Experiment with Confidence: Security tips for incorporating AI into regulated payments

In the evolving realm of Financial Payments, the integration of artificial intelligence (AI) offers unparalleled efficiency, yet it also ushers in an array of intricate risks. As Chief Information Security Officer (CISO), my commitment lies in fostering a comprehensive approach to risk management—one that blends the specific requirements mandated by regulatory bodies  (NYDFS Part 500 and PCI). By synergizing these financial regulatory frameworks with the NIST AI Risk Management Framework, organizations can skillfully navigate the AI landscape while upholding data integrity and security.

Unpacking AI Risks in Financial Payments: From a Regulatory Perspective

  1. Data Governance (NYDFS Part 500): NYDFS Part 500 mandates robust data governance practices, including data encryption, access controls, and incident response planning. AI integration amplifies data concerns, making it critical to secure AI-driven financial transactions while complying with NYDFS data protection requirements.
  2. Payment Card Industry Data Security Standard (PCI DSS): PCI DSS enforces stringent security controls for payment card data. As AI influences payment processing, organizations must ensure AI systems handling cardholder data adhere to PCI requirements, maintaining data confidentiality and integrity.
  3. Data Bias and Fairness: The NYDFS and PCI frameworks necessitate unbiased decision-making and fairness. AI algorithms trained on biased data could infringe on these principles, leading to disparate treatment and regulatory non-compliance.
  4. Adversarial Attacks in Financial Transactions: Both NYDFS and PCI emphasize securing customer data. Adversarial attacks exploiting AI vulnerabilities can lead to unauthorized access to sensitive payment information, breaching NYDFS and PCI compliance.

A Unified Approach: NIST AI Risk Management, NYDFS Part 500, and PCI

  1. Precise System Categorization: Begin by classifying AI systems based on their impact and role in financial operations. Align these classifications with applicable data categories and data handling requirements.
  2. Holistic Risk Assessment: Evaluate AI-associated risks through the lenses of NIST, NYDFS, and PCI. Consider data security, model vulnerabilities, fairness, and operational stability in tandem.
  3. Strategic Risk Mitigation: Deploy tailored controls that satisfy NIST, NYDFS, and PCI mandates. Encrypt AI-related data, institute access controls, and monitor for both regulatory compliance and AI vulnerabilities.
  4. Integrated Monitoring and Evaluation: Employ AI-driven monitoring tools that consider the intricacies of NYDFS and PCI requirements to swiftly respond to any anomalies that threaten compliance or data security.
  5. Transparent Documentation and Communication: Document risk assessment findings, mitigation strategies, and compliance efforts according to NYDFS and PCI guidelines. Transparent communication that aligns with regulatory expectations ensures inline compliance requirements.
  6. Adaptation and Collaboration: Foster a collaborative environment where AI development teams, compliance officers, and data security experts regularly convene to review and discuss the evolving AI landscape and regulatory changes. Schedule periodic reviews to update risk management practices, ensuring that they remain in sync with the dynamic nature of AI technology and compliance requirements.

We should embrace this transformative “tool”, much much like we have embraced previous tools that have helped businesses become more productive. Yet, let us not forget the value of vigilant oversight and thoughtful controls. And in fact, this exact article you are reading now was produced with the assistance of Generative AI (ChatGPT), coupled with human curation, has allowed us to produce this content in a relatively short period of time – freeing time to work on higher-priority items within the business. The strides in productivity are undeniably transformative, showcasing the potency of AI-powered capabilities. Nevertheless, these gains can not be without (at least not at this point in time) thorough review and validation.

In conclusion, the convergence of AI and regulatory compliance (NYDFS Part 500 and PCI) presents both opportunities and complexities in the Financial Payments sector. Security Professionals must navigate these challenges adeptly to safeguard financial transactions while adhering to regulatory mandates. By combining the principles of AI specific security frameworks, such as the NIST AI Risk Management Framework, with the related financial industry policies of the NYDFS and PCI, organizations can establish a secure, compliant, and innovative environment that sustains the integrity of financial operations in an AI-driven era.

-Andy Seul, Chief Information Security Officer @ PTI

273 239 Soo Hea Hopkins
Start Typing
Privacy Preferences

When you visit our website, it may store information through your browser from specific services, usually in the form of cookies. Here you can change your Privacy preferences. It is worth noting that blocking some types of cookies may impact your experience on our website and the services we are able to offer.

Our website uses cookies, mainly from 3rd party services. Define your Privacy Preferences and/or agree to our use of cookies.