Security & Compliance

Securing Borrower Data: Best Practices for Nonbank Commercial Lenders

January 23, 2025

7 minutes

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Cyberattacks, data breaches, and hackers threaten every industry and individual. However, for nonbank lenders dealing with sensitive client data, these pose potentially detrimental risks. To protect consumers from the consequences of data leaks, the FTC implemented new requirements in 2024 enhancing disclosure requirements for non-banking financial institutions to report data breaches and other cybersecurity events. With emerging technology making hackers even more sophisticated, and the proliferation of devices, networks, and platforms creating even more ways to access sensitive data, the responsibility to safeguard sensitive borrower data has grown more complex. Protecting personal and financial information isn’t just about compliance—it’s about maintaining customer trust.

What can nonbank commercial lenders do to keep trust and security front and center?

Why Data Security Matters in Nonbank Commercial Lending

Nonbank lenders handle vast amounts of sensitive data, from personal identification details to credit histories and financial statements. This data is essential for assessing creditworthiness, managing portfolio risk, and delivering streamlined client support. However, it also makes lenders attractive targets for cyberattacks and data breaches.

Beyond external threats, the consequences of data mismanagement or regulatory non-compliance can also be severe, leading to hefty fines, reputational damage, and loss of client trust. In today’s lending environment, robust data security isn’t optional—it’s foundational.

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Challenges Nonbank Lenders Face in Protecting Client Data

Sophisticated Cyber Threats

Hackers employ everything from advanced ransomware techniques to social engineering and phishing to obtain sensitive login information and infiltrate systems. Financial institutions, including nonbank lenders, are prime targets due to the high value and sensitivity of their data.

Complex Regulatory Frameworks

Nonbank lenders must navigate a patchwork of regional and international regulations such as AML (anti-money laundering) and KYC (know your customer) compliance, and industry-specific data protection laws. These regulations require careful data handling, storage, and reporting practices to remain compliant.

Vendor-Dependent Risks

Outsourcing or co-sourcing operations to third-party vendors for loan processing, analytics, or cloud storage introduces additional vulnerabilities. A breach at the vendor level can expose borrower data even if the lender’s systems are secure.

Balancing Innovation and Security

Commercial nonbank lenders face significant challenges in balancing innovation (e.g., adopting advanced technologies to streamline lending processes) with security (e.g., protecting sensitive data and ensuring compliance). This balancing act becomes even more critical due to the increasing reliance on digital platforms, big data, and AI in lending. For example, adopting new generative AI models for underwriting might speed up decision-making, but it may also potentially introduce noncompliance risks with privacy laws if data is not properly anonymized.

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Strategies to Maintain Data Security in Nonbank Lending

1. Choose Secure and Compliant Commercial Lending Software

Investing in automated, digital lending platforms is essential, but security features must be a priority. Look for software that offers data encryption at rest and in transit to provide unauthorized data access. Comprehensive role-based access security provides permissions that ensure only authorized users access sensitive borrower data, often down to the field-security level. And, enhanced compliance tools that provide automated regulatory checks and reporting support can simplify compliance management and reduce manual, human errors.

2. Strengthen Cybersecurity Measures

Building a robust cybersecurity framework protects systems from potential threats. Essential measures include Multi-Factor Authentication (MFA) which adds an extra layer of protection beyond password inputs. With regular penetration testing, simulated cyberattacks help identify system vulnerabilities proactively, before there’s an active threat. And threat detection tools leveraging AI-powered solutions help monitor and block suspicious activity in real-time.

3. Vet and Monitor Third-Party Vendors

Working with third-party vendors can enhance efficiency, but it also introduces shared risks. To mitigate these risks, conduct detailed security audits of outsourcing and co-sourcing vendors before entering into an agreement. Ensure all vendors comply with the same level of data protection standards and protocols as in-house employees. And periodically reassess vendor security practices via the same cybersecurity measures used for in-house platforms to address evolving risks.

4. Automate Compliance Management

Regulatory compliance is a complex and time-consuming task, but digital commercial loan management platforms with integrated compliance features can help. Find a platform that helps ensure compliance with data privacy laws while enabling the adoption of new technologies like generative AI. Automate all documentation and audit trails via a secure platform to assist with regulatory reporting and compliance.

5. Foster a Culture of Security

Data security is everyone’s responsibility and requires a company-wide commitment. To build a security-first culture, conduct regular training for employees on cybersecurity best practices. Establish clear protocols for data access, storage, and sharing, and ensure protocols are supported by a platform’s built-in role-based access security and data storage permissions.

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The Role of Technology in Protecting Borrower Data

Commercial loan management platforms can help protect data privacy and security with built-in tools and resources.

Artificial Intelligence for Risk Monitoring

AI-powered systems can analyze massive datasets and detect patterns indicative of cyber threats. They can identify anomalies like unusual system access attempts or large data transfers, flagging potential breaches before they escalate.

Cloud Security Enhancements

Cloud-based platforms offer advanced security features, including end-to-end encryption, dynamic threat response systems, and tools for managing encryption keys. These capabilities ensure secure storage and processing of borrower data while enabling scalability.

Automated Risk Assessments

Data security tools integrated with commercial lending software can continuously evaluate the risk profile of borrowers and portfolios. This not only helps with operational efficiency but also ensures that data remains protected during assessments.

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How Nonbank Lenders Can Balance Innovation and Security

To ensure borrower data is secure, nonbank lenders must adopt a multi-faceted approach that combines technology, compliance, and cultural shifts. By investing in secure commercial lending software, enhancing cybersecurity frameworks, and fostering internal accountability, lenders can protect sensitive data while driving operational success.

  1. Adopt a Security-by-Design Approach: Incorporate security measures during the development phase of new technologies rather than retrofitting them later.
  2. Invest in Cybersecurity Tools: Use advanced threat detection systems, encryption, and secure APIs to protect data without sacrificing speed or user experience.
  3. Prioritize Transparency: Clearly communicate to borrowers how their data is used and protected to build trust.
  4. Implement Continuous Monitoring: Regularly update systems and monitor for potential vulnerabilities or breaches.
  5. Leverage Technology: Use tools that help ensure compliance with data privacy laws while allowing for innovation.
  6. Train Employees: Regularly educate employees on cybersecurity best practices and data handling procedures.

The future of nonbank lending lies in balancing innovation with responsibility. As the industry grows more competitive, maintaining borrower trust through robust data security practices will remain a key differentiator.

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