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80 % REDUCTION Daily Reconciliation Cycle (4 hours to less than 45 minutes) Reduced daily reconciliation time, enabling the finance team to focus on higher value priorities. |
95 % MATCH RATE Automatic, Zero-Touch Reconciliation Automated reconciliation for standard credit card and terminal batches, with only exceptions requiring human review. |
“Claude-powered AI transformed reconciliation from a time-consuming manual process into an intelligent, exception-driven operation. By automating 95% of routine matches and reducing daily reconciliation time by 80%, we have given our finance team more time to focus on analysis, controls, and higher-value business priorities.”
-Rajesh Devarajan, MD, Hablis Hotel
Client profile
Recognized as one of Chennai ’s premier business hotels, Hablis offers a contemporary hospitality experience designed for today’s corporate travelers. Strategically located in one of Chennai’s key commercial districts, the hotel combines modern accommodation, business-focused amenities, and attentive service to provide a seamless, comfortable, and productive stay.
The challenge
Despite operating a single property, the hotel’s high-volume, multi-channel revenue model created significant financial complexity. Each day, the finance team spent hours reconciling transactions across front-desk payment terminals, restaurant outlets, spa bookings, Online Travel Agencies (OTAs), payment processors, and the hotel’s central bank account.
The result was a labor-intensive daily reconciliation process characterized by fragmented data, manual calculations, and exception handling, limiting the finance team’s ability to focus on higher-value financial analysis and strategic priorities.
The solution
The hotel implemented a AI/Claude-powered Intelligent Reconciliation Engine, securely integrated with its Property Management System (PMS), payment platforms, OTA channels, and banking data sources. The solution automated the end-to-end reconciliation process while maintaining appropriate controls and human oversight.
Intelligent Fee & Variance Matching: The AI engine automatically retrieves gross revenue and transaction data from the PMS, calculates expected merchant processing fees, and accounts for settlement timing differences. By intelligently resolving gross-to-net variances, the system can accurately match payment terminal batches with corresponding bank deposits.
Automated OTA Data Capture: Secure automation connects with OTA portals to retrieve virtual credit card (VCC) information and support transaction data. AI-powered document extraction captures relevant details from invoices and folio documents and matches them with corresponding reservation and transaction IDs in the PMS
Exception-Driven Reconciliation: Instead of requiring the finance team to review thousands of transactions, the engine automatically reconciles approximately 95% of standard matched entries. Only exceptions and higher-risk anomalies—such as duplicate charges, settlement discrepancies, unmatched transactions, or unexpected bank fees—are routed to the finance team for investigation and resolution.
Business Impact
The result is a shift from labor-intensive transactions matching to intelligent, exception-based financial operations, enabling the finance team to spend less time reconciling data and more time on financial analysis, controls, and higher-value activities.
95% Automated Match Rate: Achieved zero-touch reconciliation for approximately 95% of standard credit card and payment terminal transactions, with only exceptions routed for human review.
80% Reduction in Reconciliation Time: Reduced the daily reconciliation cycle from approximately 4 hours to less than 45 minutes, allowing the finance team to redirect its time toward analysis, controls, and higher-value strategic activities.