Global Generative AI in Banking Market: 2024-2030
Description
Our Generative AI in Banking research suite provides in-depth analysis and evaluation of how banks and other financial institutions are reinventing their products, how their business models operate and how they serve their customers, by leveraging the latest developments within GenAI and artificial intelligence. It includes analysis of 16 key use cases of GenAI within banking, such as for compliance, customer services, and other key financial services capabilities, providing a highly valuable resource for stakeholders navigating this emerging sector.
The suite includes both a data deliverable, sizing the market and providing key forecast data across 60 countries and several different segments, as well as a Market Trends & Strategies document, which gives a complete assessment of the key trends, challenges and recommendations for stakeholders. Collectively, they provide a critical tool for understanding this rapidly emerging market; allowing banks and technology vendors to shape their future strategy.
KEY FEATURES
Market Dynamics: Insights into key trends and challenges of the expanding use of generative AI within the banking market. It also examines the ramifications and potential risks of banks and financial institutions using more artificial intelligence and machine learning solutions in their operations, which will fundamentally change their business models. The study includes a detailed analysis of 16 separate use cases for GenAI within banking; identifying the solutions that will drive efficiency and create transformation within the highly complex banking space, such as enhancing compliance processes, improving the customer experience and reducing cost. The list includes the following:
Asynchronous Servicing
Chat and Voice Bots
Customer Acquisition
Customer Onboarding
Dynamic Pricing
Fraud Detection
Investment Advice and Financial Forecasting
Knowledge and Data Management
Negotiation Engines
Personalised Marketing Campaigns
Portfolio Management
Regulatory Monitoring and Compliance
Risk Management and Collections
Servicing
Spending Insights
Transaction Processing
Key Takeaways & Strategic Recommendations: In-depth analysis of key development opportunities and findings within the generative AI in banking market, accompanied by key strategic recommendations for stakeholders.
Benchmark Industry Forecasts: The forecasts include the total number of banks deploying generative AI, their total spend on generative AI solutions, and the savings attributable for banks from generative AI deployments. These metrics are split by 3 key use cases: customer service, portfolio management and back-office applications.
Juniper Research Competitor Leaderboard: Key player capability and capacity assessment for 15 generative AI in banking vendors, via the Juniper Research Competitor Leaderboard:
Amazon
Amdocs
Cognizant
Coveo
Dataiku
Edgeverve
Fujitsu
Genpact
Google
IBM
Microsoft
Mostly AI
OpenAI
Oracle
Temenos
Please note: the online download version of this report is for a global site license.
The suite includes both a data deliverable, sizing the market and providing key forecast data across 60 countries and several different segments, as well as a Market Trends & Strategies document, which gives a complete assessment of the key trends, challenges and recommendations for stakeholders. Collectively, they provide a critical tool for understanding this rapidly emerging market; allowing banks and technology vendors to shape their future strategy.
KEY FEATURES
Market Dynamics: Insights into key trends and challenges of the expanding use of generative AI within the banking market. It also examines the ramifications and potential risks of banks and financial institutions using more artificial intelligence and machine learning solutions in their operations, which will fundamentally change their business models. The study includes a detailed analysis of 16 separate use cases for GenAI within banking; identifying the solutions that will drive efficiency and create transformation within the highly complex banking space, such as enhancing compliance processes, improving the customer experience and reducing cost. The list includes the following:
Asynchronous Servicing
Chat and Voice Bots
Customer Acquisition
Customer Onboarding
Dynamic Pricing
Fraud Detection
Investment Advice and Financial Forecasting
Knowledge and Data Management
Negotiation Engines
Personalised Marketing Campaigns
Portfolio Management
Regulatory Monitoring and Compliance
Risk Management and Collections
Servicing
Spending Insights
Transaction Processing
Key Takeaways & Strategic Recommendations: In-depth analysis of key development opportunities and findings within the generative AI in banking market, accompanied by key strategic recommendations for stakeholders.
Benchmark Industry Forecasts: The forecasts include the total number of banks deploying generative AI, their total spend on generative AI solutions, and the savings attributable for banks from generative AI deployments. These metrics are split by 3 key use cases: customer service, portfolio management and back-office applications.
Juniper Research Competitor Leaderboard: Key player capability and capacity assessment for 15 generative AI in banking vendors, via the Juniper Research Competitor Leaderboard:
Amazon
Amdocs
Cognizant
Coveo
Dataiku
Edgeverve
Fujitsu
Genpact
IBM
Microsoft
Mostly AI
OpenAI
Oracle
Temenos
Please note: the online download version of this report is for a global site license.
