Ramp Introduces AI Agents for Finance Teams: Revolutionizing Expense Management and Policy Enforcement

Ramp rolls out AI agents

This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author. Ramp's smart automation helps businesses of all sizes cut down on manual tasks, increase productivity, and make decisions about money faster. It does everything from approving expenses to analysing spending in real time. Finance teams are being asked to do more with less, yet the function remains largely manual. Teams using legacy platforms today spend up to 70% of their time on tasks like expense review, policy enforcement, and compliance audits. As a result, 59% of professionals in controllership roles report making several errors each month. Ramp's agents for controllers solve these problems by eliminating redundant tasks, working autonomously to review expenses and enforce policy. Built on Ramp Intelligence, powered by OpenAI's reasoning models Ramp's agents for controllers apply context-aware, human-like reasoning to manage entire workflows independently and proactively. Unlike traditional automation that relies on basic rules and conditional logic, these agents reason and act on behalf of the finance team, working independently to enforce spend policies at scale, immediately prevent violations, and continuously improve company spending guidelines. Ramp agents are meticulous, auditable, and consistent, escalating issues when needed and providing a clear audit trail for every decision. Early customers reported 99% accuracy in expense approvals1. Ramp's AI agents act on data instantly, giving finance teams a co-pilot for real-time operations by suggesting actions and pointing out problems. "Before Ramp agents, we manually reviewed 100% of transactions. Now, Ramp agents take the first pass and flag what actually needs our attention. Every decision Ramp makes is logged with a clear audit trail. Accuracy matters, and Ramp consistently gets it right. We've seen fewer errors, faster reviews, and stronger policy enforcement across the board," said Richard Gobea, Finance Manager at Quora. Ramp agents are powered by Ramp Intelligence, Ramp's AI platform that automates expense reporting, data entry, contract review, and accounting accuracy. Agents learn and adapt directly from company policies and feedback from users to: Approve low-risk expenses or provide a recommendation with rationale to the approver Alert of suspicious receipts and invoices Answer employee questions about spend policy Uncover trends that signal fraud or careless spend Suggest edits to company expense policies based on usage and feedback "Ramp agents have complete knowledge of your accounting rules and expense policies that employees don't carry in their heads, plus instant access to transaction details that finance teams would need time to gather. This lets them act faster and more accurately on every transaction," said Karim Atiyeh, co-founder and CTO at Ramp. "This isn't just automation. It's intelligent reasoning that handles complex financial decisions to reduce errors, strengthen policy enforcement, and stop fraud." "It's amazing to see what Ramp has built with our newest reasoning models," said Olivier Godement, head of platform product at OpenAI. "These agents are taking care of key financial processes and, most importantly, getting them right - letting teams focus on deeper strategic work." The AI advantage for finance Ramp agents put best-in-class AI into the hands of finance teams and provide a new layer of engineering support to resource-constrained teams. Ramp invests 50% of its payroll in research and development so every finance team, no matter the size, can benefit from the latest breakthroughs in AI automation and reasoning. "Ramp takes the manual work off our plate and gives us the confidence that we're ahead of emerging AI fraud threats before they hit us," said Lawrence Dann-Fenwick, Head of Strategic Finance at Hex. Finance teams at leading AI companies like Notion, Hex, Sierra, and Quora already use Ramp to move faster, operate smarter, and stretch every dollar further.

Ramp Debuts AI Agents Designed for Company Controllers | PYMNTS.com

The new offering is designed for controllers, helping them to automatically enforce company expense policies, block unauthorized spending, and stop fraud, and is the first in a series of agents slated for release this year, the company said in a Thursday (July 10) news release. "Finance teams are being asked to do more with less, yet the function remains largely manual," Ramp said in the release. "Teams using legacy platforms today spend up to 70% of their time on tasks like expense review, policy enforcement, and compliance audits. As a result, 59% of professionals in controllership roles report making several errors each month." Ramp says its controller-centric agents solve these issues by doing away with redundant tasks, and working autonomously to go over expenses and enforce policy, applying "context-aware, human-like" reasoning to manage entire workflows on their own. "Unlike traditional automation that relies on basic rules and conditional logic, these agents reason and act on behalf of the finance team, working independently to enforce spend policies at scale, immediately prevent violations, and continuously improve company spending guidelines," the release added. PYMNTS wrote earlier this week about the "promise of agentic AI," systems that not only generate content or parse data, but move beyond passive tasks to make decisions, initiate workflows and even interact with other software to complete projects. "It's AI not just with brains, but with agency," that report said. Industries including finance, logistics and healthcare are using these tools for things like booking meetings, processing invoices or managing entire workflows autonomously. But although some corporate leaders might hold lofty views for autonomous AI, the latest PYMNTS Intelligence in the June 2025 CAIO Report, "AI at the Crossroads: Agentic Ambitions Meet Operational Realities," shows a trust gap among executives when it comes to agentic AI that highlights serious concerns about accountability and compliance. "However, full-scale enterprise adoption remains limited," PYMNTS wrote. "Despite growing capabilities, agentic AI is being deployed in experimental or limited pilot settings, with the majority of systems operating under human supervision." But what makes mid-market companies uneasy about tapping into the power of autonomous AI? The answer is strategic and psychological, PYMNTS added, noting that while the technological potential is enormous, the readiness of systems (and humans) is much murkier. "For AI to take action autonomously, executives must trust not just the output, but the entire decision-making process behind it. That trust is hard to earn -- and easy to lose," PYMNTS wrote, noting that the research "found that 80% of high-automation enterprises cite data security and privacy as their top concern with agentic AI."