AI Is Transforming Financial Services. Hyperpersonalization Is Now the Advantage.
The pandemic changed how people bank, invest, and insure almost overnight. That shift didn’t fade. It hardened into new expectations. Customers want experiences that feel intuitive, personal, and built around their financial needs. They want to feel understood by the institutions they trust with their money.
And they switch fast when they don’t get that.
Research backs this up: according to Mckinsey, 71% of consumers expect personalized interactions, and 76% feel frustrated when they don’t get them.
A global survey captures this shift clearly: trust is the top reason people choose a financial institution, and digital experience ranks second. Yet although many brands believe they deliver a strong digital experience, fewer customers agree.
There’s your gap. And AI is the only realistic way to close it.
The New Reality: Personalization Starts the Moment a Customer Shows Up
Modern financial services customers no longer just appreciate personalization. They expect it. They want their bank to use the information they share to shape experiences around their goals, and that expectation starts from the first interaction.
63% of consumers want their bank to understand their unique needs, and more than half would switch for more personalized experiences.
A refi quote, a credit card application, an insurance inquiry — these early signals reveal what matters to a customer. When activated well, they become the backbone of a journey that stays consistent across every channel, powering tailored onboarding, personalized dashboards, relevant recommendations, smarter cross-sell, and timely, contextual communication.
Poor personalization remains a leading reason digital banking journeys fail or get abandoned. And the upside is clear. Customers reward relevance, and they move on quickly when they don’t get it. Banks that excel in personalization can see revenue lift by as much as 10 percent.
Why AI Is the Only Way to Personalize at the Speed Customers Expect
Financial institutions sit on rich behavioral data, transactional histories, product signals, and engagement insights. But understanding all of it in real time (and acting on it) may seem impossible.
AI changes that. It gives banks the ability to read context faster, understand customer needs more precisely, and deliver the right experience in the exact moment it matters. It makes personalized product design, intuitive recommendations, and accurate risk and fraud responses not only possible, but scalable. The industry’s direction is clear. By 2026, 60% of banks are expected to prioritize AI-based decisioning to improve customer experience.
Some companies report benefits from using AI for personalization. Others cite operational savings and improved customer satisfaction. And fintechs have achieved notable ROI and efficiency gains after unifying knowledge and decisioning with AI.
Momentum continues to build. Banks that embed advanced analytics and AI into their decision-making see performance improvements ranging from two to five times in key marketing and engagement outcomes. AI pushes this even further. Experts note that the next era of banking requires a redesigned interface where AI has a comprehensive and precise grasp of each customer’s situation, actions, requirements, and inclinations. Multi-agent AI systems now make that level of precision practical — orchestrating workflows with accuracy no human team can match.
Putting Theory to Work
To ground this shift in the real world, we recently explored these exact challenges during our Minders AI Academy Ecuador — an exclusive workshop hosted by Minders in collaboration with Deuna (Banco Pichincha) and Braze. Marketing, product, and data teams came together to decode how AI, machine learning, and reinforcement learning are transforming customer experience.
Through hands-on exercises, attendees built predictive models from scratch, learned how AI Decisioning supports smarter business decisions, applied generative AI to communication strategies, and examined real cases from companies already achieving results with AI.
The workshop made one thing clear: leading teams are not just watching the AI wave — they’re preparing to ride it.
The Hidden Problem: Prediction Alone Isn’t Personalization
For years, many financial brands relied on Next Best Action (NBA) models. On paper, the logic made sense: predict what a customer might do next, then personalize around that prediction. But NBA has a fundamental flaw. It predicts behavior. It doesn’t decide what marketers should do to create better outcomes.
This creates real risk. A customer may already be planning to open the product the model recommends, turning the outreach into a wasted touchpoint. The “next best action” might not be the action that delivers the most value. Or communicating at all may not influence the outcome.
To sum it up: “The NBA model is making a prediction about customer behavior, rather than identifying the best decision for the marketer.”
And that gap is exactly where AI Decisioning takes over.
Why AI Decisioning Is the New Standard
AI Decisioning is done with guessing. It decides.
Rather than predicting what a customer may do, it determines the best action a brand should take for each individual, using reinforcement learning to continuously experiment, learn, and adapt. Organizations that apply advanced decisioning and analytics to customer journeys see two to five times stronger performance across key engagement metrics.
This gives marketers true next best everything — not just the next best product, but the best channel, message, timing, frequency, and creative for every customer.
AI Decisioning stands apart because it:
-> Optimizes for the metrics that matter — revenue, margin, NPV, engagement — without manual testing
-> Learns continuously and adapts automatically as behavior or market conditions shift
-> Replaces complex webs of rules and predictive models with one adaptive system
-> Personalizes 1:1, not by segment, using all available first- and zero-party data
-> Works alongside existing predictive models but doesn’t depend on them
-> Tests constantly, discovering better decisions instead of relying on what worked before
-> Optimizes multiple dimensions at once — product, timing, channel, message — even when they influence each other
Traditional NBA models aren’t useless, but they’re no longer state of the art. AI Decisioning gives marketers what they’ve always needed: a clear, automated, continuously improving way to deliver the right action to the right customer every time.
Personalized interactions drive significantly higher trust, with more than three-quarters of consumers feeling more loyal to brands that tailor their communication.
Why Braze Is Built for This Moment
AI Decisioning delivers intelligence. Braze turns that intelligence into action.
Braze Decisioning and AI Studio allow financial institutions to use all their zero- and first-party data to determine and deliver the next best moment, message, or offer in milliseconds. It becomes the execution engine that transforms insights into real, coordinated customer experiences — across email, mobile, in-app, SMS, and web.
Braze unlocks:
-> Real-time activation of customer data
-> Millisecond-level decisioning
-> AI-powered journey optimization
-> Natural language interfaces that remove technical barriers
-> Seamless multichannel orchestration
-> Personalization at scale, without complexity
Braze becomes the command center for engagement, powering personalized onboarding, dynamic recommendations, smarter cross-sell, timely alerts, and communication that stays relevant throughout the entire lifecycle. For institutions competing with digital-first challengers, this level of speed and precision is transformational.
And when paired with AI Decisioning, Braze becomes one of the most powerful customer experience platforms in financial services.
Real Numbers, Real Impact
Organizations embracing AI-powered personalization already report:
-> Double-digit increases in satisfaction and conversion
-> Major time savings in operations
-> Stronger fraud detection and risk management
-> More effective loyalty programs
-> Better product adoption and deeper engagement
AI-driven personalization can increase customer engagement by up to 70%. The business case is no longer theoretical — it’s proven.
Where Most Institutions Struggle: Implementation
AI Decisioning is powerful, but getting it right requires the correct strategy. You need clean data, clear KPIs, smart journey design, solid measurement, and a team that understands both the technical and operational realities of financial services.
That’s where Minders comes in.
We help companies turn Braze into a real-time personalization engine powered by AI Decisioning. From data foundation to activation, from journey redesign to optimization, we make the technology work the way it should — and deliver the outcomes your business needs.
If you want to transform customer communication, eliminate guesswork, and deliver financial experiences people actually value, Minders is the partner that gets you there.