Redefining AI in Finance: A New Approach to Payments and Banking
Artificial intelligence (AI) often takes center stage in tech discussions, but when it comes to finance, it’s becoming clear that subtler applications can drive significant improvements. i2c, a leader in payment and banking solutions, exemplifies this trend by leveraging AI not as a replacement for human capabilities but as an enhancer of operational efficiency.
A Decade of Innovation
John Bresnahan, the global head of operations at i2c, emphasizes that their journey into AI isn’t just a trend; it has been evolving for over ten years. i2c views AI as “augmented intelligence,” aiming to empower human roles rather than eliminate them. This perspective fosters a culture where AI integrates seamlessly into various functions—including fraud detection, compliance, and customer service—yielding real impact rather than mere novelties.
The Evolution of AI in Financial Services
As many financial organizations wrestle with outdated tech or dive into generative AI, i2c sets itself apart with mature AI models that enhance risk management and customer service on a large scale. With over 50 dedicated AI analysts and cross-disciplinary strategies, they are transforming financial services from the inside out.
However, a significant challenge persists in the form of “data silos,” which can restrict the flow of information within AI systems. To combat this, i2c has developed a unified infrastructure that allows data from various domains—fraud models, dispute workflows, and human decisions—to inform each other effectively.
Cutting-Edge Solutions: SecureAuth 3.0
Among i2c’s notable innovations is SecureAuth 3.0, a sophisticated fraud detection model that effectively identifies 40% of total fraud volume across its platform. What’s remarkable is that it maintains a mere 0.5% fraud decline rate, striking a delicate balance between thorough fraud prevention and customer experience.
AI’s strength lies in its ability to analyze hundreds of behavioral signals in real time—factors such as transaction history and contextual details—to create a dynamic risk score. Unlike traditional systems that rely on static rules, these models adapt as new data emerges, enhancing their ability to detect threats that might otherwise escape notice.
Keeping Pace with Change
i2c sets itself apart by retraining its AI models every three to four months, a stark contrast to many institutions that often update their systems only annually. This approach minimizes "model drift," where outdated systems become ineffective under new conditions. Bresnahan suggests the possibility of even shorter retraining cycles in the near future, underlining a commitment to responsiveness and transparency—if an AI decision cannot be explained, it is not integrated into their system.
AI at i2c does not work in isolation. High-risk events trigger automated responses but ambiguous scenarios are escalated to human experts. This hybrid approach—combining AI efficiency with human judgment—is what Bresnahan terms "commonsense intelligence."
A Future Built on Collaboration
Ultimately, i2c’s model isn’t about flashing headlines but about creating operational frameworks that deliver impactful results. Thanks to AI, compliance rates have surged, and real-time problem identification has become the norm, ensuring that no compliance gaps go unnoticed.
Looking forward, i2c aims to broaden the range of signals used in its decision-making processes while further refining its AI models. As the financial landscape becomes more data-rich and regulatory expectations heighten, the demand for robust, explainable AI solutions is likely to grow, marking an exciting evolution in the integration of technology and finance.
In a world where efficiency and security are paramount, i2c’s approach may pave the way for a new standard in how AI transforms the financial sector.
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Bio: Priya specializes in making complex financial and tech topics easy to digest, with experience in fintech and consumer reviews.