AI Solutions for Financial Institutions

Megabanks, digital banks, regional banks, and AI solution providers for financial institutions

Chapter 1: Overview

1. Market Overview
   　　1.1. Definition of the Market for AI Solutions for Financial Institutions
   　　1.2. Areas of AI Adoption in the Financial Sector
   　　1.3. The Role of Generative AI, RAG, and AI Agents
2. Background and External Environment Shaping the Market
   　　2.1. Expansion of AI Use in Financial Institutions
   　　2.2. Full-Scale Adoption of Generative AI
   　　2.3. Advances in Data Utilization in Financial Operations
   　　2.4. AI Governance and Security
3. Progress in AI Adoption at Financial Institutions
   　　3.1. Support for Internal Operations, Such as Document Creation and Search
   　　3.2. Operational Support Utilizing RAG and Internal Data
   　　3.3. Application to Core Operations, Such as Lending, Credit Review, and Sales
   　　3.4. Use of AI in Customer Interactions
   　　3.5. Business Processes Handled by AI Agents
4. Structure of the AI Solutions Market for Financial Institutions
   　　4.1. Relationships Between Financial Institutions and AI Solution Providers
   　　4.2. In-House Development, Joint Development, and Use of External Services
   　　4.3. Expansion of Solutions Specialized for Financial Operations
5. Market Size
6. Market Outlook
   　　6.1. Platforms for Building and Managing AI Agents, and Development Support
   　　6.2. Expansion of Solutions Specialized for Lending Operations
   　　6.3. Integration with External AI at Customer Touchpoints
   　　6.4. Factors Limiting Market Growth

Chapter II: The Current State of the AI Solutions Market for Financial Institutions

1. Market Overview
   　　1.1. Overview
   　　1.2. Business Models
2. Business Performance Trends
3. Initiatives to Strengthen Business Operations
   　　3.1. Initiatives Related to AI Credit Assessment and AI Scoring
   　　3.2. Initiatives Related to AI for Loan Approval Document Preparation Support
   　　3.3. Initiatives Related to Retail AI
   　　3.4. Initiatives Related to Fraud Detection and Risk Management
   　　3.5. Initiatives Related to Generative AI and AI Agents
4. Perspectives on the Business Environment of Major Players
   　　4.1. Streamlining Credit Assessment and Addressing Labor Shortages at Regional
   　　　　Financial Institutions
   　　4.2. Demand for Fraud Detection in the Credit Card and Mortgage Sectors
   　　4.3. Changes in the Role of External Providers Amid the Proliferation and In-House
   　　　　Development of General-Purpose Generative AI
5. Challenges Facing Major Providers
   　　5.1. Securing Talent
   　　5.2. Adapting to Financial Institutions' System Environments
   　　5.3. Establishing Operational Frameworks on the Financial Institutions’ Side
   　　5.4. Ensuring Adoption on the Front Lines
   　　5.5. Clarifying Implementation Requirements and Costs
6. Outlook for Major Providers
   　　6.1. Service Expansion and Broadening of Sales Channels
   　　6.2. Integrated Support for Corporate Sales and Lending Processes by System
   　　　　Integrators
   　　6.3. Financial Institutions' External Sales and In-House Development, and the Role
   　　　　of External Providers
7. Market Size Trends and Forecasts
   　　7.1. Market Forecasts and Adoption Outlook
   　　7.2. Horizontal Expansion and Provider Differentiation Supporting Market Growth

