Vendor Communication Risk Assessment

☢️Manage Third-Party AI Risks Before They Become Your Problem☢️ AI systems are rarely built in isolation as they rely on pre-trained models, third-party datasets, APIs, and open-source libraries. Each of these dependencies introduces risks: security vulnerabilities, regulatory liabilities, and bias issues that can cascade into business and compliance failures. You must move beyond blind trust in AI vendors and implement practical, enforceable supply chain security controls based on #ISO42001 (#AIMS). ➡️Key Risks in the AI Supply Chain AI supply chains introduce hidden vulnerabilities: 🔸Pre-trained models – Were they trained on biased, copyrighted, or harmful data? 🔸Third-party datasets – Are they legally obtained and free from bias? 🔸API-based AI services – Are they secure, explainable, and auditable? 🔸Open-source dependencies – Are there backdoors or adversarial risks? 💡A flawed vendor AI system could expose organizations to GDPR fines, AI Act nonconformity, security exploits, or biased decision-making lawsuits. ➡️How to Secure Your AI Supply Chain 1. Vendor Due Diligence – Set Clear Requirements 🔹Require a model card – Vendors must document data sources, known biases, and model limitations. 🔹Use an AI risk assessment questionnaire – Evaluate vendors against ISO42001 & #ISO23894 risk criteria. 🔹Ensure regulatory compliance clauses in contracts – Include legal indemnities for compliance failures. 💡Why This Works: Many vendors haven’t certified against ISO42001 yet, but structured risk assessments provide visibility into potential AI liabilities. 2️. Continuous AI Supply Chain Monitoring – Track & Audit 🔹Use version-controlled model registries – Track model updates, dataset changes, and version history. 🔹Conduct quarterly vendor model audits – Monitor for bias drift, adversarial vulnerabilities, and performance degradation. 🔹Partner with AI security firms for adversarial testing – Identify risks before attackers do. (Gemma Galdon Clavell, PhD , Eticas.ai) 💡Why This Works: AI models evolve over time, meaning risks must be continuously reassessed, not just evaluated at procurement. 3️. Contractual Safeguards – Define Accountability 🔹Set AI performance SLAs – Establish measurable benchmarks for accuracy, fairness, and uptime. 🔹Mandate vendor incident response obligations – Ensure vendors are responsible for failures affecting your business. 🔹Require pre-deployment model risk assessments – Vendors must document model risks before integration. 💡Why This Works: AI failures are inevitable. Clear contracts prevent blame-shifting and liability confusion. ➡️ Move from Idealism to Realism AI supply chain risks won’t disappear, but they can be managed. The best approach? 🔸Risk awareness over blind trust 🔸Ongoing monitoring, not just one-time assessments 🔸Strong contracts to distribute liability, not absorb it If you don’t control your AI supply chain risks, you’re inheriting someone else’s. Please don’t forget that.

How do you identify the inherent risk of an AI vendor? With AI embedded in more products than ever, risk teams need quick, practical ways to triage AI vendors—before jumping into full assessments. Here’s a lightweight framework to evaluate inherent risk, along with how answers can help categorize vendors as Low / Medium / High Risk: 1. What does the AI do? (Function & Impact) Low Risk: Internal tooling, limited automation, or decision support only. Medium Risk: External-facing, influences workflows or user actions. High Risk: Autonomous actions, decision-making, or regulatory impact (e.g., underwriting, hiring, diagnosis). 2. What data does it access or process? (Data Sensitivity) Low Risk: Public data, or no access to sensitive info. Medium Risk: Internal business data, some customer metadata. High Risk: PII, PHI, financial data, IP, or regulated datasets. 3. Where is the model hosted and how is it trained? (Infrastructure & Lineage) Low Risk: Hosted securely in enterprise-grade cloud, trained on synthetic or public data. Medium Risk: Custom model hosted externally, mixed training data. High Risk: Unknown model provenance, unclear hosting, or lack of security controls. 4. How transparent is the vendor about their AI? (Governance & Explainability) Low Risk: Clear documentation, known failure modes, strong governance. Medium Risk: Basic explanations, limited testing info. High Risk: Black box, no visibility into training, governance, or testing. This framework doesn’t replace full due diligence—but it gives you a head start in prioritizing where to spend your limited time and resources. AI risk management starts with better questions. Risk categorization starts with better context. #cyberrisk #TPRM #AIgovernance #vendorrisk #inherentrisk #thirdpartyrisk #AIsafety #riskmanagement

