How to Implement Agentic AI in Financial Services Safely

What is agentic AI and what role could it play in financial services? Why the next stage in AI is about adding automation to multi-step processes, helping financial professionals scale their expertise. Read more: https://lnkd.in/eAMrNs-G Partner Content by Moody’s #ai #innovation #financialservices Moody's Analytics

Data-Led Innovation with AI: Transforming Financial Services - Finextra Research: It recognizes that data quality is an ongoing process, not a one-time event. Instead of striving for perfection upfront, organizations focus on ...

"The magic isn’t in having AI take over entirely — it’s in creating partnerships where both human and machine intelligence contribute their unique strengths, together." - Oliver King-Smith, Founder and CEO, smartR AI. This quote perfectly captures the future of finance! Our new article on Finextra details how financial services are leveraging "Assistive Intelligence" to drive innovation. We're not aiming for "artificial" intelligence, but for a powerful partnership. Learn how to embrace this new paradigm: https://lnkd.in/dgEAd4k7

There’s a simple truth behind AI success in finance: poor quality data means poor quality outcomes. Publicly available datasets might fuel experimentation, but regulated financial institutions need trusted, traceable, and governed data to deploy AI safely and effectively. @Ron Lefferts and @Gianluca Biagini, explain how we’re enabling financial institutions to unlock AI’s full potential, powered by decades of expertise in data quality, governance, and delivery. https://lnkd.in/dRwuzZ2u

The AI Inflection Point – Volume 1: Financial Services How AI Is Transforming Financial Services — with Evidence, Not Promises Artificial Intelligence has progressed beyond prototypes. The question for financial leaders today isn’t “Can AI work?” — it’s “Can it deliver measurable business value?” 📗 Infinidatum Press is proud to announce the release of The AI Inflection Point – Volume 1: Financial Services, a landmark evidence-based study examining real-world AI deployments at leaders like Ramp, Nubank, Coinbase, RBC, and Stripe. Unlike typical “AI trend” books, this volume emphasizes proof over hype. Each case study features: ✅ Verified ROI and performance metrics ✅ Transparent data sources and confidence levels ✅ Architectural diagrams and implementation lessons ✅ Cross-functional takeaways for executives, engineers, and regulators ✅ ROI analysis for Credit Unions and smaller institutions included. Every chapter includes a full evidence ledger — tagging each claim as [D] Disclosed, [C] Calculated, or [E] Estimated — setting a new standard for transparency in AI business writing. 💡 Why Executives and Practitioners Should Read It For executives → clear insights into where AI creates returns, what doesn’t work, and how to invest responsibly. For AI & data leaders → ready-to-use blueprints for deploying LLMs, RAG systems, and foundation models in regulated settings. You’ll learn how to: Turn proprietary data into competitive advantages Build audit-ready RAG pipelines for financial compliance Design AI architectures with human oversight Measure ROI, reduce hidden costs, and grow responsibly   ⚙️ The Infinidatum Difference At Infinidatum, we prioritize transparency in AI adoption. Our frameworks, tools, and publications turn AI deployment from Guesswork into science — helping CEOs, CAIOs, and regulators gain confidence in measurable AI impact.   🌐 Explore our comprehensive AI-Risk Analysis and Compliance ecosystem at www.infinidatum.com   Check out our flagship products, RiskLens and Compl.y   📖 Available Now The AI Inflection Point – Volume 1: Financial Services Published by Infinidatum Press LLC (2025) ISBN 979-8-9935232-3-1 (Paperback) • 979-8-9935232-0-0 (eBook) 📈 Now on Amazon → https://lnkd.in/eZc6MM2d   🌍 Learn more → www.infinidatum.com 🔖 Hashtags for Reach #AIROI #AIGovernance #FinancialServices #AICompliance #ResponsibleAI  #AITransformation #EUAIAct #LLM #RAG #AIRISK

The potential of AI in financial services is extraordinary – from transforming workflows to unlocking actionable insights in seconds.   But without trusted data, AI can’t deliver on its promise. Financial institutions rely on precision, accuracy, and accountability. And that’s exactly where LSEG’s data makes the difference.   Ron Lefferts and I share our perspective on how trusted data underpins AI innovation in our new blog: https://lnkd.in/eFYA8cgr I’m proud of how LSEG is helping our customers adopt AI responsibly, at scale, and with confidence in every decision.   #LSEG #AI #FinancialInnovation #TrustedData #AIFinance  

