AI Risk Indicator

AI Risk Indicator

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This page describes the Beta Artificial Intelligence (AI) Risk Indicator that Tradecloud is running with selected customers.
The AI Risk Indicator is only available on Tradecloud One. To participate in the Beta programme, you can submit your request to

What is the AI Risk Indicator?

The AI Risk Indicator calculates the probability of an exception occurring for a new order line, issued to the supplier. An exception is defined as:

  • A supplier proposes changes for an issued line
  • A supplier rejects an issued line

The outcome of the calculation is presented as a percentage that indicates the probability of an exception.
A 90% probability indicates that our AI Risk Indicator expects that there is 90% chance that the supplier will either reject the issued line, or propose changes.

How is this risk calculated?

The AI Risk Indicator is trained using the state-of-the-art Machine Learning (ML) and AI algorithms, based on all order event data available in Tradecloud One. Any sensitive or personal data is obfuscated and cannot be exploited.

It will dynamically learn what information is most relevant for predicting the risk. It could be that for your order lines, the item details may be significant, the requested delivery schedule, or perhaps the destination. Or perhaps it is a combination of all of these. The AI Risk Indicator is able to detect patterns in your order event data and leverage this to provide an accurate prediction.

What are the benefits for your company?

Tradecloud is exploring the benefits that can be brought to our customers with the help of AI.
The idea is that AI provides our customers with tools to pro-actively handle specific order lines even before an exception happens. This will allow our customers to address disruptions in the supply chain as early as possible, when the impact of such a disruption is still low.

What next?

User data and actual feedback from interviews will be collected to evaluate the usage and benefits of the AI Risk Indicator. Based on the evaluation, next steps can be determined according to the needs of the customers.

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