Lending in times of AI: three imperatives for banks

AI is no longer hype—it’s the engine driving the next era of financial services. For banks and lenders, the question isn’t if, but how to harness its potential. Over the past year, we’ve seen AI move from experimental pilots to core business strategies in leading banks. According to recent industry reports, over 70% of financial institutions are now investing in AI-driven solutions to streamline operations and enhance customer experiences. At the end of 2025, the buzz has settled into a new reality: Artificial intelligence will permanently reshape how we work, especially in financial services. While visions of a fully automated future grab headlines, the real challenge for commercial lenders is much closer to home. 

Here are three key AI considerations for commercial lenders right now. 

1. Watch the bubble: lend with caution 

AI is fueling a surge of innovation. And with it comes the risk of an overheated hype market. Valuations for tech companies—especially those touting AI capabilities—are soaring to unprecedented heights. But history offers some cautionary tales. Spanning from the dot-com bubble to the more recent fintech surge and crypto boom, there are several examples of when exuberance outpaced facts. Once the excitement faded many investors were left exposed. 

For lenders, particularly those extending credit based on cash flow projections, this environment demands extra vigilance. It is imperative to dig deeper than surface-level success stories. Some borrowers may appear to be thriving, but their business models or revenue streams could be fragile, propped up by a heated market. 

To avoid repeating past mistakes, prudent risk assessment and vigilant underwriting are more important than ever. This means going beyond traditional financial metrics and scrutinizing the sustainability of a borrower’s business model, the quality of their data and the resilience of their revenue streams. The work doesn’t stop on the day of signing. Continuous monitoring of the market and potential shifts is required to ensure a well-balanced portfolio. Leveraging real-time analytics and AI-powered monitoring tools can help lenders track borrower performance and market signals. Thereby they can go for proactive risk management rather than reactive responses. 

2. Frameworks matter: invest with purpose 

AI is now fundamental to driving efficiency for employees and improving customer interactions. Traditional value drivers in commercial lending are being replaced by gains made possible through AI. Automating routine processes, enhancing risk assessment, or delivering more personalized client experiences are only a few examples. 

However, with a plethora of AI solutions available and the industry evolving at breakneck speed, leaders need to be highly selective about where and how they deploy their capital most effectively. The temptation to experiment widely is strong, but the most successful organizations are those that start with practical, high-impact areas and scale from there. 

A careful assessment of needs, costs and potential gains is critical for commercial lending leaders. This means evaluating not just the immediate benefits, but also the long-term alignment with business strategy and the ability to solve pressing challenges. A robust AI investment framework should include clear governance structures, cross-functional collaboration and well-defined KPIs to measure success. 

Without these guardrails, investments risk being scattered, chasing the latest trends rather than delivering real value. For example, some lenders have rushed to implement AI-powered chatbots or analytics tools without first ensuring data quality or integration with existing systems. This can easily result in limited impact and wasted resources. By taking a structured, purpose-driven approach, organizations can ensure that resources are channeled into projects with lasting impact, not just short-term buzz. 

3. Data: clean, consistent and standardized 

AI is only as powerful as the data it can work with. Messy, inconsistent data leads to unreliable outcomes or even missed opportunities. For lenders, this means a renewed focus on the need for lean architectures and robust data management. 

But true data discipline goes beyond just cleaning up isolated datasets. The real differentiator is end-to-end and front-to-back integration across the entire lending lifecycle. By connecting every stage—from origination and credit risk management in the front office, through loan servicing and collateral management, to accounting and analytics in the back office—lenders can ensure a seamless flow of information and a single source of truth for all loan-related data. 

Standardized, high-quality data empowers AI to deliver accurate, actionable intelligence—helping lenders make smarter, faster decisions and respond proactively to market changes. With SAP Fioneer’s modular lending stack, banks can achieve comprehensive coverage and transparency, unlocking the full potential of automation and AI while maintainingcontrol and flexibility across all lending types. 

The time to act is now 

As AI continues to evolve, the most successful lenders will be those who combine innovation with discipline and strategic focus. Want to learn more about how SAP Fioneer is helping financial institutions harness the power of AI? Explore our latest insights or get in touch with our experts to start your transformation journey.