FP&A teams often face the challenge of analyzing large amounts of financial data to spot outliers. Reviewing all the data manually is time-intensive and inefficient, delaying decisions that rely on accurate insights.

What’s new?

We are launching our Abacum Intelligence anomaly detection feature to empower teams like yours to automatically identify and address unusual patters in actuals data so that you can proactively explore outliers and take corrective actions if needed.

How does it work?

There are two modes of operation:

1. Automated anomaly detection: You can enable anomaly detection for specific variable so that every time this data is updated due to an actuals change anomaly detection model will be run to check if there is any outlier. You can also adjust “lookback” setting, which allows you to define how many months of historical data the AI will analyze to establish a baseline for normal behavior.
2. Ad-hoc anomaly detection: You can additionally activate initiative detection manually by selecting the “Detect data anomalies” action for specific variables.

Once anomalies have been detected, you can resolve these anomalies. The resolution workflow works like this:

• Notifications alert you when anomalies are detected.
• Review and resolve anomalies directly in the activity sidebar by marking them as resolved with a predefined reason.
• You can choose between permanent or transient resolutions, providing clarity for recurring or one-time issues.

Learn more about this in the academy: AI Anomaly Detection.

This feature is being rolled out gradually to our customers. If you don’t see it in your account yet, don’t hesitate to contact your customer success manager, and we’ll be happy to activate it for you.