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Money Forward Consulting Co., Ltd., a group company of Money Forward, Inc., has begun offering an “AI Anomaly Detection Function” for its business management and budgeting system, “Sactona.” This function allows AI to instantly identify anomalies in monthly performance data, significantly streamlining data analysis and verification processes.
The “AI Anomaly Detection Function” automatically analyzes historical data from the past 12 months to detect sudden data fluctuations and deviations from predicted values. If a threshold is exceeded and an anomaly is detected, an alert will be issued along with a display of the reason for the detection.
This automates the process of checking budget-to-actual variances and year-on-year comparisons, which were previously calculated manually, preventing the oversight of anomalies due to human error. It significantly reduces the workload of those responsible for checking, while also supporting improved analytical accuracy and faster management decision-making.
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In today’s rapidly changing business environment, companies are required to quickly identify risks and changes and make rapid decisions. However, in budget and performance management, a significant amount of time is spent identifying input errors and sudden fluctuations from vast amounts of monthly performance data, leading to major challenges such as overlooking anomalies and reliance on individual expertise for analysis.
This feature solves these problems. By leveraging Sactona’s strengths in handling complex and large organizational structures, it automates cross-functional anomaly detection that was difficult to perform visually, providing an environment where personnel can focus on more advanced analysis and high-value tasks.
In the future, we plan to implement a function that automatically generates reports based on instructions in natural language. Through the continuous expansion of AI functions, Sactona aims to further improve convenience for user companies and enable more advanced business management.
SOURCE: PRTimes
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