Blockchain Gaming Studio Automates Global Payment Reconciliation for Faster Financial Closes

Mythical Games, a leading blockchain gaming studio, faced significant challenges in their finance department with manual, time-consuming daily data reconciliation across numerous global payment gateways. This often led to inconsistencies, errors, and delayed monthly closing processes. By implementing Sheetgo, the team automated the integration and merging of critical financial data from various sources, drastically improving reporting accuracy and accelerating their financial close cycle, allowing them to focus on strategic initiatives.

The finance team at Mythical Games struggled with an incredibly time-consuming and error-prone manual process for daily data reconciliation. Their commission reporting workflow relied on outdated integrations and a multitude of disparate spreadsheets, frequently resulting in data inconsistencies. A persistent issue involved repeatedly failing connections to external financial files, causing incorrect data reflections and requiring constant recreation of data links. This not only consumed valuable team resources but also disrupted the critical monthly closing process. Furthermore, the slow processing of large financial data files exacerbated these operational hurdles, impacting the accuracy of financial reporting and elevating the risk of errors in reconciliation.

Sheetgo transformed Mythical Games' financial operations by completely automating their daily data reconciliation process. Sheetgo established robust, automated connections to over a dozen global payment platforms, eliminating the need for manual data extraction and integration. Complex financial datasets from various sources were automatically merged and filtered based on specific conditions, ensuring only relevant and accurate information was used for analysis and fed into a centralized financial overview. This automated workflow, often triggered daily, drastically reduced manual steps, eliminated errors, and significantly improved processing times, especially for large files. The improved data accuracy and operational efficiency allowed for faster monthly closing cycles, significantly reducing the risk of reporting errors and freeing up valuable team time to focus on strategic financial analysis rather than tedious data management. The ability to share these automated workflows also fostered better collaboration within the finance team.