Post de Guillaume Bour

David Rice, COO of HSBC, shares how AI will revolutionize how banks operate, making them faster, easier to work with, and more proactive. With access to data across 62 markets, HSBC is positioned to provide customers with powerful insights that go beyond traditional banking. From unlocking new revenue streams to optimizing business operations, AI is setting the stage for a smarter, more efficient future. And it’s not just about technology—it’s about making AI work safely and ethically to benefit everyone. Curious how AI will shape the way banks and businesses grow? Watch the full video to find out 🎥

What’s the game-changing insight that could redefine #banking as we know it today? Don't miss out on our upcoming webinar where I'll be presenting groundbreaking insights from our latest research with #Qorus, "AI at Work: Turning AI Potential into Results." 🔍 Research Focus: #CustomerExperience, #OperationalExcellence, #EmployeeExperience, #RiskManagement I've interviewed on behalf of UiPath key decision-makers from leading banks around the world to explore how AI is reshaping these critical areas. Find out from top experts and real-world success stories. Join this UiPath webinar on July 4 at 10:00 AM CET. See you soon! #AI #Banking #Webinar #CustomerExperience #OperationalExcellence #EmployeeExperience #RiskManagement #FutureOfBanking #Innovation #Leadership #UiPath

First Belgian AI Barometer reveals transformative impact on Financial Institutions 🚀🌟 The report by FINTECH BELGIUM and Sailpeak offers a comprehensive overview of AI’s integration within the Belgian banking and insurance industries, underscoring the ongoing shift towards digital transformation. By surveying 17 key institutions and conducting in-depth interviews with industry leaders, the report furthermore highlights the current landscape and future potential of AI in financial services. Key findings demonstrate significant Artificial Intelligence (AI) adoption within Belgium’s financial sector. Predictive AI is widely implemented, with 84% of institutions utilizing it for applications such as customer segmentation, fraud detection, and risk modeling. This technology is particularly mature in marketing (61%) and insurance operations (58%), enhancing processes like underwriting and claims processing. Generative AI, while in its early stages, is being explored by 79% of institutions, particularly in marketing and customer-focused areas, with projects like chatbots and personalized communication. We want to extend our heartfelt thanks to everyone who contributed to this pioneering report. A special thank you goes to the banks, insurance companies, Fintechs, partners, and clients. Your invaluable support and insights were crucial in making this report a reality! Learn more and download the full report here 👉 https://lnkd.in/eKQxCtEH Nico Vincent, Léonard Baesen-Wagner, Bjorn Cumps, Jean-François Heering, Alessandra✨ Guion - Gambrill, Frédéric MARTIN, Jonathan Neubourg, Izabella Molnar, Anthony Belpaire, Charlotte De Meyer, Pieter Desmedt, Frederic Lebeau, Quentin Felice, Jos Gheerardyn, Jo Cijnsmans, Bart Coppens, Ann Vanlommel, Fabrice Deprez, Ethias, Belfius, BNP Paribas Fortis, Baloise BE, Yields, Argenta, Datavillage - Confidential Data Collaboration, Centre for Finance, Innovation and Technology (CFIT), Intelli-Select, Clearstream, Discai, Crelan, Duco, Europ Assistance, iBanFirst, Mifundo, Febelfin Academy, Assuralia, FINTECH BELGIUM, Sailpeak #fintechbe #News #FinancialServices #AIBarometer

How can banks get ready for an AI future? 🏦 With gen AI expected to add up to $340 billion in annual value, banks are gearing up to integrate this technology effectively across all functions. From boosting productivity to potentially revolutionizing customer interactions, gen AI offers a wide range of opportunities for banks. Learn how leading institutions are scaling their projects to capture significant economic benefits. https://mck.co/3YN1O30 #NeverJustTech

Fintech isn’t dead.  It’s at a new beginning 🚀     Tech in financial services adapts/ creates large opportunities in every product cycle.  We are just at the beginning with AI. 🖥 Product cycle: PC/Internet era Fintech wave 1: “put it on a website”  👉 LendingClub started to make loans on the internet (vs. in bank branches) 📱 Product cycle: Mobile  Fintech wave 2: Mobile/Full Stack 👉 Chime built full stack bank w/ “get your paycheck early” wedge, Robinhood built free mobile trading w/ fractional shares ☁ Product cycle: Cloud  Fintech wave 3: "Every company is a fintech" 👉 Every layer of the stack “as a service” so companies could monetize/retain customers with fintech (Moov for payments, Sardine for fraud etc.).  🧠 NOW Product cycle: AI Wave 4: “AI inside” (tm Intel:) — we are just at the beginning but will include: 1️⃣ Labor becomes software:  Financial institutions have many of the white collar jobs that will soon have co-pilots & agents (compliance officers, insurance claims adjusters etc.) 2️⃣ Enterprise customers WILL rip and replace legacy software: Banks are full of SW (Black Knight, FIS, FiServ) built 20-30+ years ago.  The AI driven newcos are 10x better.  Banks/insurance cos are already rip/replacing. 3️⃣ Sales/marketing/finance: FIs/Insurance companies have huge sales & marketing teams, large financial back offices.  This labor spend is an opportunity for AI too. 4️⃣ Default global: AI companies cross borders & span multiple industries even earlier in their lifecycles.  They will require more cross border extensibility, flexibility, speed.  New infra cos will be built to support.  Startups from Waves 1,2,3 are best suited (vs. incumbents) to adapt quickly and are "adding AI". New companies are emerging fast. Fintech may need a new name, but the concepts/ investment opportunities are more powerful than ever.  (requisite message from our compliance team: The above is not intended to be investment advise. Please visit a16z.com/ investment-list for a full list of a16z portfolio companies)