Table of Contents
71 Pages
- 1. Key Takeaways & Strategic Recommendations
- 1.1 Key Takeaways
- 1.1.1 Despite Its Challenges, Generative AI Implementation in Banking Will Continue to Grow
- 1.1.2 Generative AI Use Cases in Banking Industry Are Limited, but Expanding Rapidly
- 1.1.3 Customer Retention and Cost Reduction Will Remain as the Main Drivers of Generative AI Deployments for Banks in the Short Term
- 1.2 Strategic Recommendations
- 1.2.1 Start with Quick Wins for Generative AI Implementation
- 1.2.2 Deploy Generative AI in Conjunction with Traditional AI Systems and Solutions to Attain Maximum Benefit
- 1.2.3 Invest in the Development of More Complex Generative AI Use Cases to Yield Competitive Advantage
- 2. Market Landscape
- 2.1 Introduction
- 2.2 Definitions and Scope
- 2.3 The Banking Market
- 2.4 Generative AI Landscape
- Figure 2.1: Overview of LLM Capabilities
- Figure 2.2: Share of S&P 500 Companies Mentioning AI in Earnings Calls, 2010- Q2 2023
- Figure 2.3: Generative AI Value Chain
- 2.5 Key Trends & Drivers
- 2.5.1 Rising Cost Pressures for Banks
- 2.5.2 Increased Competition for Banks
- 3. Use Cases & Challenges
- 3.1 Use Cases and Challenges
- 3.1.1 Customer Acquisition
- 3.1.2 Customer Onboarding
- 3.1.3 Chat and Voice Bots
- 3.1.4 Personalised Marketing Campaigns
- 3.1.5 Spending Insights
- 3.1.6 Dynamic Pricing
- 3.1.7 Negotiation Engines
- 3.1.8 Transaction Processing
- 3.1.9 Servicing
- 3.1.10 Asynchronous Servicing
- 3.1.11 Knowledge and Data Management
- 3.1.12 Investment Advice and Financial Forecasting
- 3.1.13 Portfolio Management
- 3.1.14 Risk Management and Collections
- 3.1.15 Fraud Detection
- 3.1.16 Regulatory Monitoring and Compliance
- 4. Generative AI in Banking Competitor Leaderboard
- 4.1 Why Read This Report?
- Table 4.1: Juniper Research Competitor Leaderboard: Generative AI in Banking Vendors Included & Product Portfolio
- Figure 4.2: Juniper Research Competitor Leaderboard for Generative AI in Banking
- Table 4.3: Juniper Research Competitor Leaderboard: Generative AI in Banking Platform Vendors & Positioning
- Table 4.4: Juniper Research Competitive Leaderboard Heatmap: Generative AI in
- Banking Platform Vendors
- 4.2 Vendor Profiles
- 4.2.1 Amazon
- i. Corporate
- Table 4.5: Amazon’s Financial Performance (USD $bn), 2019-2022
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.2 Amdocs
- i. Corporate
- Table 4.6: Amdocs’ Financial Performance (USD $m), 2019-2022
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- Figure 4.7: Gen AI Assistant in amAIz Framework
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.3 Cognizant
- i. Corporate
- Table 4.8: Cognizant’s Financial Performance (USD $bn), 2019-2022
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.4 Coveo
- i. Corporate
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.5 Dataiku
- i. Corporate
- Table 4.9: Dataiku’s Funding Rounds, 2014-2022
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- Figure 4.10: Dataiku LLM Mesh Overview
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.6 EdgeVerve
- i. Corporate
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.7 Fujitsu
- i. Corporate
- Table 4.11: Fujitsu’s Financial Performance (USD $bn), 2019-2022
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- Figure 4.12: Fujitsu’s Kozuchi AI Platform Overview
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.8 Genpact
- i. Corporate
- Table 4.13: Genpact’s Financial Performance (USD $bn), 2019-
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- Figure 4.14: Cora LiveWealth Solution Overview
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.9 Google
- i. Corporate
- Table 4.15: Google’s Financial Performance (USD $bn), 2019-2022
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- Figure 4.16: Generative AI Workflow in Google Vertex AI
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.10 IBM
- i. Corporate
- Table 4.17: IBM’s Financial Performance (USD $bn), 2019-2022
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- v. Juniper Research Strategic Recommendations and Key Opportunities
- 4.2.11 Microsoft
- i. Corporate
- Table 4.18: Microsoft’s Financial Performance (USD $bn), 2020-2023
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- Figure 4.19: Microsoft Copilot Commercial Solutions Overview
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.12 Mostly AI
- i. Corporate
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.13 OpenAI
- i. Corporate
- Table 4.20: OpenAI’s Funding Rounds, 2016-2023
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.14 Oracle
- i. Corporate
- Table 4.21: Oracle’s Financial Performance (USD $bn), 2020-2023
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.2.15 Temenos
- i. Corporate
- Table 4.22: Temenos’ Financial Performance (USD $m), 2019-2022
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offerings
- v. Juniper Research’s View: Strategic Recommendations & Key
- Development Opportunities
- 4.3 Juniper Research Competitor Leaderboard Assessment Methodology
- 4.4 Limitations & Interpretation
- Table 4.23: Juniper Research Competitor Leaderboard Scoring Criteria –
- Generative AI in Banking Platforms
- 5. Generative AI in Banking Market Forecasts
- 5.1 Forecast Introduction
- 5.1.1 Methodology & Assumptions
- Figure 5.1: Generative AI within Banking Forecast Methodology
- 5.2 Generative AI in Banking Forecasts
- 5.2.1 Generative AI Spend
- Figure & Table 5.2: Total Bank Spend on Generative AI Deployments ($m), Split
- by 8 Key Regions, 2023-2030
- Table 5.3: Total Bank Spend on Generative AI Deployments ($m), Split by Use
- Case, 2023-2030
- 5.2.2 Savings from Generative AI Deployment
- Figure & Table 5.4: Total Bank Savings from Generative AI Deployments ($m),
- Split by 8 Key Regions, 2023-2030
- Table 5.5: Total Bank Savings from Generative AI Deployments ($m), Split by Use
- Case, 2023-2030
Pricing
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