Reconciliation of Bank Statements
Hyperbots Payment Co-pilot automates the reconciliation of invoices with bank transactions, using Al for intelligent matching, anomaly detection, and real-time updates to ERP systems.
Key Features
Automated invoice matching
The co-pilot automatically matches invoices with corresponding payment transactions in bank statements, reducing manual effort.
Intelligent reference matching
Uses AI to match transaction references, such as invoice numbers, vendor names, or payment IDs, even with slight discrepancies.
Partial and multi-invoice payments
Supports reconciliation of partial payments or single payments covering multiple invoices, ensuring accurate allocation.
Anomaly detections
Identifies mismatches or discrepancies between invoices and bank transactions, flagging them for review.
Customizable reconciliation rules
Allows configuration of matching rules based on company policies, such as thresholds for tolerances or specific fields to prioritize.
Comprehensive audit trails
Maintains detailed logs of all payment actions, including user interactions and system actions, ensuring traceability and compliance.
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: 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.
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.
Ready to take the next steps?
Book a demo with one of our Financial Technology Consultants to get started!