How AI can transform banking tech stacks

What does it take to deliver truly personalized banking at scale without sacrificing accuracy or trust? In this episode of The Innovators Exchange, Hiten Patel and Cosimo Schiavone interview Edward Maslaveckas, co-founder and CEO of Bud Financial, on the data foundations behind generative AI, the shift from broad marketing to tailored product recommendations, and how smaller US banks are partnering more readily with fintechs than many UK peers. Ed also unpacks why resilient operating models and disciplined training data are pivotal as AI-driven engagement tackles more complex customer needs. Tune in to hear the rest of their conversation: https://owy.mn/47hykOH

Discussed our insights from McKinsey's research "Unlocking Value From Technology In Banking: An Investor Lens" at a panel in Dallas hosted by the Mid-Size Bank Coalition of America and moderated by Vikram Nafde of Webster Bank. https://lnkd.in/gzgrAUDC At a time when banks are contemplating spending many billions on AI, the history of productivity from investing in technology in banking in the US is mixed. It comes as no surprise therefore that several articles in the press recently have questioned whether companies are seeing value from AI in their bottom-lines. Our answer: "Sprinkling AI sugar" doesn't help. Only those companies who are up for rewiring processes, changing organization and team structures and ways of working, retraining and apprenticing talent, and enabling a robust infrastructure that assures security, stability, reliability of the AI will see the value. While the technology is new, the problem is an old one. You're going to be hearing a lot more on this from us as the wave of companies who we are helping rewire start demonstrating the value from AI.

David vs Goliath in Banking: Are Mid-Tiers Winning the AI Race? I had a fascinating chat yesterday with a senior data governance lead who’s seeing a pattern: mid-tier banks are acting like David against the Goliath of Tier 1s when it comes to AI adoption. Tier 1s have long leaned on AI in domains like trading, credit risk modelling, and fraud detection. But their scale and complexity can slow down experimentation and enterprise-wide embedding. Mid-tiers, on the other hand, often empower business heads to roll up their sleeves, test ideas hands-on, and build use cases from the ground up. That agility gives them sharper insights into how AI can genuinely deliver efficiency and value across business lines. Industry data reflects this shift: leading banks are advancing AI maturity at twice the speed of laggards, with workflows like lending, onboarding, and document processing now top targets for AI transformation. If mid-tiers keep this momentum, with less legacy drag and more curiosity at the business level, they may well surprise the giants. What are you seeing? Are Davids really taking the lead, or will Goliaths pivot and reclaim the crown? Leading Point Rajen Madan Thushan KumaraswamyJaidip BanerjeeElin Bidmark Irène RocheSophie Monga Vinit Sahni Gaurav Sarin #AIAdoption #AIRiskManagement #Financialservices

From weeks to minutes. Most banks still take weeks to process unstructured data. Argiro’s AI-driven spreading module turns that into real-time insight: - Upload your financials. - Watch the platform deconstruct and process them live. - Ask questions. - Shape the output. - Get the intelligence you need, instantly. We’re already working with some of the region’s leading banks to make credit transformation a reality. This is what the future of banking looks like and it’s happening now. Hear from our Head of AI Joseph Roccisano

We recently brought together some of the brightest minds across global banks, insurers, and Databricks to tackle the big questions: What does true resilience look like in financial services today? How can data and AI drive not just efficiency, but also client trust and meaningful growth? The takeaway: thriving in 2025 requires openness, agility, and a bold new playbook for innovation and collaboration. Thanks to Will Turner from HSBC Innovation Banking, Mandar Purohit from Thrivent, Roshni Joshi, Mimi Park, and Antoine Amend from Databricks for sharing your insights! Learn more: https://lnkd.in/dCRdRFFn Kevin Fisher Lauren Raeburn Erin Butler Marcela Granados Lavoie #FinancialServices #AI #OpenBanking #Innovation #Leadership

Rewiring banks as we know it today to be truly AI-centric across the enterprise. Our upcoming flagship annual Global Banking report analyzes and discusses this rewiring in depth - trajectories, implications for the industry profit pools, what will determine winners, and much more. Ido Segev Saptarshi Ganguly Darius Imregun Atanas Stoyanov Pradip Patiath Klaus Dallerup Teresa Diviu Here's JPMorgan Chase's blueprint to become the first fully AI-powered megabank https://lnkd.in/eJyxiVEh

In the last edition of our newsletter, we heard from Henrique Figueira Lopes (Director of Analytics and AI at Nubank) and other global leaders on how to build successful AI strategies in risk management. Up next: How risk teams are turning open banking data into better customer experiences – and what’s still standing in the way. Whether you’re a seasoned professional or a curious learner, there’s a place for every voice in the conversation. Not signed up yet? Subscribe to The Risk Digest via the link in the comments 💬 #RiskManagement #RiskInsights #RiskCommunity

What must banks act on today to stay ahead of the curve? Rahul Nawab and Nagendra Sastry unpack the key AI shifts reshaping the banking industry now. Gain actionable insights by watching the interview here: https://hubs.ly/Q03LwvTL0 Co-presented by M. G. Science Institute and in collaboration with Simprosys InfoMedia #QuantumComputing #InnovationLeadership #ethicalAI #FutureOfAI

🌐 The Power of Data Science in Modern Banking In today’s rapidly evolving financial world, data science has become the heartbeat of innovation and decision-making in banking systems. Banks generate enormous volumes of data every day from transactions, customer behavior, and risk assessments to fraud detection and compliance monitoring. The challenge isn’t just collecting this data but transforming it into actionable intelligence. That’s where data science plays a critical role. Through advanced analytics, machine learning, and AI, banks can: ✅ Detect fraudulent activities in real time ✅ Personalize customer experiences and product offerings ✅ Enhance credit risk modeling and decision accuracy ✅ Streamline operations through predictive insights ✅ Ensure better compliance with regulatory requirements The true value of data science lies not in the numbers themselves, but in the clarity and foresight it brings to decision-makers. By integrating data-driven insights into banking systems, financial institutions can build more resilient, customer-centric, and future-ready operations. As we move deeper into the digital era, banks that embrace data science as a strategic asset, not just a technical tool, will define the future of finance. #DataScience #BankingInnovation #DigitalTransformation #Analytics

💡 “Customers can skip, but data never hides.” In today’s AI-driven recovery world, skip tracing isn’t about chasing — it’s about connecting dots smartly. Here’s how Banks & NBFCs are tracing skip customers faster 👇 🤖 AI & Analytics – Predict fresh contact or location links 📊 Credit Bureau Data – Reveal updated addresses or loans 📱 Digital & Social Footprints – Track job or city movement 🚗 Vehicle & GPS Trails – Identify asset movement 🧭 Field Apps – Blend on-ground & data intelligence AI + Data + Field = Smart Recovery, Zero Skip! #AIinBanking #SkipTracing #LoanRecovery #NBFC #DigitalCollections #Fintech #RBICompliance