You’ve just joined a mid-size company as a GRC Coordinator. Your manager asks you to support an upcoming vendor risk review. One of the company’s key third-party platforms experienced a minor outage last month. Leadership now wants better visibility into vendor risk before renewing the contract. You begin by checking if the vendor has submitted any recent documentation. You locate an outdated security questionnaire from over two years ago. It mentions a legacy data center setup, but the vendor now operates entirely in the cloud. That discrepancy is a red flag. You reach out to the vendor, letting them know your company is refreshing its records. You send over a short but targeted questionnaire with updated questions about incident response, encryption practices, and subcontractors. You also ask for any available certifications, like a SOC 2 report or ISO 27001. Internally, you check with Procurement and IT to understand the vendor’s role. It turns out this vendor supports customer login and account access, which means their reliability directly impacts the user experience. You mark them as high impact and recommend that they be monitored more closely. You update your team’s vendor risk tracker with the new responses and supporting files. In your notes, you recommend moving this vendor to the quarterly reassessment schedule instead of annual, based on their business function and the recency of the outage. 1. You identified a risk based on outdated information. 2. You improved visibility by asking for updated documentation. 3. You flagged a business-critical system and recommended changes to the review cadence. 4. You kept your company informed and protected with practical follow-up. You don’t have to be a vendor risk expert to add value. You just need to ask the right questions, connect with the right people, and document what you find clearly.

Vendor risk isn’t just about the vendor... It’s also about the use case. You’re not assessing “the vendor” as a whole, you’re assessing the risk of that vendor AND the specific product or service you’re consuming. "Approving" a vendor ≠ approving ALL their products and services Just because a vendor "passed" your security review for one product or service doesn’t mean you can blindly adopt everything else they offer. Their CRM might be secure, but their AI analytics tool could be a compliance nightmare. Different use cases = different risk profiles A vendor handling marketing emails has much different security profiles than one storing sensitive customer data. Treating all services the same is a waste of time and money. Tier the vendors based on their access, location within your data flow, and criticality to your operations. I like 3 tiers. More on that in a future post. One assessment doesn’t last forever Risk isn’t static. If the vendor updates their product, expands their scope, is acquired, or moves to a new hosting provider, your original assessment is outdated. For bonus points, build this into your change management program. How to Fix It -Assess risk at the vendor + product/service level you're consuming, not just the vendor. -Define clear use case boundaries. What exactly are you using, where is the data flowing, what access do they have, and what’s the impact if something goes wrong? -Require reassessments for new services. Don’t assume past approvals cover new use cases. -Document compensating controls if security gaps exist and mitigate, don’t ignore. This saved my ass once. Stop treating vendor "approvals" like a golden ticket to consume everything they offer. Risk is contextual. Assess accordingly. #ciso #dpo #msp #riskmanagement

