AWS re:Invent 2025 - Accelerating Business Value with Cloud and AI (BIZ324)

Accelerating Business Value with Cloud and AI at NatWest

Transforming NatWest's Digital Spine

• NatWest is a leading UK bank focused on retail, business, and wealth customers
• Their ambition is to be the most customer-centric digital bank, delivering great experiences through AI-powered capabilities
• This is enabled by their "digital spine" - a set of shared, AI-powered, cloud-native capabilities that underpin their AI-driven future

Key Components of the Digital Spine

1. Integration: Secure connectivity for AI-orchestrated services, enabling ecosystem interoperability
2. Data Marketplace: A data fabric that fuels the insights and models of their AI ecosystem
3. Intelligent Core Banking: An AI-driven platform that delivers adaptive and personalized products
4. Scaled AI Ecosystem: Empowering every employee to achieve more through AI

NatWest's AI Reference Architecture

• NatWest has developed a 4-tier AI reference architecture:
  1. Operating Model: Establishes an AI-ready culture and governance framework
  2. Core Tech and Data Fabric: Focuses on integration, security, and scalable data access
  3. AI-Powered Decision Making: Building AI-powered products and agentic solutions
  4. Digital Engagement: AI-ready interfaces and intelligent products/services

AI Use Case Portfolio

NatWest sees their AI use cases as a value chain across 4 areas:

1. Scaled AI, End-User, Low-Code Use Cases: Empowering every employee to be more productive
2. Commodity-Driven Use Cases: Small, point-based AI solutions built by engineers
3. Complex Firsts: Agentic services requiring orchestration, automation, and autonomy
4. Leading Edge Research: Investing in emerging capabilities like deep fake protection, avatars, and biometrics

Competitive Advantage through Partnerships and Culture

• In an AI-powered world, competitive advantage comes from partnerships, culture, talent, and enablement - not just technology
• NatWest is focused on building the right operating model, governance, and AI-ready culture to drive their transformation

LPL Financial's AI-First Transformation

LPL Financial Overview

• Largest broker-dealer in the US, serving 32,000 financial advisors and 8 million households
• Focused on empowering advisors with the best tools to support their clients' financial goals
• Experienced rapid growth, doubling AUM and advisor base in recent years

Key Transformation Personas and Objectives

1. Financial Advisors: Provide personalization, speed, and proactive insights to free up time for client relationships
2. Investors: Build trust, transparency, and seamless digital experiences
3. Operations: Automate manual tasks and reduce friction through AI
4. Developers: Enable more time for innovation by automating routine tasks

AI-Powered Use Cases

1. Banking Wizard: AI-powered chatbot to provide self-service support for new banking products
2. Account View: Modernizing the customer-facing investor portal with cloud migration and rearchitecture
3. Lending: Automating manual document review and surveillance in the lending process
4. Developer Efficiencies: Leveraging AI-powered tools like Copilot for test automation and code generation

Future AI Initiatives

• Payment exception handling
• AI-powered back-office assistant
• Financial crime detection and anti-money laundering

Truist's Enterprise AI Blueprint

Integrating AI Capabilities

• Truist is focused on integrating various AI capabilities from their own knowledge domains, vendor products, and platform-native AI
• Goal is to create a cohesive enterprise blueprint that enables scaling AI use cases and driving faster integrations

Key Elements of the Blueprint

1. Enterprise Knowledge Domain: Investing in curating and managing internal knowledge to power both traditional and generative AI
2. Platform Layer: Leveraging enterprise platforms like Bedrock and SageMaker for model development and deployment
3. Orchestration Component Layer: Enabling integration and orchestration of different AI capabilities
4. Experience Framework: Providing consistent user experiences for different AI use cases, from RPA to agentic platforms

Priorities for Truist

• Scaling integrations to drive 150+ AI use cases
• Achieving cohesiveness by using the right tool for each job
• Prioritizing speed and agility in delivering AI-powered capabilities

NatWest's Commercial Banking Platform Transformation

Bankline Platform Overview

• Critical digital platform for NatWest's commercial and institutional customers
• Provides account and payment capabilities across mobile, web, and API channels
• Serves businesses with turnover from £750K to £500M

Transformation Objectives

1. Digital Customer Journeys: Deliver a unified, intuitive customer experience
2. Single Point of Access: Provide frictionless access to products and services
3. Increased Pace of Delivery: Leverage cloud to accelerate capability deployment

Transformation Progress and Impact

• 60% increase in digital service requests
• Single mobile platform across all brands
• Integration of key products like asset finance and FX
• Significant migration of workloads to the cloud

Role of AI in the Transformation

• Code analysis to understand legacy dependencies
• Automated documentation generation
• Migration planning based on AI insights
• Code refactoring to modernize the codebase

Key Takeaways

• NatWest, LPL Financial, and Truist are undergoing significant AI-powered digital transformations
• Core focus is on building flexible, scalable platforms and architectures to enable AI-driven capabilities
• Specific use cases span from intelligent automation to agentic services and leading-edge research
• Successful transformation requires the right operating model, governance, culture, and partnerships - not just technology
• AI is a critical enabler, but must be integrated thoughtfully into the overall enterprise blueprint