For over a decade, financial institutions have been at the forefront of adopting analytics and AI solutions. Banks and Insurance companies, in particular, recognized early on the value of leveraging large volumes of data and the use of powerful data warehouses to streamline internal processes, reduce costs, and improve operational efficiency - as of 2024, 77% of all Financial Institutions had adopted some sort of Analytics and AI technology and led cost savings initiatives of $447B - (1). From directing clients toward lower-cost digital channels, proactively offering credit limit increases based on expenditure and payment history to automating loan and credit request processes and transforming repetitive inquiries into FAQs, financial institutions have historically focused their efforts inward.

However, the game has changed.

Today’s Analytics and AI capabilities have evolved dramatically. With predictive data analytics, data visualization tools, real time analytics and generative AI, real-time predictive models, and deep personalization now within reach, continuing to focus solely on cost optimization is no longer a competitive strategy—it’s a missed opportunity. The true potential lies in harnessing these technologies to deliver exceptional, personalized customer experiences that drive engagement, loyalty, and financial wellness – to both clients and organizations.

A Risk-Averse Industry in a Rapidly Evolving Landscape

Despite being well-equipped with customer data and digital infrastructure, many financial institutions remain stuck in a traditional, risk-averse mindset. Their reluctance to fully embrace the power of Analytics and AI for customer engagement often stems from concerns about regulatory scrutiny and internal cultural inertia. Meanwhile, FinTechs such as Robinhood, Coinbase, Cleo, Lemonade and other digital-native players are seizing the moment—delivering agile, hyper-personalized experiences that win over modern digital-native players are seizing the moment—delivering agile, hyper-personalized experiences that win over modern customers.

According to a PwC report (2), 73% of banking executives say customer expectations are increasing significantly, yet only 35% feel they are effectively leveraging AI to improve customer experience.

Letting startups lead the way in innovation while established institutions remain cautious might seem like a prudent risk management strategy. But, in reality, it exposes traditional banks, insurance companies and investment firm to a slow erosion of market share, brand relevance, and customer trust—especially among younger, tech-savvy demographics.

Turning Data into a Differentiator

Financial institutions possess a goldmine of customer data—account behaviors, transaction history, spending patterns, risk profiles, and even lifestyle indicators. The opportunity to turn this data into personalized, proactive financial guidance, using Business Intelligence tools is unprecedented.

Imagine using AI-driven insights to inform a customer about an attractive mortgage option based on the fact the client is about to retire, or suggesting an insurance plan proactively knowing the customer recently purchased an all-inclusive vacation package on their credit card or providing a short-list of stocks which are delivering above industry, to a client who tends to buy tech stock every quarter. Personalization is no longer a luxury: it is an expectation.

As an interesting fact, McKinsey (3) reports that banks that personalize customer interactions can increase revenue by 10-15% and reduce churn by up to 30%.

Also, Jim Marous, a leading financial services influencer during a recent webinar, said it best:

“Banks know more about their customers than the customers know themselves. Use this information—and share it in a meaningful way!”

This is the new competitive edge: moving from generic product offerings to highly relevant, contextual experiences that meet customer needs before they’re even articulated.

Turning day-to-day transactional Interactions into Memorable Moments

Financial institutions engage with customers billions of times each year. These interactions, however, are overwhelmingly transactional. Checking balances, transferring funds, purchasing travel insurance, buying stock, withdrawing cash. Functional? Yes. Memorable? Not even close.

With Analytics and AI solutions , these everyday moments can be transformed into relationship-building touchpoints. Imagine receiving personalized stock updates related to your investment portfolio while browsing related news, being alerted to tax-saving investment options during a high-spending month or even being alerted when stock price of your portfolio has reached a peak and hence allowing you to make the decision to sell – or maybe simply let you know of your recent increment of wealth.

According to Accenture, 67% of consumers say they want companies to provide relevant recommendations before they even ask (4). And yet, only 36% of financial institutions claim to provide proactive suggestions based on customer data.

As Monica Hovsepian, Global Industry Strategist for Financial Services at OpenText, also mentioned a recent event on Financial Services and Analytics and AI Solutions:

“AI solutions can empower automation and allow a frictionless processing of operations while reducing inefficiencies and cost—while enhancing the experience of end users.”

AI-powered personalization can offer real-time insights, contextual alerts, and educational nudges that help customers make better financial decisions—turning routine banking into intelligent guidance.

Winning the Hearts of the Next Generation

Millennials, Gen Z, and Gen Alpha are fundamentally reshaping the financial services landscape. They are more open to sharing personal data, more comfortable with digital ecosystems, and far more willing to experiment with new services—provided they are relevant, fast, and intuitive. In addition, they are more risk averse and are willing to try new things to get more value into their lives - read more about Gen Zs and the future of finance  on the following blog.

While older generations favored in-person trust, younger customers value digital transparency and personalization. They expect their bank to behave more like Spotify or Netflix—anticipating needs and tailoring experiences by letting these companies use their information. Let’s be clear here: they know their usage and consumption data is being used to build superb experiences via Predictive Analytics and Business Intelligence plays . And guess what: They love it!

Salesforce reports that 84% of customers say the experience a company provides is as important as its products and services (5).

And yet, many traditional banks still rely on outdated engagement models. While some have launched digital banks or partnered with fintech's, these efforts often lack integration with core banking systems or fail to deliver seamless, personalized journeys.

Instead of playing defense, financial institutions should fully embrace the capabilities of Advanced analytics and AI to attract, understand, and retain the next generation of customers—on their terms.

Conclusion: A New Mandate for the Future of Finance

The future of financial services doesn’t lie in simply becoming more efficient—it lies in becoming more human.

Yes, cost savings and process automation are necessary. But they are just the beginning. The real opportunity is in creating intelligent, empathetic, and proactive customer experiences that build long-term value, loyalty and deepen trust—for both the institution and the individual.

Financial institutions already have the tools, data, people and infrastructure. What they need now is a mindset shift—from risk aversion to customer obsession.

Those who act now will not only differentiate themselves in a crowded marketplace but also redefine what it means to be a trusted financial partner in the Analytic and Artificial Intelligence (AI) age.

Sources

• (1) "Impact, Future, Trends and Key Insights" (2025)
• (2) “Financial Services Experience Survey” (2023)
• (3) “The value of getting personalization right—or wrong—is multiplying” (2023)
• (4) “Banking on the Cloud: Technology Vision” (2023)
• (5) “Customer Engagement Research” ( 2023)

The post Analytics and AI in Financial Services: Shifting from Efficiency to Customer-Centric Innovation appeared first on OpenText Blogs.