Early Payments Recommendations
Hyperbots Payment Co-pilot analyzes early payment discounts, payment terms, cost of capital, and vendor criticality to recommend optimal payment timings.
Key Features
Early payment discount analysis
Extracts early payment discount terms from invoices and POs to calculate the financial benefits of early payment.
Payment term extraction and evaluation
Retrieves payment terms from invoices and POs to determine due dates and optimal payment schedules.
Cost-of-capital consideration
Analyzes the company’s cost of capital to evaluate the financial feasibility of taking early payment discounts.
Vendor criticality assessment
Considers the importance of the vendor to the company’s supply chain and business continuity when recommending payment timings.
Data integration for holistic recommendations
Combines insights from invoices, POs, and ERP data to provide comprehensive payment timing recommendations.
Real-time decision making
Provides real-time payment timing recommendations to ensure timely decision-making and maximize financial benefits.
Actionable insights for payment approvals
Presents clear, data-backed recommendations to decision-makers, ensuring informed payment approvals.
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: Early Payments Recommendations
How does the Co-pilot analyze early payment discounts?
The Co-pilot extracts early payment discount terms from invoices and POs, calculating potential financial benefits, such as savings from terms like "2/10 Net 30."
What payment terms does the Co-pilot evaluate?
It retrieves and evaluates payment terms like "Net 45" from invoices and POs, determining optimal schedules for early or on-time payments.
How does cost of capital factor into payment recommendations?
The Co-pilot analyzes the company’s cost of capital to assess whether pursuing early payment discounts is financially beneficial compared to holding cash.
Does the Co-pilot consider vendor importance in recommendations?
Yes, the Co-pilot assesses vendor criticality to the company’s operations, prioritizing early payments for strategic or essential vendors.
How does the Co-pilot provide holistic payment recommendations?
It integrates data from invoices, POs, and ERP systems to align recommendations with financial policies and cash flow conditions.
Can the Co-pilot make real-time payment recommendations?
Absolutely, the Co-pilot provides real-time, actionable insights, ensuring timely decisions on early payment opportunities to maximize financial benefits.
Give an example of when an early payment discount might not make sense.
If the discount is "0.5/30 Net 45" and the company’s cost of capital is 10% annually, early payment would not make sense. The annualized discount is 6% (0.5% × 12), which is lower than the cost of capital, making it uneconomical to pay early.
What to do when an early payment discount makes sense but the company doesn’t have enough cash to pay on time?
The Co-pilot can identify alternative financing options, such as short-term credit or supplier financing, to leverage the discount. It also provides insights on prioritizing payments to maximize financial benefits within available cash flows.
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!