AI inside Launches Financial Statement Processing Solution for Financial Institutions—Achieving Automation from Financial Statement Digitization to Screening System Registration
AI inside Launches Financial Statement Processing Solution for Financial Institutions
📋 Article Processing Timeline
- 📰 Published: March 28, 2026 at 00:27
- 🔍 Collected: March 28, 2026 at 21:59 (21h 32m after Published)
- 🤖 AI Analyzed: April 15, 2026 at 02:22 (412h 22m after Collected)
AI inside Inc. (President and CEO: Taku Toguchi, Headquarters: Minato-ku, Tokyo, hereafter 'AI inside') announces the launch of a solution that digitizes financial statement processing for financial institutions with high accuracy and automates the registration into screening systems.
This service utilizes the proprietary LLM 'PolySphere-4' to accurately digitize complex financial statements, which have different formats for each company. Furthermore, an AI agent automatically links the read results to the subsequent screening system, automating the entire workflow for financial institutions, from reading financial statements to system registration.
Service Site: https://go.inside.ai/finance
## Background of the Launch
In the loan screening operations of financial institutions, the daily task involves checking financial information such as sales, operating profit, ordinary profit, and net assets from financial statements submitted by companies, and inputting this data into a screening system.
However, financial statements have formats that differ from company to company, and many cases involve complex structures with hierarchical account structures, subtotals, breakdowns, and multi-year comparisons, posing a challenge for stable reading with conventional AI-OCR. Additionally, the process of registering data into the screening system required data entry on multiple screens, contributing to operational workload and input errors.
This service uses the proprietary LLM 'PolySphere-4' to understand the overall structure and context of the document to read the necessary information. It is particularly capable of digitizing financial statements that include hierarchical account structures, subtotals, and breakdowns while preserving the structure. Furthermore, an AI agent automatically links the extracted data to the screening system via API, automating the entire workflow from reading financial statements to system registration.
## Use Case
### Labor Saving in Loan Screening Operations
In loan screening operations, the work involves checking financial statements submitted by companies and inputting financial data such as sales, operating profit, and net assets into the screening system. Because the format varies for each company, the confirmation and transcription work could take 5 to 7 hours a day in some cases.
With this service, the AI agent automatically extracts and digitizes the necessary items from the financial statements and executes the registration process into the screening system. This reduces the working time to about 1 to 2 hours per day, making it possible to cut down on about 100 hours of work per month.
This service utilizes the proprietary LLM 'PolySphere-4' to accurately digitize complex financial statements, which have different formats for each company. Furthermore, an AI agent automatically links the read results to the subsequent screening system, automating the entire workflow for financial institutions, from reading financial statements to system registration.
Service Site: https://go.inside.ai/finance
## Background of the Launch
In the loan screening operations of financial institutions, the daily task involves checking financial information such as sales, operating profit, ordinary profit, and net assets from financial statements submitted by companies, and inputting this data into a screening system.
However, financial statements have formats that differ from company to company, and many cases involve complex structures with hierarchical account structures, subtotals, breakdowns, and multi-year comparisons, posing a challenge for stable reading with conventional AI-OCR. Additionally, the process of registering data into the screening system required data entry on multiple screens, contributing to operational workload and input errors.
This service uses the proprietary LLM 'PolySphere-4' to understand the overall structure and context of the document to read the necessary information. It is particularly capable of digitizing financial statements that include hierarchical account structures, subtotals, and breakdowns while preserving the structure. Furthermore, an AI agent automatically links the extracted data to the screening system via API, automating the entire workflow from reading financial statements to system registration.
## Use Case
### Labor Saving in Loan Screening Operations
In loan screening operations, the work involves checking financial statements submitted by companies and inputting financial data such as sales, operating profit, and net assets into the screening system. Because the format varies for each company, the confirmation and transcription work could take 5 to 7 hours a day in some cases.
With this service, the AI agent automatically extracts and digitizes the necessary items from the financial statements and executes the registration process into the screening system. This reduces the working time to about 1 to 2 hours per day, making it possible to cut down on about 100 hours of work per month.