Asuene Expands SSBJ Compliance Features for 'ASUENE' CO2 Tracking and Reporting Cloud

## Asuene Enhances SSBJ Compliance Features

Asuene Inc. (Headquarters: Minato-ku, Tokyo; CEO: Kohei Nishiwada) has expanded the system features of its 'ASUENE' CO2 tracking, reduction, and reporting cloud platform to support SSBJ standards compliance.

These new features include AI-assisted disclosure document creation, financial impact assessment, and hourly electricity data integration. Companies can manage information organization, financial impact calculation, and disclosure document drafting within 'ASUENE,' reducing the time required for SSBJ compliance by up to 90%.

As a 'Climate AI' company, Asuene leverages its expertise in decarbonization and AI to reduce the practical burden of SSBJ compliance and support data-driven sustainability reporting.

### Background of Feature Expansion

Sustainability reporting requires not only calculating CO2 emissions but also explaining the impact of climate change on business and financial outcomes. SSBJ compliance specifically demands that companies organize emissions and financial data to craft disclosure documents that address both risks and opportunities.

In practice, this information is often scattered across various departments and documents. Manually reconciling reports, environmental data, and financial records is time-consuming. Furthermore, drafting documents that meet SSBJ standards requires specialized knowledge in sustainability reporting and decarbonization.

This update combines Asuene’s expertise with AI to streamline SSBJ compliance directly on the 'ASUENE' platform.

### Feature Overview

1. AI Disclosure Document Creation
By uploading existing materials such as securities reports to 'ASUENE,' AI extracts relevant SSBJ items to assist in creating disclosure documents. The AI identifies target items, organizes them by impact, risk, and opportunity, and generates draft answers matched to SSBJ requirements.

2. AI Financial Impact Assessment
This feature calculates and simulates climate-related financial impacts based on CO2 emissions, reduction targets, and internal carbon pricing (ICP). By comparing multiple scenarios, it visualizes costs and future financial impacts of reduction measures.

3. Hourly Electricity Data Integration
Integration with 30-minute interval electricity data allows management of hourly usage and renewable energy utilization. By syncing with environmental attribute data, it improves the accuracy of information regarding renewable energy use.