Case Study
Our customer is a family-owned hospitality company, with 15 resorts across Mexico and the US
For the past two decades, our customer has been expanding its geographic presence in the Mexican and US markets through acquisitions. This expansion created a complicated network of disparate ERPs, Property Management Systems, and Electronic Invoicing platforms powering the company’s financial operations. As a result, to close the books for the Hotel Division every month, the Finance team had to manually consolidate accounts from each system, a time-intensive process requiring up to 15 days to complete.
This challenge had several downstream repercussions, including limited access to accurate financial and operational data, as well as a lack of real-time electronic invoicing controls.
After a recent audit uncovered hundreds of thousands of dollars in duplicated supplier invoices, the CFO was committed to tackling his organization’s challenges head-on – a perfect use case for our AI-Platform.
After a three-month journey, the Finance team cut P&L closing time for the Hotel Division by 50% supplying the CFO and her leadership team with reliable analytics and streamlined electronic invoicing controls.
First, our customer integrated its multiple operating systems’ data bases into Arkham’s Data Lakehouse using our JDBC native connectors.
Subsequently, they leveraged our Pipeline Builder to automatically integrate the Property Management System Accounts with the Corporate ERP, enabling the Hotel Division to close its P&L in half the time.
Having ensured the P&L data was 100% reliable, our customer leveraged Arkham’s modular workbooks to build weekly and monthly financial analytics reports for multiple stakeholders across the organization.
Moreover, our customer deployed Arkham's Anomaly Detection models on their newly centralized electronic supplier invoicing data. These models identify irregularities in SAT Invoices flagging abnormal or duplicated supplier transactions for secondary review.
In parallel with automating FP&A reporting, our customer adopted Arkham’s Data Analysis Assistant. This tool empowers their FP&A analysts to perform analyses in mere hours—tasks that once spanned days. This efficiency surge eliminates the need for manual data manipulation and the mastery of Python or SQL. Now, financial analysts simply choose the appropriate dataset in Arkham and query it in any language.
After successfully automating the majority of their financial close processes, our customer is planning to leverage Arkham’s AI Platform to deploy additional operational controls across its Hotel Division.
