ACES and SMBC Co-Develop AI Application for Corporate Sales
ACES and Sumitomo Mitsui Banking Corporation (SMBC) have co-developed and launched a specialized AI application that structures bank-specific knowledge to support corporate sales proposals.
📋 Article Processing Timeline
- 📰 Published: April 24, 2026 at 19:00
- 🔍 Collected: April 24, 2026 at 10:31
- 🤖 AI Analyzed: April 25, 2026 at 02:54 (16h 22m after Collected)
ACES Inc. (Headquarters: Bunkyo-ku, Tokyo; Representative Director: Koichiro Tamura; hereinafter 'ACES') announces that it has co-developed an AI application with Sumitomo Mitsui Banking Corporation (President and CEO: Akihiro Fukutome; hereinafter 'SMBC') to support the proposal activities of corporate sales representatives. The application is now being utilized within SMBC.
This application supports the entire workflow of corporate sales representatives, from interview preparation to the materialization of proposals. By combining SMBC's customer interaction data and sales insights accumulated over many years with ACES's knowledge structuring and AI design technologies, it enables practical support reflecting SMBC's specific product knowledge and sales methodologies—something difficult to achieve with generic AI tools.
■ Background
In the corporate sales of financial institutions, as customers' management issues and the provided solutions become more complex, more time is required for research and preparation for proposals. As a result, a structural issue arises where the quality and speed of proposals tend to depend heavily on the individual representative's experience and skills.
Furthermore, product-related materials and information on points to note during proposals are scattered across various departments, making it difficult to quickly access necessary information at times. Even if the information itself is accumulated within the company, there was a limit to how effectively sales representatives could cross-reference and utilize it in their daily proposal preparations.
In response to these challenges, SMBC has been developing an AI utilization foundation and working to expand AI use and improve literacy among its employees. To take AI utilization to the next level based on this accumulation, they co-developed an AI application with ACES that directly supports the proposal activities of sales representatives by leveraging the knowledge and customer interaction data accumulated on the frontlines of corporate sales. By breaking away from person-dependent operational structures and raising the baseline of proposal capabilities across the organization, they aim to provide more rapid and accurate value.
In this project, ACES supported the sophistication of corporate sales by structuring the product knowledge and sales insights accumulated within SMBC and embedding them into the AI in a way that can be used naturally in the field. This embodies ACES's concept of 'Expert AI'*, which supports practical operations by utilizing company-specific knowledge and frontline know-how.
■ ACES's Role and Technical Features
1. Structuring knowledge and information in financial operations
Materials related to financial products and proposal-related information existed across various departments in diverse formats, meaning they were not in a state where AI could easily cross-reference and utilize them. Working with each department within SMBC, ACES organized and structured this information—such as product characteristics, application conditions, and points to note during proposals—establishing it as a knowledge base usable by both AI and human representatives. This allowed sales representatives to quickly access necessary materials and related information from the application, significantly reducing the information search burden required for proposal preparation.
2. Systematizing sales insights and implementing them into AI
Through interviews with SMBC's sales representatives, ACES organized frontline insights—such as how to assess customer issues, criteria for product selection, and key points during proposals—and reflected them in the AI's inference and presentation logic. This implemented a mechanism that suggests candidate products and services according to the customer's management issues and supports the organization and consideration of the proposal's direction.
3. Application design and development for continuous field use
To ensure it can be used effortlessly in actual operations, the design and development included operability, user flow, and the method of information presentation. Through close requirements definition and field testing with SMBC, they achieved application quality predicated on use in daily operations.
■ Application Overview
This application uses AI to support the entire process for corporate sales representatives, from interview preparation to proposal materialization. The main functions are as follows:
- Organizing Latent Needs and Discussion Points: Based on the dialogue with the customer and the representative's hypotheses, the AI organizes expected management issues and comprehensively presents optimal product and service candidates. By linking with a knowledge base including SMBC's unique customer interaction data and sales insights, it enables industry-specific reasoning and support based on proprietary insights that cannot be achieved with generic AI tools. This makes it easier even for less experienced sales representatives or those recently transferred to consider approaches and proposal directions, leading to improved proposal capabilities across the organization.
