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Many risk management and compliance (R&C) functions are costly, labor-intensive programs trying to keep pace with the speed of business and technology. Reliant on capabilities designed for one purpose rather than evolving risks―and on siloed tools developed in a bygone era―some find it harder to generate value and maintain relevance. Yet these teams have significant, untapped potential that, unlike the front office, has largely eluded digital reengineering efforts.
Why is that? Until recently, business leaders either didn’t see the potential ROI or they feared unintended consequences of disrupting R&C functions. But that’s changing, as emerging use cases for transforming these processes point to substantial opportunities for savings and growth hiding in plain sight. Fueling this shift is a growing openness among regulators toward the responsible use of AI.
As confidence grows and regulatory expectations evolve, senior executives now see a window to modernize responsibly—using AI not just to spur efficiency but to drive speed, capacity, and growth. The need for speed and smart risk-taking is more pressing than ever as companies navigate the uncertainty of geopolitical shifts, regulatory change, and the latest advances in technology.
R&C teams who seize this moment will position themselves for a very different future. By scaling their capabilities with automation, risk-signal monitoring, agentic solutions, and real-time insights to help make smart decisions faster—all while reducing operational expenses—these teams can evolve into highly strategic advisors to the business.
The impossible is now possible. AI is helping unlock entirely new ways of managing risk and compliance that, until recently, weren’t feasible. Let’s consider several innovative, high-impact examples.
- Implement risk-horizon scanning
- Manage regulatory change in real-time
- Simulate data for scenario planning
- Build a virtual regulator
- Validate models with risk analytics
Implement risk-horizon scanning
With internet access to voluminous external data sources and indicators of risk, and now agentic AI, your R&C teams can continuously scan risk signals and highlight those that warrant further review and potential action. And, by supplementing those data sets with internal indicators, issues, and insights, your old static interview-only risk assessments will become a relic of the past. AI can also tell you which clients, suppliers, functions, locations, products, or transactions may pose higher risk and warrant closer scrutiny. Think of this input as a flashlight (versus a control) to help you uncover potential problems not on your radar.
Manage regulatory change in real-time
Regulatory change management has always been a cumbersome task spread across different groups, and few organizations do it well. With AI-enabled technology and agents, companies can now monitor various regulatory bodies and promptly update internal policies, procedures, and controls to reflect new requirements.
Simulate data for scenario planning
Traditional scenario planning often falters because of insufficient data needed to replicate real-world situations and varying risk factors. That’s where AI comes in. It can quickly generate synthetic data needed to mimic and test any hypothetical scenario—e.g., modeling of policy or geopolitical shifts and their potential impact on company operations—enabling you to make strategic decisions with greater speed and confidence.
Build a virtual regulator
When dealing with novel compliance questions, businesses historically resorted to analyzing the universe of applicable rules, guidance, and decisions to help predict which course of action would pass regulatory muster, then hope for the best. AI can front-load that process by creating virtual regulators―personas informed by the relevant agency’s body of regulations, guidance, and decisions―to pressure-test upfront your organization’s plans and avoid unnecessary sunk costs. Using a similar approach, you might consider building a virtual auditor, which can further reduce compliance costs as well as auditor fees.
Validate models with risk analytics
AI is transforming how institutions test, document, and monitor models, an area under increasing regulatory scrutiny. These tools can automatically generate documentation, compare outputs under different conditions, and flag anomalies or data drift for review. They can also create synthetic data sets to stress test model performance in varied scenarios without exposing sensitive information. All of this will require review by people to foster defensible, transparent decision-making, but the AI outputs can give your teams an important head start and uncover issues and patterns no human could spot unaided.
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