Chapter III: Trends in Financial Institutions' AI Initiatives

1. Summary
   　　1. Status of AI and Generative AI Adoption
   　　2. AI Adoption by Business Type
   　　3. Major Areas of Application
   　　4. Changes in the Stages of AI Adoption
2. Megabanks
   　　1. Background and Objectives of AI Adoption
   　　2. Directions for AI Adoption
   　　　　2.1. Scope of AI Utilization
   　　　　2.2. Three Approaches to Building a Common AI Infrastructure
   　　　　　　2.2.1. MUFJ Bank’s AI Strategy and Direction
   　　　　　　2.2.2. Sumitomo Mitsui Banking Corporation’s AI Strategy and Direction
   　　　　　　2.2.3. Mizuho Bank’s AI Strategy and Direction
   　　　　2.3. Scope and Roles of AI Agents in Business Processes
   　　3. Key Initiatives
   　　　　3.1. Establishing a Common Operational Infrastructure for Internal Document
   　　　　　　Search
   　　　　3.2. Corporate Banking and Wealth Management: From Information Gathering
   　　　　　　to Proposal Preparation
   　　　　3.3. Lending and Credit Review: Support for Document Creation and
   　　　　　　Separation of Credit Decision-Making
   　　　　3.4. Customer Touchpoints: AI Responses Without Bank Employee Verification
   　　　　3.5. Scope of Automated Processing and Integration of Individual Tasks Using
   　　　　　　AI Agents
   　　4. AI Development and Implementation Framework
   　　　　4.1. Division of Roles Between Technical Organizations and Business
   　　　　　　Departments
   　　　　4.2. In-House Development and Collaboration with External Companies
   　　　　4.3. Expanding AI Investment and Developing the Human Resources and
   　　　　　　Organizational Structure to Support Operational Implementation
   　　5. Bottlenecks During Implementation
   　　　　5.1. Organizing Large Volumes of Internal Information and Ensuring Accurate
   　　　　　　Access
   　　　　5.2. Ensuring Accuracy and Establishing Verification Systems for Utilizing AI
   　　　　　　Responses in Banking Operations
   　　　　5.3. Ensuring Information Management and Response Quality in Customer-
   　　　　　　Facing AI Services
   　　　　5.4. Model Management and Governance Systems to Support the Expansion
   　　　　　　of AI Utilization
   　　6. Benefits of Implementation
   　　　　6.1. Expansion of AI Use and Progress in Operational Efficiency
   　　　　6.2. Benefits by Business Area
   　　　　6.3. Expansion of AI Investment and Realization of Economic Benefits
   　　　　　　6.3.1. MUFJ Bank's Perspective on Implementation Benefits
   　　　　　　6.3.2. Sumitomo Mitsui Banking Corporation’s Perspective on
   　　　　　　　　　Implementation Benefits
   　　　　　　6.3.3. Mizuho Bank’s Perspective on Implementation Benefits
   　　7. Challenges
   　　　　7.1. Expanding from Individual Task Efficiency to End-to-End Business
   　　　　　　Processes
   　　　　7.2. Utilization of Customer-Specific Information and Integration with
   　　　　　　Transaction Functions
   　　　　7.3. Establishment of a Management Framework to Support the Expanded
   　　　　　　Operation of AI Agents
   　　8. Outlook
   　　　　8.1. Expanded Application for AI Agents
   　　　　　　8.1.1. MUFJ Bank's Direction Regarding AI Agents
   　　　　　　8.1.2. Sumitomo Mitsui Banking Corporation's Approach to AI Agents
   　　　　　　8.1.3. Mizuho Bank's Direction Regarding AI Agents
   　　　　8.2. Enhancing Customer Touchpoints and Expanding to Individual Financial
   　　　　　　Services
   　　　　　　8.2.1. MUFJ Bank's Direction Regarding the Enhancement of Customer
   　　　　　　　　　Touchpoints
   　　　　　　8.2.2. Sumitomo Mitsui Banking Corporation's Direction Regarding the
   　　　　　　　　　Enhancement of Customer Touchpoints
   　　　　　　8.2.3. Mizuho Bank's Direction Regarding the Enhancement of Customer
   　　　　　　　　　Touchpoints
3.  Digital Banking
   　　1. Background of AI Adoption and Objectives
   　　2. Directions for AI Adoption and Service Structure
   　　3. AI Adoption in Key Operations
   　　　　3.1. Corporate Account Opening Screening and AI-Assisted Interviews
   　　　　3.2. AI Adoption in Customer Analysis and Credit Screening
   　　　　3.3. Automated Customer Inquiries and Operational Support for Agents
   　　　　3.4. Administrative Tasks Related to Suspicious Transaction Detection and
   　　　　　　Financial Crime Prevention
   　　　　3.5. Application of Generative AI to Core Banking System Development
   　　4. AI Development, Procurement Framework, and Operational Management
   　　5. Integration of Banking APIs and External AI Agents
   　　6. Implementation Benefits and Evaluation Criteria
   　　7. Challenges
   　　　　7.1. Division of Roles for AI in Non-Face-to-Face Financial Transaction
   　　　　7.2. Operation and Evaluation of Conventional AI and New Generative AI
   　　　　　　Services
   　　　　7.3. Utilization of Financial Functions via External AI and Management of
   　　　　　　Execution Permissions
   　　8. Outlook
   　　　　8.1. Expansion of AI Transaction Support Functions for Customers
   　　　　8.2. Commercialization of AI Credit Screening as an External Service and
   　　　　　　Expanded Use of Banking APIs
4. Regional Banks
   　　1. Background and Objectives of AI Adoption
   　　2. Directions for AI Utilization
   　　3. AI Utilization by Major Business Area
   　　4. AI Development, Shared-Use Models, and Division of Roles at Regional Banks
   　　5. Major Bottlenecks in AI Implementation
   　　6. Evaluation of the Effects and Outcomes of AI Implementation
   　　　　6.1. Streamlining the Preparation of Loan Approval Documents and Improving
   　　　　　　Quality
   　　　　6.2. Improving Preparation for Client Visits and Proposal Quality in Corporate
   　　　　　　Banking
   　　　　6.3. Verification of the Effects of Automating Head Office Document
   　　　　　　Preparation
   　　　　6.4. Approach to Evaluating Results
   　　7. Challenges
   　　　　7.1. Coordination Between Branch and Head Office Operations and
   　　　　　　Verification of Processing Results
   　　　　7.2. Bank-Specific Verification and Operational Capabilities in a Shared-Use
   　　　　　　Environment
   　　8. Outlook
   　　　　8.1. Expanding Practical Applications in Corporate Sales and Lending
   　　　　　　Operations
   　　　　8.2. Expansion of Shared-Use Services and Their Application to Bank-Specific
   　　　　　　Operations

