BANKING, FINANCIAL SERVICES & INSURANCE
Unlocking Value: Where strategy meets intelligence and growth
Banking appears to have a renewed energy
- Regional banks are merging to offset regulatory costs and achieve operational efficiencies
- Banks using centralized AI frameworks are achieving 70% production success rates (vs. 30% for decentralized models)
- Generative AI is forecasted to add $200B–$340B annually to banking through personalized pricing, hyper-targeted marketing, and automated compliance
- Legacy platform overhauls require expertise in cloud-first architectures and API integration to compete with fintechs
- 52% of commercial clients now prefer digital self-service, necessitating AI-driven tools for seamless integration with internal systems
- Regional banks are deploying AI to analyze community-specific data, enabling tailored products for SMEs and high-net-worth clients
Banking executives have had a new set of priorities over the last couple of years
1. CMO
- Proving and maximizing marketing ROI amidst budget cuts
- Combatting brand erosion from embedded finance
- Competing with neobanks and fintechs
- Data privacy and management amidst AI-driven campaigns
- Scaling hyper-personalization and AI adoption
2. CIO
- Manage security gaps with vendor ecosystems, especially after the 2024 Crowdstrike outage
- Address lack of policies for data usage, bias mitigation, or explainability
- Modernize legacy systems that are incompatible with real-time payments or AI tools
- Democratize data to enable secure, cross-departmental data access for AI
- Control shadow IT and proliferation of tools
3. CDAOs
- Data/AI monetization
- Data democratization, governance and hyper-personalization
- Data security, ZT entitlements
- AI governance and ethical model deployment
4. CFOs
- Managing costs of legacy system modernization
- Shaping the profitability of your customer portfolio across vintages, products and regions
- Cost optimization to manage through rising interest rates
While lots of growth opportunities lie within reach of the banks, there are several pre-requisites to monetizing them
Some questions worth answering are:
- Are our deposit campaigns (still) profitable?
- Are you tired of hearing about upselling and cross-selling, but unsure how to capture that revenue uplift?
- Do you have an overwhelming list of product investment needs but unsure which ones will help you lead the marketplace?
- Which of the 40+ use cases for real-time payments are most profitable for you?
- Are you keen to monetize AI and GenAI but getting impatient to realize big gains?
- Is your core banking platform flexible, agile, easy to maintain? Are you able to bring new products to market fast? Is your servicing cost low?
- Are What is the best way to avoid a never-ending data cloud program?
- Are your servicing operations fully AI-enabled?
Call us if the answer to any of these questions is a Yes. Kepler Cannon helps its client answer these questions and many more. However, finding the right solution gets you only 20% of the way. The remaining 80% comes from rapid and focused execution… we make that happen too!
70 %
production success rate for banks using centralized AI frameworks (vs 30% for decenralized models)
$300B
forecast to be added to banking by Gen AI annually through personalized pricing, hyper-targeted marketing, and automated compliance
52 %
commercial clients now prefer digital self-service, necessitating AI-driven tools for seamless integration with internal systems
Perspectives: Banking, Financial Servies & Insurance
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