- Supporting Proposal Preparation: The AI backs up comparative examinations and proposal preparation by sales representatives based on the latest product-related information and points to note during proposals. By streamlining access to necessary information, it reduces the time required for research and internal inquiries, allowing more time to be allocated to dialogue with customers and grasping essential issues.
■ Future Outlook
This application supports the entire workflow of corporate sales representatives, from interview preparation to the materialization of proposals. By combining SMBC's customer interaction data and sales insights accumulated over many years with ACES's knowledge structuring and AI design technologies, it enables practical support reflecting SMBC's specific product knowledge and sales methodologies—something difficult to achieve with generic AI tools.
■ Background
In the corporate sales of financial institutions, as customers' management issues and the provided solutions become more complex, more time is required for research and preparation for proposals. As a result, a structural issue arises where the quality and speed of proposals tend to depend heavily on the individual representative's experience and skills.
Furthermore, product-related materials and information on points to note during proposals are scattered across various departments, making it difficult to quickly access necessary information at times. Even if the information itself is accumulated within the company, there was a limit to how effectively sales representatives could cross-reference and utilize it in their daily proposal preparations.
In response to these challenges, SMBC has been developing an AI utilization foundation and working to expand AI use and improve literacy among its employees. To take AI utilization to the next level based on this accumulation, they co-developed an AI application with ACES that directly supports the proposal activities of sales representatives by leveraging the knowledge and customer interaction data accumulated on the frontlines of corporate sales. By breaking away from person-dependent operational structures and raising the baseline of proposal capabilities across the organization, they aim to provide more rapid and accurate value.
In this project, ACES supported the sophistication of corporate sales by structuring the product knowledge and sales insights accumulated within SMBC and embedding them into the AI in a way that can be used naturally in the field. This embodies ACES's concept of 'Expert AI'*, which supports practical operations by utilizing company-specific knowledge and frontline know-how.
■ ACES's Role and Technical Features
1. Structuring knowledge and information in financial operations
Materials related to financial products and proposal-related information existed across various departments in diverse formats, meaning they were not in a state where AI could easily cross-reference and utilize them. Working with each department within SMBC, ACES organized and structured this information—such as product characteristics, application conditions, and points to note during proposals—establishing it as a knowledge base usable by both AI and human representatives. This allowed sales representatives to quickly access necessary materials and related information from the application, significantly reducing the information search burden required for proposal preparation.
2. Systematizing sales insights and implementing them into AI
Through interviews with SMBC's sales representatives, ACES organized frontline insights—such as how to assess customer issues, criteria for product selection, and key points during proposals—and reflected them in the AI's inference and presentation logic. This implemented a mechanism that suggests candidate products and services according to the customer's management issues and supports the organization and consideration of the proposal's direction.
3. Application design and development for continuous field use
To ensure it can be used effortlessly in actual operations, the design and development included operability, user flow, and the method of information presentation. Through close requirements definition and field testing with SMBC, they achieved application quality predicated on use in daily operations.
■ Application Overview
This application uses AI to support the entire process for corporate sales representatives, from interview preparation to proposal materialization. The main functions are as follows:
- Organizing Latent Needs and Discussion Points: Based on the dialogue with the customer and the representative's hypotheses, the AI organizes expected management issues and comprehensively presents optimal product and service candidates. By linking with a knowledge base including SMBC's unique customer interaction data and sales insights, it enables industry-specific reasoning and support based on proprietary insights that cannot be achieved with generic AI tools. This makes it easier even for less experienced sales representatives or those recently transferred to consider approaches and proposal directions, leading to improved proposal capabilities across the organization.
- Supporting Proposal Preparation: The AI backs up comparative examinations and proposal preparation by sales representatives based on the latest product-related information and points to note during proposals. By streamlining access to necessary information, it reduces the time required for research and internal inquiries, allowing more time to be allocated to dialogue with customers and grasping essential issues.
■ Future Outlook