unique data usage and risk exposure.
• Regular reviews: Continuously audit and refine policies to adapt to evolving threats.

Monitoring also helps the team identify how data moves within the business and where potential vulnerabilities lie.

Here is our guide on DLP policies.

4. Employ big data analytics for threat detection

Using big data analytics, banks can detect patterns and anomalies indicative of security threats. By analyzing vast amounts of data, banks can identify suspicious activities such as unauthorized access attempts or unusual data transfers, allowing for proactive threat mitigation.

Key practices:

• Real-time monitoring: Implement tools that monitor data activities in real time to detect and respond to threats immediately.
• Automated alerts: Set up systems that automatically alert security teams of potential breaches.
• Regular updates: Continuously update analytics models and train security personnel to address evolving threats.

5. Restrict physical access to sensitive data

In addition to digital security measures, banks should limit physical access to locations where sensitive data is stored. Key areas include:

• Data centers
• Branch offices
• Back-office operations

For these banks should implement:

• Control access: Use biometric authentication, security badges, and monitoring systems to secure data centers and offices.
• Role-Based access controls (RBAC): Limiting access to sensitive data based on job roles and responsibilities and implementing least privilege access to minimize the risk of data breaches.

In digital environments, you can implement Mandatory Access Control (MAC), where the operating system or database strictly enforces access rules, limiting a user’s ability to access sensitive data based on predefined security policies.³

6. Secure cloud storage and file sharing for banking data

With the increasing reliance on cloud services, banks must ensure the security of cloud storage and file-sharing systems used for storing and transferring sensitive financial data. Essential actions include:

• Data encryption: Encrypt all banking data before it is uploaded to the cloud to protect it from unauthorized access.
• Multi-factor authentication (MFA): Enforce MFA for all users accessing cloud storage or file-sharing platforms.
• Secure collaboration platforms: Use platforms that offer end-to-end encryption and comply with industry standards to protect data during collaborative processes.

For more on cloud data loss prevention.

FAQs

Further reading

• Top DLP Pharma Best Practices & Software
• DLP Review: Benchmark Testing of 5 DLP Products

External resources

• 1. Kompanion Bank Case Study | Endpoint Protector.
• 2. The Global Risk Report. World Economic Forum. Accessed: 20/August/2024.
• 3. Implementation of Mandatory Access Control in Distributed Systems | Automatic Control and Computer Sciences . Pleiades Publishing