Access to latest Machine Learning and AI Research for Shared Services leaders and the S2P/P2P/AP Global Process Owner
Consider Solutions is undertaking extensive applied research in the area of advanced machine learning analytics for key financial processes.
We have evolved a proof of concept using the latest techniques in artificial intelligence/cognitive computing that applies statistical models embedded in software to learn about data patterns and automatically detect outliers in transactions and data, representing unusual process operation, error, waste and potential fraud.
The goal is to increase the precision, dramatically simplify and reduce the cost of identifying anomalies in business processes and thus reduce the cost of process operation and assurance through increased standardization.
Our current focus is on the Source to Pay / Purchase to Pay / Accounts Payable process.
Machine Learning software is very different to the traditional programmatic/scripting approach to defining rules and conditions in systems. With Machine Learning, a discipline of Artificial Intelligence, the software is trained and evolves itself to learn from large bodies of data to understand complex patterns and develop themes and schemes that expose unusual outliers and anomalies. Instead of using human intelligence to define logic that is based on previous experience, Machine Learning evolves with the data to highlight exceptions we may not have thought of. The volume, velocity, variety and complexity of the big data world has further increased the potential of machine learning—and the need for it. It’s early usage has been in consumer applications for image recognition, the driverless car, recommendation systems, sentiment analysis, consumer fraud detection, behaviour prediction and in some services of Google, Amazon, Apple, Facebook et al.
We would like to invite you to take part in this research for your S2P/P2P cycle.
There is no charge!
If you want to experience the next generation of P2P analysis of your master data and transaction trends, outliers and exceptions, leave your name and email below and we will be in touch to share more information and discuss what is involved. It requires very little effort from you, typically a total of 4 hours over 4 weeks, including a detailed review of findings.
It doesn’t matter what ERP system or systems you use, whether SAP, Oracle, Microsoft, Infor or any other.
It’s all about the data…
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Thank you, we will be in touch shortly.