GNCI’s Post

The Future of Banking

The Future of Banking with Generative AI! 🚀   Join us in an insightful video interview with Daragh Morrissey, Director of Artificial Intelligence at #Microsoft Worldwide Financial Services. `𝐃𝐞𝐦𝐲𝐬𝐭𝐢𝐟𝐲𝐢𝐧𝐠 𝐆𝐞𝐧𝐀𝐈 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐢𝐧 𝐁𝐚𝐧𝐤𝐢𝐧𝐠` In this conversation, we explore the transformative potential of Generative AI in Financial Services. Daragh shares his expertise on: - Early use cases of Generative AI in banking - The relationship between Predictive and Generative AI - The data work required for deploying GenAI processes - Overcoming data silos safely - The cultural changes needed for AI-driven organizations - The future evolution of banking as AI gets smarter   Chapters: - 00:00 Introduction and Guest Welcome - 03:20 Generative AI in Financial Services, Early Use Cases - 07:35 Predictive AI vs. Generative AI – Collaboration or Competition - 15:18 Demystifying GenAI deployment in Banking – Data, Training - 17:21 Is the Data madness continuing? - 19:22 What is different this time & Examples - 24:18 Thoughts on the Evolution of Banking as AI gets Smarter - 26:13 Areas of Impact in Banking Link to full video discussion 👉 https://lnkd.in/ddAmBagj Links to your favorite podcast platforms in the comments. #banking #fintech #AI #data #GenAI #LLMs #efiinsights      Enjoy the snippet below

Byte Sized AI: AI in Finance: Revolutionizing Banking and Investments 💸 AI in Finance applies machine learning algorithms to analyze financial data, automate trading, detect fraud, and personalize customer experiences. - It enhances decision-making and risk management in banking and investment sectors. - Applications include algorithmic trading, credit scoring, and customer service automation. Example: Developing AI-driven predictive models to forecast market trends and optimize investment portfolios based on real-time data analysis. #AITopics #AIinFinance #MachineLearning

AI advancements in the banking sector are rapidly reshaping the industry landscape. Forbes' latest article delves into the 2024 trends, highlighting key areas where AI is making a significant impact: - Hyper-personalization: Tailored financial products and services driven by AI. - Enhanced fraud detection: AI systems boosting identification and prevention of fraudulent activities. - Conversational AI: Chatbots revolutionizing customer service and support. - Automated loan underwriting: AI streamlining loan approval processes. Explore the future direction and potential challenges of AI in banking: [Link to the article] #AI #Banking #Fintech #Forbes #TechCouncil

📊 9.6%: That’s the market share of Gen AI in the Banking, Financial Services, and Insurance (BFSI) sector, as highlighted in a recent study by Kumari, Kaur, & Swami (2024). For an industry where AI promises transformative capabilities—such as enhanced profitability, proactive credit risk management, and seamless contactless solutions—this number seems remarkably low. The study reveals that while the benefits of AI are clear, foundational barriers like structured data availability and data-fluent resource allocation are holding back widespread adoption and capability development. Data readiness, is a critical enabler—without it, AI efforts don’t make it out of the gate. This study, Adoption of artificial intelligence in financial services: a policy framework, suggests a focus on foundational data governance and quality control around structured data as well as infrastructure and resource training before diving deep into Gen AI at scale. Do you agree? I’d love to read your thoughts. Also, I’d love to hear your take: What do you see as the biggest challenges to AI adoption in financial services today? Incidentally, you can read the study here: https://buff.ly/3ZEpeZI #ArtificialIntelligence #DataStrategy #FinancialServices #Ortecha #DigitalTransformation #DataManagement #AIAdoption

We recently discovered a significant improvement in one of our bank statement analysis project. We were using GPT-4o to analyze bank statements, but it kept messing up. For a 6 month SME bank statement with about 1800 transactions, it got 6 end-of-day balances wrong and messed up around 63 transactions. But then we switched to Claude 3.5, and boom! 💥 ~Zero errors so far. This could be a game-changer for our financial analysis work. It's crucial to remain adaptable and open to switching to more advanced models when necessary. Here's why: 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐢𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧: The field of LLMs is experiencing rapid advancements, with new models and capabilities emerging frequently. 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐯𝐚𝐫𝐢𝐚𝐭𝐢𝐨𝐧𝐬: Different LLMs may excel in various tasks or domains, so it's beneficial to explore alternatives if your current provider doesn't meet your needs consistently. 𝐀𝐯𝐨𝐢𝐝𝐢𝐧𝐠 𝐨𝐯𝐞𝐫-𝐫𝐞𝐥𝐢𝐚𝐧𝐜𝐞: While LLMs can be incredibly helpful, it's important not to become overly dependent on a single provider or model. 𝐌𝐚𝐱𝐢𝐦𝐢𝐳𝐢𝐧𝐠 𝐛𝐞𝐧𝐞𝐟𝐢𝐭𝐬: By staying open to switching to more powerful models, you can ensure you're leveraging the best available technology for your specific needs. Remember, the goal is to harness the most effective tools while maintaining a balanced and informed approach to AI integration. #AI #FinTech #GenAI #Claude #FSMK

HOT OFF THE PRESS IDC just published a sweeping examination of use cases for generative AI (GenAI) across all industries. The Generative AI Use Case Taxonomy for Banking is a deep dive into the business and IT areas in the banking industry that will be transformed by this innovative technology. IDC continues to lead the industry in the analysis and advice of adopting technologies like GenAI and their impact to financial services. IDC

This is a carefully curated list of use cases that are both practical and significant, for bankers planning or implementing Generative AI. Jerry Silva Marc DeCastro Maria Adele Di Comite Aaron Press Raymond Pucci Tom Zink

AI and ML are revolutionizing the banking sector. (And it's happening faster than you think.) In our latest blog post, we explore how these groundbreaking technologies can be applied in banking services: - Dynamic pricing - Automated credit checks - Personalized recommendations - Customer segmentation - Churn prediction Discover how you can make your bank more efficient and customer-centric with AI and ML! 👉 Don’t miss out! Read the full post here: https://buff.ly/3WUfjNm #AI #MachineLearning #BankingInnovation #Fintech #DigitalTransformation #Syntheticaire

Unleashing the Potential of Generative AI in the Banking Sector: McKinsey estimates that Gen AI could annually increase in value by a staggering $2.6 trillion to $4.4 trillion globally (https://lnkd.in/gbpX6PrV). Financial services are anticipated to be one of the most significant prospects among industries, with a yearly potential of $200 billion to $340 billion, mainly due to increased productivity. Read how InferIQ’s Advanced AI-powered Intelligent Document Processing Platform transforms data extraction for banking. https://lnkd.in/gCrqtDpU #banking #generatieveai #financialservices #banks