Fintech isn’t dead.  It’s at a new beginning 🚀     Tech in financial services adapts/ creates large opportunities in every product cycle.  We are just at the beginning with AI. 🖥 Product cycle: PC/Internet era Fintech wave 1: “put it on a website”  👉 LendingClub started to make loans on the internet (vs. in bank branches) 📱 Product cycle: Mobile  Fintech wave 2: Mobile/Full Stack 👉 Chime built full stack bank w/ “get your paycheck early” wedge, Robinhood built free mobile trading w/ fractional shares ☁ Product cycle: Cloud  Fintech wave 3: "Every company is a fintech" 👉 Every layer of the stack “as a service” so companies could monetize/retain customers with fintech (Moov for payments, Sardine for fraud etc.).  🧠 NOW Product cycle: AI Wave 4: “AI inside” (tm Intel:) — we are just at the beginning but will include: 1️⃣ Labor becomes software:  Financial institutions have many of the white collar jobs that will soon have co-pilots & agents (compliance officers, insurance claims adjusters etc.) 2️⃣ Enterprise customers WILL rip and replace legacy software: Banks are full of SW (Black Knight, FIS, FiServ) built 20-30+ years ago.  The AI driven newcos are 10x better.  Banks/insurance cos are already rip/replacing. 3️⃣ Sales/marketing/finance: FIs/Insurance companies have huge sales & marketing teams, large financial back offices.  This labor spend is an opportunity for AI too. 4️⃣ Default global: AI companies cross borders & span multiple industries even earlier in their lifecycles.  They will require more cross border extensibility, flexibility, speed.  New infra cos will be built to support.  Startups from Waves 1,2,3 are best suited (vs. incumbents) to adapt quickly and are "adding AI". New companies are emerging fast. Fintech may need a new name, but the concepts/ investment opportunities are more powerful than ever.  (requisite message from our compliance team: The above is not intended to be investment advise. Please visit a16z.com/ investment-list for a full list of a16z portfolio companies)

[#EVENT] How is #AI transforming the way we work? This essential technology was at the heart of ‘My Digital Days’, our global event dedicated to innovation and digital transformation. What opportunities does AI offer, and how can we learn to maximise them? These questions were at the heart of discussions during the two-day conferences and workshops : 👉 Banking in the era of artificial intelligence: Xavier Musca, Chief Executive Officer and Deputy Chief Executive Officer of Groupe Crédit Agricole in charge of the Large Clients division, Pierre Dulon, Deputy General Manager in charge of IT & Operations Services Emmanuel Sardet, Deputy Chief Information Officer Group at Crédit Agricole S.A. and Chief Technical Officer Group franck DESAUTY, Head of AI Factory (Artificial Intelligence) and Aymen SHABOU, PhD, CTO & Head of AI at DataLab Groupe Crédit Agricole kicked-off the event with a deep dive into the banking sector in the era of Artificial Intelligence. In our second conference, Anne-Catherine Ropers, Deputy General Manager and Global Head of Human Resources, Jeremy Lamri, CEO Tomorrow Theory, Romaric Rollet, Head of Innovation, Thomas LEMONNIER, Global Coverage & Investment Banking, Coverage Banker, and Julien Cocault, Global Markets Division, Sales IT Programme Director. We delved into the impacts of generative AI on the future of work, providing valuable insights into the opportunities that lie ahead. 👉 Discover the latest practices and innovations in the digital world: Participants had the chance to experience the power of AI firsthand through workshops. An open forum also showcased the latest digital innovations, highlighting our ongoing commitment to digital transformation. Take a look back at the event through these pictures 👇 Thank you to all the participants and speakers for their contributions! 🌐🚀

Transforming Bank Guarantee Risk Assessment with Big Data: A New Era of Financial Precision Big data is revolutionizing how financial institutions assess risks in bank guarantees. By leveraging advanced data analytics, banks can now make more informed, accurate, and timely decisions. Here are 10 key points on how big data enhances risk models for bank guarantees: 1. Comprehensive Data Analysis: Big data allows banks to analyze vast amounts of information, including market trends, borrower history, and global economic factors. 2. Real-Time Insights: By processing data in real-time, banks can quickly adapt to changing market conditions, improving their risk assessments. 3. Increased Accuracy: With more data to analyze, risk models become far more accurate, reducing the likelihood of defaults. 4. Predictive Analytics: Machine learning algorithms can forecast future risks, helping banks make proactive, data-driven decisions. 5. Custom Risk Models: Big data enables the creation of highly personalized risk models, tailored to specific industries or clients. 6. Enhanced Decision-Making: Data-driven insights help banks make faster, more informed decisions about issuing guarantees. 7. Risk Reduction: Big data analytics allows institutions to identify potential risks early, mitigating them before they become critical issues. 8. Competitive Advantage: Financial institutions that adopt big data gain a significant edge over competitors still relying on traditional risk models. 9. Automation of Risk Assessments: Big data and AI can automate much of the risk assessment process, saving time and resources. 10. Future-Proofing Guarantees: By continuously refining models using big data, banks ensure their guarantees are resilient and future-ready. Embrace big data to transform your bank guarantee risk assessments and drive smarter financial decisions. #BigData #Fintech #BankGuarantees #RiskManagement #DataAnalytics #MachineLearning #FinancialSecurity #FinanceInnovation #AI #PredictiveAnalytics