Building AI Bank of the Future 🤖🏦; Apple is developing its own AI chatbot called Apple GPT 🤯; Should N26 leave Brazil? 🇧🇷
FinTech is Eating the World, 20 July
Hey Everyone,
Happy Thursday! Today’s issue is super important as we’re looking at how to build the AI Bank of the Future (key building blocks & lots of deep dives on AI + Finance), Apple which is developing its own AI chatbot called Apple GPT (why it’s a game-changer making Apple one step closer towards the first Super App of the West), and examine why N26 should leave Brazil (exit is more than logical + some deeper dives into N26’s biz). Let’s jump straight into the spicy stuff 🌶
Building AI Bank of the Future 🤖🏦
Note: this was initially posted on LinkedIn but due to massive interest and engagement, I’m sharing it here as well. Plus, some extra reads too.
Untapped potential 🚀 Artificial Intelligence will unlock $1 trillion of additional value for banks. Each year 😳
Let’s take a look at how to build the AI bank of the future that will be driving the next wave of FinTech innovation.
Perspective 🔎 We already know that rapidly evolving AI technologies have the potential to skyrocket bank revenues, slash costs, and unveil untapped opportunities through improved personalization, automation, and data-driven insights.
According to McKinsey, the potential annual value of AI in banking is estimated to be as much as $1 trillion 🤯
More on this 👉 But to fully leverage AI, banks need to undergo a holistic transformation spanning their engagement layer, decision-making layer, core technology/data layer, and operating model. Piecemeal AI initiatives will fall short.
Here are the most important building blocks for the AI-centric bank:
👥 The engagement layer
Should provide intelligent, personalized propositions across all channels, seamlessly integrate within partner ecosystems, and enable smart servicing with fast, simple interactions.
💡The decision-making layer
It requires deploying advanced analytics and machine learning models across the customer life cycle for automated, data-driven decisions. This requires industrializing model development.
📊 The core technology/data layer
Modernizing the core technology/data layer is crucial to make systems scalable, resilient, and adaptable enough to fuel real-time AI capabilities. This includes transitioning to the cloud, having robust APIs, data platforms, etc.
⚙️ Operating model
The operating model must bring together the right talent, culture, and organizational design in cross-functional teams to synchronize all layers of the AI stack. The platform model creates business-tech partnerships.
Value to be unlocked 💸 If done right and put together, these building blocks will transform financial services from the ground up and allow the following:
- Hyper-personalized recommendations and insights driven by advanced analytics
- Intelligent virtual assistants and chatbots providing 24/7 customer service
- Automated fraud detection and risk management using machine learning
- Streamlined operations and reduced costs through increasing process automation
- Tailored products and pricing based on individual customer data and behaviors
- Seamless omnichannel experiences with secure biometric authentication
✈️ THE TAKEAWAY
Looking ahead 👀 Going forward, banking will be all about experiences & personalization and AI is the key technology to unlock it. Banks that fail to become AI-first will inevitably lose to FinTechs and Big Tech competitors (think Apple, Revolut, or Klarna here). Welcome to the new world of finance.
And if you want to stay ahead of the curve, read these:
ICYMI: Game-changer: the first Open-Source Financial LLM is finally here 🤯
Bonus: The insurance sector is more and more exploring the benefits of AI 🤖
Generative AI will completely transform FinTech and Banking over the next 3 years 🤖🏦
JPMorgan is developing a ChatGPT-like AI service for investors 😳 [+6 more reads]