Host: The Japanese Society for Artificial Intelligence
Name : The 39th Annual Conference of the Japanese Society for Artificial Intelligence
Number : 39
Location : [in Japanese]
Date : May 27, 2025 - May 30, 2025
This study explored AI's potential to streamline accounting at Shinshu University, addressing labor shortages due to Japan's demographic shift. Using accounting data (April 2020 - December 2023, partially excluded), a BERT-based AI model (UiPath AI Center) was employed. Data from April 2020 to December 2022 trained the model, from January to December 2023 served as evaluation data. Evaluated different fine-tuning patterns, including product name and vendor consideration. Evaluation metrics were AI-human agreement rates (count and amount-based) and AI confidence. The count-based agreement rate exceeded the 85.29% benchmark from previous research. Limiting transactions to under ¥100,000 achieved the same rate for amount-based agreement. Confidence and count-based agreement correlated proportionally, but this was less clear for amount-based agreement. However, the correlation appeared when transactions were limited to under ¥100,000. AI can thus streamline accounting for transactions under ¥100,000.
