Reconciling Invoices and Bank Transactions

Automates the matching of payments to invoices, detects discrepancies, and keeps ERP records up to date for more accurate cash flow tracking.

Key Features

Automated invoice matching

Automatically matches invoices with related bank transactions, cutting down on manual work and speeding up reconciliation.

Intelligent reference matching

Uses AI to match payment details like invoice numbers or vendor names, even when there are minor mismatches.

Partial and multi-invoice payments

Handles partial payments and single payments split across multiple invoices, ensuring accurate matching and allocation.

Anomaly detections

Spots differences between invoices and bank transactions and flags them for quick review.

Customizable reconciliation rules

Lets teams set matching rules based on business policies, like tolerance limits or fields to prioritize.

Comprehensive audit trails

Captures detailed logs of all payment activity, both user and system actions, to ensure full traceability and compliance.

KEY BENEFITS

Payment Co-Pilot boosts cash flow by timing payments for discounts, routes approvals automatically for same-day releases, supports ACH, checks, and wire transfers with a full audit trail—delivering accurate, secure payments and tighter spend control.

10%

Cash outflow

Co-pilot optimizes payment timings and methods, analyzing payment terms, discounts, penalties and, cost of capital

Vendor satisfaction

Vendors have higher satisfaction as they know real-time status of invoice processing and payments

Auditability

Human errors

Approvals

Reconciliations & other KPIs

Before and After Hyperbots Payments Co-Pilot

Why Hyperbots Agentic AI Platform?

Why choose hyperbots agentic AI: finance-first, accurate, adaptable AI

Finance specific

Hyperbots Agentic AI platform specializes exclusively in finance and accounting intelligence, leveraging millions of data points from invoices, statements, contracts, and other financial documents. No other platform has such large pretrained models on F&A data.

Best-in-class accuracy

Hyperbots achieves 99.8% accuracy in converting unstructured data to structured fields through a multimodal MOE model integrating LLMs, VLMs, and layout models. With contextual validation and augmentations, the platform ensures 100% accuracy for deployed agents.

Synthesis of unstructured and strutured finance data

Hyperbots agents emulate finance professionals to autonomously perform F&A tasks by reading and writing data like COA, expenses, and vendor masters from core accounting systems and integrating it with unstructured data from financial documents such as invoices, POs, and contracts.

Pre-trained agents with state of the art models

Hyperbots' Agentic platform, pre-trained on millions of financial documents like invoices, bills, statements, and contracts, ensures seamless integration, high accuracy, and adaptability to any accounting content, form, layout, or size from day one.

Company specific inference time learning

Hyperbots' Agentic platform employs state-of-the-art Auto ML pipelines with techniques like reinforcement learning to enable inference-time learning for tasks such as GL recommendation and cash outflow forecasting, ensuring continuous improvement and adaptability.

FAQs: Reconciliation of Bank Statements

Does the Co-pilot support reconciliation for partial or multi-invoice payments?

Absolutely, it supports reconciling partial payments or single payments allocated to multiple invoices, like distributing a $10,000 payment between two invoices of $6,000 and $4,000.

How does the Co-pilot automate invoice matching with bank transactions?

The Co-pilot automatically matches invoices with corresponding payment transactions in bank statements, minimizing manual effort, such as reconciling a $5,000 invoice with a payment transaction of the same amount.

Can the Co-pilot handle discrepancies in transaction references?

Yes, the Co-pilot uses AI for intelligent reference matching, resolving discrepancies.

How does the Co-pilot detect anomalies during reconciliation?

It identifies mismatches or unrecognized payments in bank statements, flagging them for review, such as detecting an unexpected payment and alerting the finance team.

Can reconciliation rules be customized to suit company policies?

Yes, the Co-pilot allows configuration of matching rules, such as setting tolerances for minor discrepancies or prioritizing specific fields like invoice numbers or payment references.

Designed by CFOs for CFOs

We worked with several CFOs to solve the right problems.

Hear what they have to say!

Designed by CFOs for CFOs

We worked with several CFOs to solve the right problems.

Hear what they have to say!

Ready to take the next steps?

Book a demo with one of our Financial Technology Consultants to get started!