Automating Travel & Expense Reconciliation for a Top 5 U.S. Bank

THE PROBLEM

When Manual Reconciliation Becomes an Operational Risk

Corporate payments teams sit at the center of a messy operational reality: transactions flowing from multiple systems, each with its own data format and failure points. 

At this leading U.S. financial institution, the process of reconciling travel and expense (T&E) transactions required employees to manually trace and match entries across three platforms, including allocation across cost centers and custom exception rules.

This was time-consuming and operationally risky. Transactions were frequently misclassified, audit trails were incomplete, and end-of-month reporting got bogged down in exceptions. Manual review wasn’t scaling with transaction volume, and leadership knew that even modest growth in T&E spending would demand either more headcount or smarter automation.

The business wanted a simple outcome: “one-click” reconciliation and allocation solution to streamline processes and reduce manual workload. But off-the-shelf tools couldn’t handle the institution’s layered rules, fragmented systems, or need for fine-grained transparency. 

Solving the problem meant moving beyond templates and capturing the messy edge-cases that make reconciliation difficult in the first place.

THE SOLUTION

Purpose-Built AI to Automate Complex T&E Matching

The institution partnered with us to test an AI-powered reconciliation system purpose-built for finance workflows. The goal of the PoC was to reduce manual work, increase transparency, and surface failure explanations for unreconciled transactions.

We deployed a specialized app that leveraged Decision AI capabilities which we tailored to the corporate payments team. This wasn’t generic automation but AI trained on real reconciliation logic and optimized for future production integration with systems like Concur and Chrome River.

The system included:

• Automated matching of transactions with configurable error margins
• Root cause classification of unreconciled items into four categories
• Dynamic dashboards that visualize reconciliation status and merchant spend
• Drill-down interfaces for exception review
• Partial audit logs to support compliance and future scaling

Though built on batch/mock data, the architecture was designed for easy transition into live, API-connected workflows.

THE RESULTS

Clarity, Control, and a Path to Scalable Automation

The outcomes were clear:

• Automatically flagged unreconciled transactions and categorized them by root cause, giving analysts immediate visibility into failure types without the need for manual triage.
• Reduced the manual effort required to review and resolve exceptions by surfacing only the items that needed human attention, along with context on why reconciliation failed.
• Provided visual dashboards that broke down spend by merchant category, highlighted unreconciled volumes, and allowed business users to filter and explore transaction data in real time.

Perhaps most importantly, the institution saw that high-volume T&E reconciliation didn’t need to remain a spreadsheet-driven bottleneck. With intelligent automation, business users gained clarity, auditors gained traceability, and operational risk decreased.

Encouraged by initial results, the bank is now exploring an expanded PoC that would deepen integration and broaden use cases.

About the customer

This financial institution is one of the largest banks in the U.S., with specialized offerings across corporate payments, expense management, and digital cash flow solutions. Their operational teams manage complex, high-volume workflows where transparency, accuracy, and scalability are essential.