RPA in Finance | Finance Process Automation
Finance teams process high volumes of structured, rule-based transactions -- invoice matching, bank reconciliation, accounts payable runs, period-end close tasks, and regulatory reporting. Most of this work follows the same logic every time. A bot executes it faster, with fewer errors, and with a complete audit trail.
We build robotic process automation systems for finance operations -- accounts payable automation, financial reconciliation, period-end close support, and regulatory reporting -- so your finance team focuses on analysis, decisions, and the work that requires financial judgment.
Accounts payable automation from invoice receipt to payment approval
Bank and financial reconciliation without manual matching
Period-end close task automation that compresses your close cycle
Regulatory reporting assembled automatically from your source systems
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Finance team spending close week manually reconciling transactions that a bot could match?
Invoice processing backlog delaying supplier payments and straining vendor relationships?
In short
RaftLabs builds robotic process automation systems for finance teams. We automate accounts payable processing, invoice matching and ERP posting, bank and ledger reconciliation, period-end close tasks, regulatory reporting assembly, and management report generation. Finance RPA eliminates the manual, rule-based transaction processing that blocks finance teams from analysis and decision-making. A focused finance automation for one process runs $20,000-$50,000. Multi-process programmes run $50,000-$130,000. Most projects deliver in 8-12 weeks at a fixed cost.
Trusted by
Manual accounts payable processing costs more per invoice than automated processing. Manual reconciliation introduces errors that take time to find and fix. Manual period-end close takes longer and creates more last-minute pressure than an automated process would.
Finance RPA addresses all three at once -- lower processing cost, fewer errors, and a faster close cycle -- because the same root cause (manual, repetitive transaction processing) drives all three problems.
Capabilities
End-to-end AP automation from invoice receipt to ERP posting and payment batch preparation. AI-powered document extraction (Azure Document Intelligence, Google Document AI) pulls vendor name, invoice number, line items, amounts, and tax from PDF, email, and EDI 810 invoices with field-level confidence scoring -- low-confidence extractions route to a human review queue rather than posting incorrectly. Three-way matching compares the extracted invoice against the purchase order and goods receipt record in your ERP (SAP FI/CO, Oracle Payables, NetSuite, Dynamics 365 Finance) within a configurable tolerance (typically ±1% or ±$50). Matched invoices post automatically; mismatches route to the responsible buyer with the discrepancy highlighted for resolution. Approval routing follows your authorisation matrix -- invoices below threshold auto-approve, those above route to the correct approver tier with a deadline. Payment batch preparation groups approved invoices by due date and payment method (ACH, BACS, wire) and generates the payment file for bank upload, with the finance director sign-off step retained. AP teams processing 500+ invoices per month typically see processing time drop from 8-12 minutes per invoice to under 2 minutes for the exception cases that require human attention.
Automated matching of bank statement transactions to general ledger entries, eliminating the manual comparison work that currently consumes finance team time during monthly close. Bank statement files (MT940, CAMT.053, CSV from your bank's data feed) are ingested automatically. They are then matched against your ERP ledger using configurable matching rules: exact amount and reference matching for direct transactions; partial matching for split payments; multi-line consolidation for bulk payment runs where a single bank transaction corresponds to multiple invoices. Matching confidence scores flag low-certainty matches for human review rather than auto-posting them -- the reviewer sees both records and the reason for the match score. Unmatched items generate an exception report with AI-suggested resolutions (duplicate payment, missing posting, timing difference) to reduce the investigation time per exception. Bank charges, interest, and FX transactions post to the correct accounts automatically based on transaction type rules. The reconciliation that currently takes 2-3 days per bank account during close week runs overnight, with the output a reconciliation pack showing matched items, exceptions with resolutions, and the cleared balance -- ready for the finance manager to review and sign off.
Automated execution of the repeatable period-end close task sequence -- accrual journal posting from source schedules, depreciation runs triggered on the first business day of each period, intercompany elimination entries generated from the intercompany transaction schedule, prepayment amortisation posting, and currency revaluation runs using ECB or Fed published rates. Each close task has an owner, a deadline, and a completion trigger -- when a task completes, the next dependent task unlocks automatically rather than waiting for someone to check. Close task dashboards show the controller which tasks are complete, in progress, and overdue without requiring individual follow-up emails to each team member. Variance analysis data is assembled automatically before the management review meeting: budget vs. actual by cost centre, period vs. prior period, and year-to-date tracking pulled from your ERP (SAP BW, Oracle OBIEE, Power BI connected to your data warehouse). The month-end close cycle that currently takes 8-10 business days compresses to 4-6 because the sequential wait-and-chase pattern is replaced by automated task sequencing with parallel execution where task dependencies allow.