🛡️🏛️ The Hidden and Growing Risks of Third-Party AI Models 🏛️🛡️ ⚡Why Vendor's Model Validation is a Growing Concern? The Federal Reserve's SR 11-7 guidance mandates that financial institutions validate all models, whether built in-house or procured from 3rd party vendors. However, in practice, vendor model validation presents unique challenges for Model Risk Management (MRM) teams, particularly due to their "black box" nature. Many vendors restrict access to their AI models, citing intellectual property concerns. But is this truly about protecting proprietary technology, or is it an excuse to mask flaws and governance gaps? ⚠️ Lack of transparency leaves institutions unable to assess risks fully. ⚡The Growing Challenge with Generative AI (GenAI) Models GenAI models have exacerbated these challenges, with critical aspects often overlooked: 1️⃣ Assumptions & Limitations: Understanding foundational assumptions is crucial for assessing a model’s applicability and reliability. 2️⃣ Data Inputs & Parameters: Knowing input sources and parameter settings is key to evaluating robustness and relevance. 3️⃣ Explainability: Clear explanations of model design and analytics help stakeholders trust and effectively use the model. 👉 Open-source initiatives like Meta’s Llama 3 represent major steps toward transparency. By making model weights publicly available, Meta has enabled greater scrutiny, collaboration, and ultimately, more trustworthy AI. 💡 How Risk Teams Can Strengthen Vendor Model Validation? 🔹 Develop Specialized Expertise – AI model validation requires domain-specific knowledge. If in-house expertise is lacking, consider training teams or engaging third-party validators. 🔹 Enforce SR 11-7 Compliance in Vendor Contracts – Require transparency on model components, design, intended use, assumptions, and limitations to ensure alignment with risk policies. 🔹 Document Model Use – Maintain internal documentation covering inputs, outputs, key assumptions, and vendor-provided details to support audits and compliance. 🔹 Validate Independently – Review vendor testing results and conduct additional testing where feasible to verify performance and identify risks. 🔹 Assess Data Sources – Scrutinize input data quality, completeness, and appropriateness, particularly for LLMs, to mitigate data transparency and copyright concerns. 💡 Final Thoughts The financial industry is undergoing a transformative period with the rapid adoption of AI models, driven by promises of efficiency gains. However, this progression must align with robust governance standards. ⚠️ Major commercial vendors often prioritize performance, sometimes at the expense of transparency and comprehensive real-world testing. 👉 It is incumbent upon risk teams to implement appropriate guardrails and advocate for a more transparent and open approach to model validation, ensuring that innovation does not compromise integrity and reliability.

Dear Business Leaders & IT Auditors, Red Flags in Vendor Cybersecurity Assessments Many organizations invest heavily in securing their internal systems, yet still face breaches. The entry point is often not their own network but a vendor’s. Payroll processors, cloud providers, and other third parties store sensitive data and sometimes have direct access to business-critical systems. The problem is that many vendor assessments focus on paperwork rather than evidence. A “yes” on a form does not equal security. Here are the most common red flags I see in vendor cybersecurity assessments: 📌 Self-attested questionnaires: Vendors claim they encrypt data or maintain firewalls, but without independent validation, these answers hold little weight. 📌 Lack of ongoing monitoring: A one-time review creates blind spots. Vendors change technologies, add subcontractors, or shift their posture over time. 📌 Weak contract language: Too many contracts skip enforceable security obligations. Missing terms on required controls, breach notifications, or audit rights leave companies exposed. 📌 No incident history disclosure: A vendor with undisclosed breaches poses hidden risks that can surface at the worst possible time. 📌 Critical vendors without audits: Providers handling sensitive data often go unchecked. If they are not subject to a formal review, the risk to your organization increases sharply. A strong cybersecurity audit must look beyond internal environments and test how vendor risk is managed. That means: 📌 Reviewing vendor risk assessment practices. 📌 Examining contract clauses for clarity and enforceability. 📌 Verifying third-party assurance reports (SOC 2, ISO 27001, etc.). 📌 Confirming that continuous monitoring is in place. Executives need to ask one critical question: How do we know our vendors are secure today, not just when the contract was signed? Outsourcing a process does not transfer the ultimate risk. When a vendor suffers a breach, regulators and customers will hold your company accountable. How confident are you that your vendors meet the same standards you enforce internally? #Cybersecurity #Audit #VendorRisk #ThirdPartyRisk #RiskManagement #Compliance #InformationSecurity #BoardGovernance #CISO #BusinessLeadership #CyberVerge #CyberYard

Third-party vendors are often the weak link in your data security chain.  Cybercriminals exploit their vulnerabilities to access your network and data.  To prevent this, you need to perform rigorous due diligence on your vendors.  Yes, this may seem uncomfortable or inconvenient to do. But a false sense of security will lead to disaster down the road. So, what can you do about it? The answer lies in conducting thorough due diligence on third-party vendors. But this isn’t just about checking their credentials and references. It’s about understanding their security practices, policies, and protocols.  And ensuring they have robust security measures in place, including firewalls, encryption, and intrusion detection systems. You need total visibility into their data security posture before you engage them. Request that they complete in-depth risk assessments and adhere to access limitations and encryption protocols that you define. Then conduct regular audits for compliance and limit data access only on a need-to-know basis. Treat vendor risk assessment with the same intensity as protecting your own infrastructure. Your data deserves nothing less.

