AIMultiple’s overview of RPA in finance highlights why bots excel at repetitive back-office work and how they pair with ML to tackle richer tasks. Priority use cases include AP/AR (invoice capture, PO matching, routing, payments), financial controls and reporting, and faster FP&A (data loading, variance reporting, forecasting). Reported wins: Thermo Fisher cut invoice-processing time 70% (824k docs/year); a Fortune 500 tech firm reduced report-gen effort ~70% with better audit trails; TreasuryOne lowered settlement errors. Benefits: lower cost, fewer mistakes, higher compliance, easier scaling, and more time for planning and investor relations. Accenture estimates up to 80% of finance ops can be automated; McKinsey puts ~42% as fully automatable. Challenges remain around bot maintenance an

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