How banks can leverage real-time insights and artificial intelligence to transform decision-making and improve customer experiences.
For decades, banks have operated with systems that worked—but not always efficiently. Today, the urgency to modernize isn’t just about keeping up with fintechs or meeting customer expectations. It’s about survival. Traditional methods can no longer keep pace with the demand for instant lending decisions, accurate risk assessment, and streamlined compliance.
Real-time data and AI are opening new doors for banks. These tools can help make smarter decisions throughout the credit process, better manage risk, and create a more satisfying customer experience. The challenge? Knowing where to begin and how to make these technologies work seamlessly together.
Why Real-Time Data and AI Matter Now
Banks that adopt real-time data and AI aren’t just catching up—they’re setting new standards. According to a McKinsey report, AI-powered banks have seen delinquency rates fall by 30%, while approval rates for small business loans have increased by up to 20%. These aren’t just statistics—they’re the outcomes of intentional, focused strategies.
Yet challenges remain. Legacy systems create silos, limiting a bank’s ability to access and analyze data effectively. Regulatory scrutiny adds layers of complexity, requiring tools that can adapt to evolving rules. For many banks, navigating these hurdles begins with the correct data and technology integration approach.
Three Steps to Begin Your AI Journey
Getting started with advanced tools like AI can feel daunting, but it doesn’t have to be. Taking a measured, step-by-step approach often delivers the most success for banks.
Starting small and scaling gradually allows you to test strategies, refine your processes, and gain confidence before tackling larger initiatives. This approach minimizes risk and lays a solid foundation for long-term growth and innovation.
- Consolidate Your Data
The first step is to eliminate silos. Many banks operate with fragmented systems that prevent seamless access to customer data. Unifying these systems creates a single source of truth, enabling faster, more accurate decisions.
Case in Point: Capital on Tap accelerated its market adaptability and decision-making efficiency by integrating GDS Link’s credit decisioning platform. With this enhancement, their underwriting teams reduced credit rule adjustment time by 30% and piloted new credit models in less than four weeks. This streamlined approach enabled Capital on Tap to expand into the U.S. market and enhance their customer experience while achieving significant cost savings.
Discover how GDS Link’s platform transformed Capital on Tap’s operations and how it can do the same for you. Download the full case study now and explore the possibilities.
💡 Tip: GDS Link’s Decisioning Platform integrates over 200 data sources into one dashboard, including alternative credit data.
- Automate Risk Assessment with AI
AI enables financial institutions to analyze massive datasets in seconds, uncovering patterns that manual processes miss. Predictive models allow lenders to assess creditworthiness more accurately and quickly, improving decision-making across the credit lifecycle.
Example: GDS Link partnered with goeasy, a Canadian non-prime leasing and lending provider, to streamline their predictive modeling process using Predictive Model Markup Language (PMML). By implementing GDS Link’s solution, goeasy reduced their model deployment time by 50%, from 20 hours to just 5–10 hours, while improving accuracy. This transformation enabled them to implement more than eight models in a single system change, helping goeasy adapt quickly to an evolving market and enhance decision-making efficiency.
Want to cut deployment time in half like goeasy did? Access the case study now to learn the strategies behind their success.
💡 Tip: When evaluating predictive modeling solutions, prioritize platforms that support PMML (Predictive Model Markup Language). PMML enables seamless deployment of statistical models, reducing implementation time and errors—critical for staying agile in dynamic market conditions.
- Strengthen Compliance with Automation
Compliance isn’t just a regulatory necessity—it’s a competitive advantage when done efficiently. AI tools can monitor lending policies in real time, flagging potential issues and ensuring adherence to regulations like TILA and CRA.
Avoiding Common Compliance Pitfalls
The risks of non-compliance are real, and mistakes can be costly. In our blog, What You Need to Know About Compliance Pitfalls in Lending, we explore key challenges lenders face and how innovative technologies, like those offered by GDS Link, are paving the way for smarter, more adaptive compliance strategies.
Dive Deeper:
- Discover how the future of automated banking is reshaping compliance strategies: Download the eBook.
- Hear from Sarah Way Milovich, General Counsel and VP of Compliance at Carleton, on navigating TILA, APR, and lending compliance in our podcast: Listen here.
💡 Actionable Step: Use compliance automation to simulate policy changes and understand their impact before implementation.
Measuring Success
Implementing technology is not enough—you need to measure its impact. According to the Capitol Tech University blog, banks using AI see operational improvements and measurable increases in customer satisfaction. These tools enable institutions to tailor products and services, ensuring a more personalized experience for clients.
- Key Metrics to Track:
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- Reduction in loan processing times
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- Improved delinquency rates
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- Increased approval rates for underserved markets
Whether you’re a Head of Retail Banking looking to modernize branch operations or a Chief Risk Officer aiming to tighten credit policies, the time to act is now. Real-time data and AI integration aren’t just innovations—they’re necessities.
Learn More: Explore how GDS Link can transform your lending operations. Schedule a demo or download our latest solutions overview to see the tools in action:
