Manual invoice processing has long been a burden for finance teams, demanding time-intensive data entry and constant vigilance for errors. Teams typically handle invoices individually, downloading files in different formats and currencies, and then painstakingly rekeying data into spreadsheets.
After this, the data must be validated and finally uploaded into accounting systems for reconciliation—leaving plenty of room for mistakes and inefficiencies, claims SS&C BluePrism.
The SS&C Invoice Data Agent aims to solve this challenge using generative AI and intelligent automation. By significantly reducing manual input—by over 90%—the solution accelerates turnaround times while minimising errors. AI is particularly well-suited for processing vast quantities of structured and unstructured data, making it an ideal fit for invoice workflows.
At the heart of the solution is a large language model (LLM) integrated with natural language processing (NLP). The Invoice Data Agent ingests invoice documents in real time, regardless of format, and assigns them to the correct client. It is capable of splitting invoices if necessary and automatically extracting all relevant line items and data points before preparing them for entry into enterprise systems.
Crucially, the tool ensures data integrity by checking for duplicates, missing items or incorrect information before progressing to reconciliation. Benefits include quicker net asset value (NAV) calculations, fewer errors, improved audit trails and seamless integration with existing ERP systems—all underpinned by robust AI governance and deployment in a secure cloud environment.
SS&C built and validated the Invoice Data Agent within its own Innovation Lab. As “customer zero”, the company ensures its AI tools are tested within live business environments before release, aiming to streamline clients’ AI transformations and reduce deployment risks.
While the blog focuses on invoicing, SS&C stresses that AI’s impact goes far beyond a single process. The move toward agentic process automation means deploying AI agents into end-to-end workflows, where they can execute increasingly complex tasks. These agents operate with growing autonomy, making decisions without human intervention while maintaining compliance through strong governance structures.
Vertical AI agents—such as the Invoice Data Agent—are trained with specific domain knowledge, allowing them to deliver high precision on narrowly focused tasks, such as fraud detection or invoice validation in the financial sector.
SS&C encourages firms to take strategic steps before implementing AI. This includes assessing vendor capabilities, deployment options, budgets and staff training needs. Identifying high-impact use cases like invoicing is a strong first step. SS&C’s own AI Gateway ensures secure, governed connections between AI models and business systems.
Real-world examples show how this automation is delivering tangible results. Laya Healthcare, for instance, implemented SS&C | Blue Prism® Decipher IDP to detect duplicate invoices using optical character recognition and structured data analysis. This allowed claims to be processed and closed without human involvement, drastically improving efficiency.
In another example, a global retailer adopted the same technology to accelerate vendor invoice payments. With automated data extraction and validation processes in place, the retailer now processes nearly 7,000 invoices per week across various formats and languages—demonstrating the scalability of the solution.
As companies look to harness the next wave of enterprise AI, tools like the Invoice Data Agent represent a practical and scalable way to boost operational efficiency.
Find the link to the full post here.
Copyright © 2025 FinTech Global
Copyright © 2018 RegTech Analyst
