Article · AI in Banking
After Adobe, Microsoft Office Is Next: AI Is Rewriting the Economics of Software
From GenOffice to WordCraft, GridCraft and DeckCraft — and what comes next
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Insights · Ideas · Impact
Shaping the future of banking with AI
Insights, research, training and advisory for a more intelligent, inclusive and human-centred banking industry.
“Leveraging AI for better banking, stronger communities and a brighter future.”
From experimentation to enterprise impact
Key areas of AI in banking
AI is changing banking, from customer experience to intelligent operations. AI Exec Hub helps leaders understand where AI creates real value, what is working today, and how to scale responsibly.
AI Strategy & Transformation
Roadmaps, use-case prioritisation and operating models.
Customer Experience
Onboarding, personalisation and relationship banking.
Agentic Banking
From AI assistants to AI co-workers.
Operations
Intelligent automation across the bank.
Risk & Compliance
AI with controls, governance and regulatory alignment.
Fraud & Financial Crime
Detection, monitoring and investigation support.
Lending & Credit
From application to portfolio monitoring.
Payments
Smarter, faster and safer payments.
Data & Architecture
The foundation for scalable AI.
Responsible AI
Governance, ethics and human oversight.
Banking Research
Original research and benchmarks on how banks adopt AI.
Banking Case Studies
Evidence-graded examples of AI at named banks.
The Banking AI Transformation Framework
A practical path from exploration to enterprise impact.
- 1
Discover
- 2
Prioritise
- 3
Experiment
- 4
Industrialise
- 5
Integrate
- 6
Scale
- 7
Transform
Seven dimensions of AI banking value
Every use case, case study and piece of research is classified by the value it creates.
| Dimension | What it covers |
|---|---|
| GROW | Revenue, acquisition, conversion and customer lifetime value |
| BOOST | Employee productivity, decision support and capacity |
| OPERATE | Workflow efficiency, turnaround and cost |
| SERVE | Customer experience, personalisation, onboarding and advice |
| PROTECT | Fraud, AML, monitoring, anomalies and risk |
| BUILD | Trust, governance, explainability, privacy, security and accountability |
| TRANSFORM | Agentic banking, AI-native workflows, propositions and operating models |
How each area is explored
Every area follows the same executive narrative, so a reader always knows where to find the evidence.
- 1Executive perspective — What is changing?
- 2Banking problem — Why does it matter?
- 3AI opportunities — Where can AI help?
- 4Use cases — Practical applications.
- 5Bank examples — Verified implementations.
- 6Architecture — How it works.
- 7Value & KPIs — How impact is measured.
- 8Risks & controls — What can go wrong?
- 9Maturity path — From experiment to enterprise.
- 10Research & insights — Related evidence and analysis.
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