Managing Risk With Emerging Technology: Governance, Models, and Third Parties
Emerging technology risk
Emerging technology changes risk faster than traditional annual reviews. Candidates should understand AI/model risk, algorithmic bias, explainability, data privacy, cyber resilience, cloud concentration, IoT/OT exposure, blockchain and smart-contract risk, third-party/vendor risk, and regulatory/compliance risk. Technology risk is not only IT failure: it includes strategic, operational, conduct, legal, reputational, and financial dimensions. Governance starts with board oversight, risk appetite for technology, clear ownership, policies, and three-lines-of-defense roles. Controls include data governance, access management, encryption, vendor due diligence, contractual protections, testing, monitoring, incident response, and business continuity. Model risk needs validation, performance monitoring, bias testing, human oversight, and documentation. Emerging tech can create opportunity, so risk management should enable innovation with guardrails, not ban it. Traps: treating emerging tech as solely a cybersecurity issue; assuming vendor contracts transfer reputational or regulatory risk; ignoring model drift, data quality, or concentration risk; and overlooking third-party and fourth-party dependencies. Worked example: for an AI underwriting tool, map harms such as unfair denial, privacy breach, and inaccurate pricing; rate inherent risk; apply controls such as bias testing and human review; then track residual risk and KRIs. Rule of thumb: if the organization cannot explain, monitor, or stop the technology, it has not adequately governed it.