AI in Accounting and Accounts Payable │ Rillion Prime Demo

Introduction

In this article, we introduce Rillion's AI machine learning functionality within Rillion Prime, designed to streamline the coding of incoming invoices. By leveraging historical data, this solution helps automate the coding process, improving efficiency and accuracy in accounts payable.

How It Works

The machine learning AI solution employs a systematic approach to invoice processing. Initially, we export your historical invoices into our model, allowing us to create a tailored machine learning model specifically for your organization. When a new invoice arrives in the invoice log, it undergoes a matching process.

Invoice Matching: The first step is to attempt to match the incoming invoice to an existing order or contract. If a match is found, the coding is directly derived from that.
AI-Powered Coding: If the invoice cannot be matched to any order or contract, the AI system utilizes your historical data to predict the appropriate coding. Each invoice receives a suggestion based on this analysis.
Approval Workflow: Once the coding suggestion is made, the invoice can be sent out for approval. Users can review the proposed coding, and if adjustments are made, this feedback is sent back to the AI engine to continually refine and improve its predictions.

Application Demonstration

Let's explore how this works within the Rillion Prime application. Once an invoice arrives, it appears in the invoice log where the matching and coding process occurs.

For example, consider an invoice that has been processed with AI matching:

The AI will provide a proposed coding, complete with a confidence percentage for each component of the coding.
In our example, the analysis might show a 98% confidence level for the account coding, but lower confidence in the cost center, indicating that further review is necessary.
Organizations can configure how to handle invoices depending on the confidence level, such as automatic approval or a review process within the accounts payable team.

Moreover, the AI can create multiple posting lines if necessary. However, there are limitations; as the number of lines increases, the confidence in prediction may decrease.

This AI machine learning functionality provides a powerful tool for automating account coding on invoices in Rillion Prime. By continuously learning from user interactions, the system becomes increasingly intelligent over time.

Thank you for taking the time to learn about our innovative AI solutions.

Keywords

AI
Machine Learning
Invoice Coding
Accounts Payable
Rillion Prime
Approval Workflow
Historical Data
Invoice Matching
Automation
Prediction

FAQ

Q1: How does Rillion Prime utilize AI for invoice processing?
A1: Rillion Prime uses AI to analyze historical data to suggest coding for incoming invoices. If no matching order or contract is found, it predicts coding based on past invoices.

Q2: What happens if the AI's coding suggestion is incorrect?
A2: If changes are made to the coding by any user, that information is sent back to the AI engine, which uses it to learn and improve future predictions.

Q3: Can the AI create multiple coding lines for an invoice?
A3: Yes, the AI can create more than one posting line if necessary, though its predictive confidence may be lower with many lines.

Q4: How can organizations manage invoices based on coding confidence levels?
A4: Organizations can set rules for handling invoices based on confidence levels, such as sending them directly for approval or requiring a review before proceeding.

Q5: What is the benefit of using Rillion Prime's AI functionality?
A5: The AI functionality enhances efficiency and accuracy in the accounts payable process by automating invoice coding and continuously learning from user feedback.