Uber Technologies has restructured its financial risk management operations by embedding technical talent and expanding the use of data, automation, and artificial intelligence to support compliance efforts as the company grows. The shift reflects a broader trend in which organizations are integrating engineering and analytics capabilities into risk and compliance functions to improve scalability and responsiveness.
The initiative builds on changes that began when Uber established a finance risk management (FRM) function ahead of its 2019 initial public offering. During its early phase, the team focused on stabilizing controls, meeting compliance requirements, and supporting executive decision-making during a period of rapid expansion. Over time, the function evolved into a more proactive unit, using operational data and insights to design controls and improve oversight across the business.
According to Adam Frank, the team later determined that deploying automated tools alone was not sufficient to keep pace with product development and global growth. Instead, Uber expanded the FRM team to include engineers capable of building scalable systems, automating workflows, and refining risk controls through iterative development.
To support this shift, Ramesh Raju was tasked with developing a compliance technology function that integrates engineering practices with financial risk management. The approach led to the development of a proprietary compliance platform designed to leverage AI, continuous monitoring, and data-driven insights to manage risk at scale.
Frank said the new structure allows the risk function to move beyond traditional assurance roles and contribute more directly to business decision-making. Capabilities initially developed for Sarbanes-Oxley (SOX) compliance were later reused across multiple compliance programs, helping transform the FRM team into a strategic partner within the organization.
The transition followed a period of continued expansion after Uber’s IPO, during which traditional risk assessment and control monitoring processes struggled to keep pace with frequent product updates and operational changes. The FRM team identified the need for technical leadership that could treat risk management as a scalable product, embedded within operational workflows rather than applied as a reactive overlay.
Raju said the early phase of the initiative focused on understanding business processes, data flows, risks, and controls. Initial efforts included small pilot programs, controls testing, and dashboard development. As automation capabilities expanded, the team began building solutions covering broader elements of the financial risk lifecycle, including testing, monitoring, and risk assessment.
The company emphasized that multidisciplinary skills are central to the approach. Raju highlighted the importance of engineers who can both develop code and understand financial reporting and compliance requirements. This combination is intended to bridge technical execution with business objectives and support more dynamic risk management.
Looking ahead, Uber expects continued integration of AI and automation across compliance functions. Frank said the evolution of hybrid skill sets—combining risk expertise with technical capabilities—will likely shape the next generation of risk professionals. Raju added that automation of routine review tasks could allow compliance teams to focus on analysis, decision support, and strategic risk insights.
The initiative reflects a broader shift toward embedding technology directly into governance and compliance processes, with organizations increasingly using data-driven tools to streamline workflows, improve oversight, and manage risk across complex operations.
#SupplyChainNews #RiskManagement #AIinCompliance #TechTransformation #CorporateGovernance