Chapter IV: The Use of AI by Financial Institutions Overseas

1. Perspectives on Overseas Trends
2. Trends in AI Adoption by Overseas Financial Institutions
   　　2.1. Operational Use of Generative AI
   　　　　2.1.1. A Milestone in Bank-wide Deployment and Changes in Management
   　　　　　　　Metrics
   　　　　2.1.2. The Beginning of Operational Transfer: Software Development
   　　　　2.1.3. Differences from Domestic Financial Institutions
   　　2.2. RAG and the Use of Internal Data
   　　　　2.2.1. Integration with In-House Systems and Data Management
   　　　　2.2.2. Turning Transaction Data into Model Assets
   　　　　2.2.3. Differences from Domestic Financial Institutions
   　　2.3. Applications in Lending, Risk Management, Customer Service, and Other Areas
   　　　　2.3.1. Lending: Automating Decisions and Supporting Analysis
   　　　　2.3.2. Risk Management and Financial Crime
   　　　　2.3.3. Customer Service
   　　2.4. Initiatives Regarding AI Agents
   　　　　2.4.1. From Assisting Operations to Taking Charge of Operations
   　　　　2.4.2. Oversight Framework for Agents
   　　　　2.4.3. Connecting External AI Agents to Financial Functions
3. AI Adoption Among Major Overseas Financial Institutions
   　　3.1. Generative AI and In-House Operational Support
   　　3.2. RAG and Internal Data Integration
   　　3.3. Application to Core Operations
   　　3.4. AI Utilization at Customer Touchpoints
   　　3.5. AI Agents and Autonomous Processing
   　　3.6. Comparison of AI Adoption by Major Financial Institutions
4. Trends in AI Adoption and Provision by Overseas Financial Technology Companies
   　　4.1. Nova Credit
   　　4.2. FICO
   　　4.3. Prism Data
   　　4.4. Zest AI
   　　4.5. EnFi
   　　4.6. Shift Technology

V. Company Profiles

• Megabanks:
  1. MUFG Bank, Ltd.
  2. Sumitomo Mitsui Banking Corporation
  3. Mizuho Bank, Ltd.
• Digital Banks
  4. DOCOMO SMTB Net Bank, Inc.
  5. GMO Aozora Net Bank, Ltd.
• Regional Banks
  6. The Joyo Bank, Ltd.
  7. The Hiroshima Bank, Ltd.
  8. The Chugoku Bank, Ltd.
  9. Aichi Bank, Ltd.
• ​AI Solution Provider for Financial Institutions
  10. NTT DATA Japan Corporation
  11. Hitachi, Ltd.
  12. The Mitsubishi Research Institute (MRI)
  13. SecondXight Analytica, Inc.