Seven Bank Accelerates AI-Driven Innovation with HULFT Square

Challenge

Fragmented Data Infrastructure Hindered AI Innovation

Seven Bank’s existing data infrastructure relied on one-to-one integration approaches that created bottlenecks for data accessibility and analysis. Their generative AI initiatives required a platform that could serve as a secure bridge for AI verification projects while maintaining enterprise-grade security. 

Their accounting system used manual processes that created dependencies on individual staff members and introduced potential points of failure. The company needed technology that would democratize data access while ensuring reliability across on-premise systems to cloud platforms. 

Solution

Cloud-Based Integration Platform Enables Secure AI Implementation

Seven Bank selected HULFT Square, a cloud-based data integration platform (iPaaS), as the foundation for both their accounting system modernization and generative AI verification projects. The platform’s ability to integrate across all system environments provided the flexibility required for Seven Bank’s complex infrastructure. 

HULFT Square’s Japanese-developed architecture offered advantages in user interface design and customer support. The solution incorporates over 30 years of file integration technology and includes job-setting functionality that enabled Seven Bank to execute multiple processes sequentially. 

For their “7Bank-Brain” generative AI interface, Seven Bank used HULFT Square to establish a secure connection between internal systems and Microsoft Azure OpenAI Service. The platform manages natural language query processing, SQL generation, data retrieval, and analysis execution while maintaining data security.

Results

Automated Workflows Transform Decision-Making Capabilities

HULFT Square enabled Seven Bank to achieve comprehensive data integration across all system environments, dramatically simplifying their previously complex data landscape. The platform’s intuitive interface facilitated in-house development capabilities, reducing dependency on external development partners and accelerating project timelines. The accounting system modernization eliminated manual processes and reduced individual staff dependencies, resulting in more reliable financial operations. 

The integration with Microsoft Azure OpenAI Service successfully enabled natural language data analysis capabilities, allowing business users to query complex datasets without SQL expertise. Seven Bank demonstrated improved loan screening accuracy by combining traditional financial data with retail shopping data, enabling them to serve previously underserved market segments such as gig workers. 

The platform positioned Seven Bank for their planned company-wide generative AI deployment in fiscal year 2025, providing the secure, scalable infrastructure necessary for enterprise AI adoption.

“Due to the complexity and security of the implementation, we had a hard time getting started on verifying data analysis with natural language. We considered multiple tools, but were hesitant because they all required uploading the data once to the vendor. When Saison Technology heard about this and made a proposal, we found that the analytical environment we were looking for could be implemented using HULFT Square, so we decided to proceed with development. We are so glad that we introduced HULFT Square.”

Yoshiyuki Nakamura, General Manager of the AI Data Strategy Division, Seven Bank

Future Vision

Enterprise-Wide AI Analytics Drive Strategic Innovation

Seven Bank envisions HULFT Square as the foundation for dramatically expanded AI and data analytics capabilities across their global operations. The company plans to extend natural language analytics to their billion-transaction ATM dataset, which would provide unprecedented insights into customer behavior patterns across urban and rural markets. This analysis capability could inform strategic decisions about partner bank relationships, fee structures, and service optimization across their international footprint. 

The planned integration of globally deployed ATM data represents a significant expansion of Seven Bank’s analytical capabilities, potentially revealing regional usage patterns and customer preferences that could drive localized service innovations. Seven Bank envisions a future where complex business questions can be answered instantly during management meetings through natural language queries, fundamentally transforming the pace and quality of strategic decision-making. 

“Just by asking during a meeting, ‘What are the trends in debit card usage of customers with a deposit balance above a certain amount?’ or ‘What are the characteristics of this customer group?’ we will get an answer, which should dramatically speed up the decision-making process. We expect this to lead to major innovation,” explains Nakamura.