Artificial intelligence is transforming financial services, but its success depends on one thing above all: trusted data. In our latest blog on https://www.lseg.com, Gianluca Biagini and I explore why high-quality, accurate, and well-governed data is the essential foundation for AI in finance. At LSEG, we’re helping the world’s leading institutions embed AI into their workflows with confidence – combining depth, breadth, and reliability of data with an open, LLM-agnostic approach. Read how we’re enabling financial firms to scale AI responsibly and effectively: LSEG Everywhere: Trusted Data for AI https://lnkd.in/dNNAxdUY #AIinFinance #TrustedData #LSEG #DataAnalytics #FinancialServices #AITransformation

Newly released results from the IIF - EY Annual Survey on AI Use in Financial Services ‼️ 🌏 🌎 🌍 ‼️ 💯 All financial institutions will increase their investments in AI in the near future. 36% of Global Systemically Important Banks (G-SIBs) will double their spending on AI in the coming 12 months. 📈 80% of financial services firms are working on Agentic AI, to varying degrees. Indicating a faster progression than seen in earlier AI systems. 🧱 8 out of every 10 firms report that data quality is the top challenge for deploying AI systems in production. ☁️ Financial institutions increasingly use third-party models to overcome challenges for deploying AI systems; however, difficulties in securing documentation and testing artifacts from vendors could affect these relationships going forward. 🔐 81% of firms identified that the best regulatory/supervisory approach consists of a joint exploration of parameters, where FIs and AI service providers define responsibilities together with the authorities. This and more key insights into the use of AI in global finance are part of the report jointly published by the Institute of International Finance and EY. To learn more about the state of AI in the industry, see the full report at: https://lnkd.in/ehXS5UTq A special thanks to the project team that made this possible❗ Tom Campanile Jan Zhao Ryan Moore, CFA Chelsea Nichols Jessica Renier Conan French Lokesh Bulchandani

Superintelligence is not one thing... there are multiple AI 'endgames.' Every problem has a time horizon: how long an agent must persist to complete it. Let's group problems (and the AIs that solve them) by the time horizon required for the task: Short: 1 second - 1 hour Medium: 1 hour - 1 day Long: >1 day Imagine hiring someone. Are you hiring a contractor to build a building? Or a kid to mow your lawn? The different time horizons require these 'agents' working for you to approach decision-making, context, and autonomy differently. ⚡ Short Time Horizon → “Assistants” or “Copilots” These AIs work interactively, helping people move faster. They compress the loop between thought and action: finishing your sentence, cleaning your spreadsheet, or visualizing an idea before you can explain it. What matters is speed, context, and seamless integration. Superintelligence here means "superproductivity:" compressing time, not replacing humans. It means multimodal interfaces (visual, audio, neural). It means deep, ubiquitous integration (imagine going up to any screen and having "your" assistant, with your data securely available, just 'being there'). There will always be short-horizon problems. We’ll always need systems that act in milliseconds, adapt instantly, and blend smoothly with human intuition. ⚙️ Medium Time Horizon → “Agents” (and swarms, and workflows) Agents act autonomously over hours or days. They hold context, make decisions, and adapt within boundaries you define. What matters is alignment, feedback, and safety mechanisms that prevent small missteps from scaling into large failures. Superintelligence here means strategic autonomy: agents that can reason about tradeoffs, ethics, and constraints as well as a human team, but faster and more consistently. This means 'AI security systems' and 'AI candidate review' and 'AI Inventory audit' and so on. This is also where most “evil AI” stories live: medium-horizon systems that drift out of alignment one decision at a time, like a weapons systems that targets the wrong thing. These problems won’t go away; any world with autonomous agents will always need oversight, correction, and trust frameworks that evolve with them. 🏗️ Long Time Horizon → “Dynamic Workflows” or “Virtual Employees” These AIs persist over time. They manage goals that evolve, coordinate across resources, and balance competing objectives. What matters is memory, temporal reasoning, and continuity of purpose. Superintelligence here means adaptive governance: systems that can manage organizations, economies, or defense systems continuously. A “superintelligent defense command structure” (as opposed to a superintelligent weapon system) fits here. Superintelligence isn't one thing. It's a placeholder term for perfecting different kinds of AI systems.

Artificial intelligence is no longer just a technology; it’s a credit risk. Moody’s developed two scenarios to model AI’s impact across sectors: Conservative: A slow rising tide of AI integration leads to better efficiency and margins without materially altering competitive hierarchies. Optimistic: Rapid AI advances create fast-moving credit effects with a far greater risk of competitive displacement for firms slow to adapt. https://shorturl.at/I8509