Check Reconciliation

Hyperbots Payment Co-pilot streamlines the reconciliation of checks, their presentation status, and associated invoices with real-time updates, anomaly detection, and customizable matching rules.

Key Features

Check status monitoring

Tracks the status of issued checks, such as presented, cleared, or pending, by integrating with bank feeds or manual updates.

Invoice and check matching

Matches checks to corresponding invoices to ensure accurate allocation and payment reconciliation.

Anomaly detection

Flags discrepancies such as mismatched amounts, duplicate check entries, or unrecognized checks in bank statements.

Stop payment integration

Supports integration with stop payment processes, allowing users to halt specific checks and manage reissuance if needed.

Detailed audit trails

Maintains comprehensive logs of all check-related actions, including issuance, status updates, and invoice matches.

Customizable matching rules

Allows configuration of reconciliation rules to align with company-specific policies, including tolerances for matching amounts.

10%

Cash outflow

Co-pilot optimizes payment timings and methods, analysing

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

VALUE PROPOSITION

Why Hyperbots Payments
Co-Pilot?

Hyperbots Payments Co-pilot automates payment processing with features like timing recommendations, approval workflows, and multi-method support (ACH, checks, wire transfers), ensuring secure, efficient, and compliant financial operations.

Before and After Hyperbots Payments Co-Pilot

FAQs: Check Reconciliation

How does the Co-pilot monitor the status of issued checks?

The Co-pilot tracks the status of issued checks, such as presented, cleared, or pending, by integrating with bank feeds or using manual updates, ensuring transparency in payment processes.

Can the Co-pilot match checks to corresponding invoices?

Yes, it matches checks to invoices for accurate allocation and reconciliation, supporting scenarios like linking a single check to multiple invoices or handling partial payments.

How does the Co-pilot handle anomalies in check transactions?

It flags discrepancies, such as mismatched amounts, duplicate entries, or unrecognized checks in bank statements, alerting the finance team for further review.

Does the Co-pilot integrate with stop payment processes?

Yes, it supports stop payment integration, allowing users to halt specific checks and manage reissuance in cases of loss or fraud.

Can check matching rules be customized?

Yes, the Co-pilot allows configuration of reconciliation rules, including tolerances for matching amounts, ensuring alignment with company-specific policies.

Why Hyperbots Agentic AI Platform?

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.

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!