Automated assembly of regulatory submissions from data across your finance, risk, and operational systems -- eliminating the manual data compilation that currently occupies a finance analyst for multiple days per reporting cycle. Data extraction queries pull from your ERP, banking systems, and risk platforms. Transformation logic applies the calculation rules specified in the regulatory template (DSCR, CRR/CRD, Pillar 3, CCAR, FINREP, or your specific regulator's schema). Validation checks confirm that required fields are populated, calculations sum correctly, and year-over-year movements are within defined bounds before the output reaches the reviewer. Submission tracking logs every regulatory deadline, the date the draft was generated, the date it was reviewed and signed off, and the date it was submitted -- providing the paper trail your compliance team needs for regulatory examination. Regulatory change monitoring alerts the team when published rule changes affect your calculation templates or data requirements, with enough lead time to update the automation before the next reporting period. The output your reviewer receives is a submission-ready document with supporting schedules, not a request to spend a week compiling raw data.
Automated extraction of financial data from every source system your finance team currently pulls from manually: bank statement files (MT940, SWIFT, OFX), supplier invoices via email and EDI, expense reports from Concur or Expensify, payroll journals from ADP or Workday, and transaction feeds from payment processors (Stripe, Adyen, PayPal). Document AI (Azure Document Intelligence, LayoutLM) handles unstructured documents where structured feeds aren't available -- extracting tabular data from PDF bank statements, supplier credit notes, and remittance advices with field-level confidence scores. Transformation and normalisation logic handles the structural differences between source formats: a Stripe payout report and a bank statement represent the same cash movement in different schemas, and the pipeline reconciles both before loading. Data loaded into your ERP (SAP, Oracle, NetSuite) or data warehouse (Snowflake, BigQuery, Redshift) with the data types, chart of accounts mapping, and cost centre attribution your downstream reporting requires. The pipeline that currently takes a finance analyst half a day runs in under 30 minutes without manual intervention.
Automated assembly of management reports -- P&L by business unit, cash flow statement, balance sheet, working capital dashboard, and budget vs. actual variance analysis -- from your ERP, CRM, and operational systems, scheduled to land in recipients' inboxes before the Monday morning management meeting rather than arriving Wednesday after a weekend of manual compilation. Data extraction queries pull actuals from your ERP (SAP, Oracle, NetSuite), budget data from your planning tool (Anaplan, Adaptive Insights, Excel), and operational KPIs from your CRM (Salesforce, HubSpot) or data warehouse. Calculation logic encodes your firm's specific P&L structure, allocation rules, and intercompany treatment -- not a generic chart of accounts template. Report generation (WeasyPrint for PDF, OpenPyXL for Excel) produces formatted output matching your existing report template: board-ready layout, company logo, commentary placeholders for the CFO to complete, and comparison columns showing current period vs. prior period vs. budget. Delivery via email with personalised subject lines and body text, SharePoint with version management, or direct Power BI dataset push. Recipients get current-period data without asking the finance team for it.
Business Process Automation -- End-to-end workflow automation across your operation
Document Automation -- Automated document generation, routing, and approval workflows
Invoice Processing Automation -- AI-powered invoice intake, matching, and ERP posting
Reporting Automation -- Automated data pipelines replacing manually assembled reports
Process, current systems, and transaction volume. We'll design the automation and give you a fixed cost.
The highest-value finance automation targets are high volume, rule-based, and involve structured data from identifiable sources. Top processes: accounts payable (invoice extraction, PO matching, approval routing, payment processing), bank reconciliation (matching bank statement transactions to ledger entries, flagging exceptions), intercompany reconciliation, period-end journal entry posting, tax data compilation for filing, regulatory report assembly (CRR, DSCR, Pillar 3, SEC filings), and management report generation. Processes with high error costs -- regulatory submissions, tax filings, supplier payments -- have the clearest automation ROI.
We integrate with ERP and accounting platforms via API, direct database access, or UI automation depending on what your system exposes. Common integrations: SAP (FI/CO modules), Oracle Financials, Microsoft Dynamics 365 Finance, NetSuite, Sage, Xero, and QuickBooks. For invoice processing, we typically combine document AI (extracting structured data from PDF invoices) with ERP integration (posting the extracted data to the correct accounts). The integration approach is determined during scoping based on your specific ERP version and data model.
RPA handles the straight-through cases automatically -- the transactions that match, the invoices that have a PO, the reconciliation items that clear. Exceptions are flagged and routed to a human review queue with the context the reviewer needs to resolve them. A well-designed finance RPA system aims for 80--90% straight-through processing, with human effort focused on the 10--20% that requires judgment. The exception handling design is as important as the automation logic -- we build both as part of the same system.
Finance automation must produce audit-ready output. Every bot action is logged -- what data was accessed, what decision was made, what system was updated, and when. Reconciliation outputs include the matching logic and any manual overrides. Period-end close automation maintains a timestamped record of each close task. This audit trail is more complete and consistent than manual processes, which often rely on individual staff members remembering what they did and documenting it after the fact. We build audit logging as a core requirement, not an afterthought.
A focused finance automation system -- one process automated (e.g., AP invoice matching and approval routing), including bot development, testing in your environment, and deployment -- typically runs $20,000--$50,000. Multi-process programmes covering AP, reconciliation, and period-end close run $50,000--$130,000. Cost depends on the number of processes, ERP complexity, and the sophistication of the exception handling required. We scope every project before pricing it.
Work with us
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