AI Trends in Banking 2025: The Strategic Transformation of Financial Services
The banking industry stands at a critical inflection point. As we advance through 2025, artificial intelligence has evolved from experimental technology to a strategic imperative reshaping how financial institutions operate, serve customers, and manage risk.
The numbers tell a compelling story. According to McKinsey's latest Global Survey on AI, 78% of organizations now use AI in at least one business function, up from 72% in early 2024 and 55% a year earlier.
Meanwhile, the financial services industry invested an estimated $35 billion in AI in 2023, with banking accounting for approximately $21 billion. This investment is expected to generate substantial returns, with AI contributing $2 trillion to the global economy through innovative investment strategies, better customer insights, and improved operational efficiency.
Based on nCino's experience with over 2,700 customers, including community banks, credit unions, independent mortgage banks, and the largest financial entities globally, three key priorities are driving AI adoption in 2025 and beyond:
In 2025, banks are moving past generic automation goals. The focus now is on applying AI to specific, high-friction workflows — especially in lending, onboarding, and document-heavy processes. Efficiency is no longer about reducing headcount. It’s about speeding up what still takes too long.
Instead of general-purpose tools, banks are deploying AI tuned to their internal workflows. These applications help teams move faster with fewer manual steps.
Examples:
Parsing tax returns or balance sheets to pre-fill borrower profiles
Prioritizing credit files based on deal complexity or risk level
Drafting loan memos from financial and historical deal data
Cycle time is still a pain point — and AI is helping by automating file assignment, surfacing bottlenecks, and routing based on business value.
Examples:
Auto-assigning stalled deals to available underwriters
Flagging missing documentation before an analyst starts a review
Dynamically re-prioritizing workloads as queues shift
Real-World Application: nCino Banking Advisor exemplifies this trend, providing a banking-focused generative AI solution that reduces manual processes and redundant data entry, giving employees more time for strategic, value-adding tasks.
AI revolutionizes risk management by transforming how institutions identify, assess, and mitigate threats. Key applications include:
Fraud Detection: Real-time transaction pattern analysis identifies anomalies with unprecedented accuracy and speed.
Credit Risk Assessment: Machine learning models predict defaults by analyzing customer behavior and transaction patterns more accurately than traditional methods.
Cybersecurity: In 2023, financial services experienced over 20,000 cyberattacks resulting in $2.5 billion in losses. AI-powered security systems detect and respond to threats in real-time.
Case Study: nCino Continuous Credit Monitoring, adopted by M&T Bank, leverages explainable AI to provide comprehensive credit risk insights while maintaining transparency in decision-making.
By strengthening these risk management capabilities, banks can confidently offer personalized financial products and services, knowing they have robust safeguards in place to protect both the institution and individual customers from evolving threats.
77% of banking leaders say personalization leads to boosted customer retention, with AI enabling the personalized experiences that drive customer satisfaction and loyalty. AI enables personalized service delivery, 24/7 customer support through chatbots, predictive analytics for proactive solutions, and streamlined digital experiences. Despite these impressive stats, only 26% of companies have developed the necessary set of capabilities to move beyond proofs of concept and generate tangible value, according to new research by Boston Consulting Group (BCG). Success requires strategic implementation focusing on four key factors:
Risk-proportionate governance that matches oversight intensity to actual risk levels, from low-risk internal automation requiring 1-2 day approvals to high-risk automated decisions demanding comprehensive review
Accelerated implementation timelines where leading institutions follow streamlined roadmaps from governance foundation through production deployment
Human-in-the-loop design that maintains human oversight as a core principle while capturing efficiency benefits
Executive leadership engagement that significantly reduces approval timeframes by providing necessary decision-making authority for rapid implementation.
Together, these strategic approaches enable banks to deploy AI solutions that can analyze customer data, predict needs, and deliver personalized experiences at the scale and speed required to compete in today's digital banking landscape.
75% of banks with over $100 billion in assets are expected to fully integrate AI strategies by 2025. Emerging trends include agentic AI for complex tasks, multimodal AI processing multiple data types, and federated learning for privacy-preserving collaboration.
Regulatory evolution will bring more specific AI requirements focusing on algorithmic transparency, standardized risk frameworks, and enhanced consumer protection. To fully embrace these opportunities, financial institutions must:
Develop a Comprehensive AI Strategy: Start with clear business objectives aligned with efficiency, risk management, or customer experience priorities.
Invest in AI Capabilities: Focus resources on people and processes rather than just technology, building AI literacy organization wide.
Choose the Right AI Partners: Work with vendors offering proven banking solutions, built-in governance controls, and integration capabilities.
Maintain Customer Trust: Prioritize transparency, implement strong data protection, and ensure human oversight for critical decisions.
The AI transformation of banking is accelerating rapidly. This growth will contribute $2 trillion to the global economy through innovative strategies and improved efficiency. Financial institutions that embrace AI responsibly and rapidly – with proper governance, risk management, and customer focus – will thrive in the digital future.
Success lies in balancing innovation with responsibility, speed with governance, and technology with human oversight. By focusing on efficiency, risk management, and customer experience while implementing proper governance frameworks, banks can harness AI's full potential to drive sustainable growth.
The future of banking is being written today, by leaders who understand, respect, and embrace the vast potential of AI. The question isn't whether your institution will be part of this transformation – it's whether you'll help lead it.
The mortgage industry is evolving at a rapid pace. Borrowers demand faster, more seamless digital-first experiences, and lenders face mounting pressure to adapt. With loan abandonment rates exceeding 75% at critical process stages, the stakes have never been higher.
The building society sector continues to demonstrate remarkable resilience and momentum, accounting for 72% of mortgage market growth between April and September 2024.
In today's increasingly complex economic landscape, financial institutions face mounting pressure to adapt to policy changes that significantly impact their lending portfolios. The current administration's implementation of tariffs presents both immediate challenges and long-term considerations for lenders across the United States. With rising economic policy uncertainty weighing on business fixed investments, financial institutions must prepare for potential credit deterioration and adjust their risk management strategies accordingly.
As community banks and credit unions navigate a constantly evolving financial landscape, a few challenges become clear. From delivering modern member experiences to understanding the role of legacy systems in a digital world, it’s crucial that community banks and credit unions find solutions that best serve their borrowers.
Transformational Innovation for Credit Union SuccessCredit unions strive to provide meaningful financial services to their members while navigating operational complexities such as compliance, risk management, competition, and evolving member expectations. Enter nCino, a technology partner uniquely equipped to address these challenges through our unified cloud-based platform.
