PING AN’s Post

🤖 AI is set to redefine the banking sector. And over the next five years, its successful adoption will determine who remains (and who emerges) as leaders in the industry. 📈 From boosting algorithmic trading to revolutionizing customer interactions, the technology is shifting from supportive business tool to strategic driving force among today’s market players. 💡 Our report outlines the critical considerations for safe and effective #AI implementation, shedding light on its benefits, limitations, and the wave of new opportunities it brings. 👉 Discover how AI is reshaping the future of #banking and capital markets: https://deloi.tt/3Nb9cQc #DeloitteLU #Technology Patrick LAURENT | Pascal Martino | Nicolas Griedlich | Giulia Pescatore

“Things happen slower than you think they should, and then they happen faster than you think they could.” While still in the early stages of the generative AI hype cycle, it’s clear that this powerful technology will have a huge impact on every aspect of our lives and the way we work in the coming years—bringing with it new opportunities and new risks requiring a thoughtful, well-managed approach. This isn’t just a shiny new toy you can sit back and observe or dip your toe into. You need to make the jump and really learn about the tech underpinning generative AI so that you’re aware of the risks, understand the capabilities and limitations, and can identify which use-cases will be most beneficial for your teams to prioritize. As noted in the Evident AI Index rankings, Capital One is well-positioned to thrive in this dynamic space thanks to our incredibly talented associates and our culture of innovation. I’m proud of the substantial work our teams are doing to advance responsible and balanced approaches to AI development and deployment that will improve our customers’ lives.

🚀 Scaling Generative AI in Banking: Choosing the Best Operating Model 🚀 Generative AI (gen AI) is revolutionizing the banking industry, from enhancing customer interactions to preventing fraud and speeding up regulatory processes. But how do financial institutions choose the best operating model to scale gen AI effectively? 🔍 Key Operating Models: 1. Highly Centralized: Fast skill and capability building, but potential silos from decision-making processes. 2. Centrally Led, Business Unit Executed: Better integration with business units, though execution can be slower. 3. Business Unit Led, Centrally Supported: Easier buy-in from business units, but challenging to implement across various units. 4. Highly Decentralized: Quick buy-in and relevant insights, but risks lacking centralized knowledge and best practices. 📊 What Works Best? At this early stage, highly centralized models are leading the way, with about 70% of such institutions progressing to production use cases. This model allows for focused resource allocation and rapid movement from experimentation to production. As gen AI technology evolves, financial institutions may shift towards more federated designs, balancing centralization with flexibility. 💡 Key Takeaway: Centralized steering helps focus resources and tackle challenges efficiently, but flexibility and integration with business units are crucial for long-term success. https://lnkd.in/dqyhSvp3 #GenerativeAI #BankingInnovation #AI #FinancialServices #TechTrends 4Enlight, AI Innovation Lab, AI Research Lab, Advanced Prompt Engineering

Unlock the Power of AI with Payarc - Digital Transactions https://buff.ly/3Xf51r4 #Payarc #AI #Technologies #FinTech #payments #processing #partner #benefits #services #transactions #approvals #GenerativeAI

How AI can transform financial services? DataArt's latest report with Arkwright Consulting unveils revolutionary insights into how AI is shaping the industry, driving innovation, and creating value for both financial institutions and customers. 🔹 Tailored Growth: AI enables financial institutions to deliver personalized solutions, boosting customer loyalty and driving revenue growth through data-driven insights and superior customer engagement. 🔹 Operational Efficiency: Beyond enhancing customer interactions, AI optimizes backend operations, driving efficiency gains and reducing costs. This allows for strategic investments in innovation. 🔹 Advanced Risk Management: AI is pivotal in real-time risk detection and regulatory compliance, helping financial organizations proactively address risks, ensuring stability, and maintaining a strong reputation. Explore these insights and more in our comprehensive report, "AI's Potential in Banking and Payments." Read the full report here: https://lnkd.in/eADcPTtv #AI #Payments #innovation #riskmanagement

📢 We're excited to present our joint report with Arkwright Consulting, which explores how #AI is reshaping retail #banking and #payment systems. The paper cuts through the hype to present a clear path for financial institutions to improve their operations and stay competitive using AI. The report, which uses insights from experts in the field, is a valuable resource for companies ready to integrate AI strategies effectively. Discover how AI can redefine your business from the ground up and generate growth opportunities. Access the full report now! #dataart #dataart_finance #dataart_insurance #arkwright #arkwright_consulting #report #artificialintelligence #retailbanking #aistrategy

generative AI has the potential to transform #openbanking by enabling new levels of personalisation, risk management, client engagement, product innovation, regulatory compliance, and market analysis. In the digital age of banking, banks may gain a competitive advantage and provide higher value to clients by leveraging the power of #generativeai. #PersonalisedFinancialadvise Generative AI can analyse massive volumes of financial data and consumer preferences to provide tailored financial advise. #MarketAnalysisPrediction Generative AI can analyse market data and offer predictive insights to help open banking ecosystem stakeholders make strategic decisions. #CreditRiskAssessment Generative AI algorithms can produce synthetic data to supplement conventional credit risk assessment methodologies. #FraudDetectionPrevention Generative AI systems can analyse transactional data to find trends that indicate fraudulent behaviour. #productinnovation Generative AI can spur product innovation by producing new ideas and concepts based on market trends, customer feedback, and competitor analysis.

Financial institutions can use AI to offer predictive pricing, based on a combination of historical and real-time data.

Generative Artificial Intelligence (Gen AI) holds immense potential for transforming the banking and financial industry. We believe that GenAI will have a significant impact on productivity in the areas of general communication, customer satisfaction and dealing with technical debt.

According to a 2021 McKinsey & Company study, AI has the potential to unlock $1 trillion of incremental value for banks every year. This staggering figure underscores the transformative power of AI in the financial services sector. But realizing this value requires more than just adopting new technology—it demands a strategic approach to integrate AI seamlessly into existing operations. Organizations in the financial services space must navigate complex regulatory landscapes, optimize AI-driven processes, and ensure robust data security measures. The journey to harnessing AI's full potential is intricate, but the rewards are substantial. The bottom line: AI is not just a tool but a catalyst for unprecedented growth and innovation in banking. Let's embrace this opportunity to revolutionize the financial industry together. #AI #Banking #FinancialServices #Innovation #TechTransformation #ValueCreation