A cybersecurity program should be well rounded and needs strong components, one of which is a Third-Party Vendor Cyber Risk Assessment program. I believe there will be regulatory push for this moving forward so adopting this practice is beneficial sooner rather than later. Organizations within critical infrastructure—such as energy, healthcare, finance, and transportation—are increasingly vulnerable to cyber threats due to the interconnected nature of modern supply chains. Third-party vendors often have direct access to sensitive data and critical systems, making them a significant cybersecurity risk. A single breach through a compromised vendor can lead to operational disruptions, data theft, regulatory penalties, and even national security threats. To mitigate these risks, organizations must implement rigorous third-party vendor cyber risk assessments as part of their cybersecurity strategy. These assessments help ensure compliance with regulatory frameworks (such as NIST, ISO 27001, CIS and CISA guidelines), protect sensitive data, and strengthen operational resilience against supply chain attacks. Key components of a robust vendor risk assessment include: Vendor Risk Profiling: Identifying vendors with access to critical systems. Security Policy & Compliance Review: Ensuring adherence to cybersecurity standards. Access Controls & Data Protection: Enforcing least privilege access and encryption. Incident Response & Recovery Readiness: Evaluating vendors’ breach response capabilities. Continuous Monitoring & Penetration Testing: Regularly assessing vulnerabilities and security posture. Contractual Security Requirements: Embedding cybersecurity obligations in vendor agreements. To strengthen third-party risk management, organizations should adopt a risk-based approach, enforce Zero Trust principles, require real-time security monitoring, and conduct regular cybersecurity exercises. Cyber threats are escalating, and organizations can no longer afford to overlook vendor risks. A proactive cybersecurity strategy that includes thorough third-party risk assessments is essential for safeguarding critical infrastructure, ensuring regulatory compliance, and maintaining national security.

Most third-party risk teams I speak with face the same challenge: Small staff, large vendor portfolios. 💼 The data backs this up: - The average portfolio is ~286 vendors; most TPRM teams have fewer than 10 staff. - 94% of teams say they cannot assess all vendors due to a lack of time or resources. - Nearly 50% of companies admit they don’t even reassess all vendors periodically. - Assessment cycles average 37+ hours per week, with vendor responses dragging 12+ days and 84% needing follow-ups. So, how do you cover more risk without more people? Here are some simple recommendations: ✅ Tier ruthlessly – Auto-tier vendors into 4 levels; reserve full assessments + monitoring for Tier 1. ✅ Use what exists – Accept SOC 2, ISO, or SIG Lite when fresh instead of sending new questionnaires. ✅ Streamline questionnaires – Keep only two: Core and Lite, with “proof selector” options to reduce doc sprawl. ✅ Event-based reassessments – Trigger quick checks after major incidents or CVEs instead of annual reviews for all. ✅ Automate workflows – SLA boards, templates, and parallel legal/security reviews speed decisions. ✅ Blend capacity – In-house for critical vendors, managed services, or external reviewers for overflow. Six metrics to prove efficiency to your board: 1) Coverage – % of Tier 1–2 assessed & monitored 2) Cycle Time – intake → decision 3) Risk Impact – remediation in 30/60/90 days 4) Accepted Risk Backlog – trend line 5) Reviewer Hours – per completed assessment 6) Cost – per Tier 1 decision Bottom line: You don’t need to assess every vendor equally. Focus depth where it matters, streamline the rest, and measure results. #ThirdPartyRiskManagement #TPRM #VendorRisk #OperationalResilience #RiskManagement #CyberRisk #Governance #Compliance #Procurement #SupplyChainRisk