AI & Fintech: Can We Put Our Trust Into Autonomous Payments?
There are two distinct areas defining the transformation of the financial industry today and one of them is embracing AI, but not without risk. As Agentic AI automates payments and lending, algorithms can amplify bias, threatening the entire credibility banking is built upon. To tackle these widespread challenges, the industry is taking on a more collaborative approach by joining banks, fintechs and policymakers alike. Expert Amanda Estiverne-Colas, Director and Head of Payments Practice at Perficient, says human oversight and empathy are non-negotiables in our financial responsibility to keep banking human amidst the changes. Read the entire article: To Build Fintech for Everybody, Combine the Speed of a Startup with the Soul of a Community Bank Our community question is: What technical measures (like data cleansing) should IT/Storage teams prioritize to ensure AI models remain trustworthy and fair? Click through to read the entire article above and let us know your thoughts around it in the comments below!Accelerate Breakout Replay: GenAI in Finance: Simplified, Scalable, and Ready for Real Time
This session covers simplified deployment, RAG workflows, reliable networking, real-time insights, and scalable AI compute for secure, low-latency finance AI. Speakers: Mike Russo Philip Ninan Jon Owings Ryan Avery, WWT Ed Chapman, Arista Kevin Curtis, Supermicro Prabhu Ramamanmoorthy, NVIDIA Nataraj Dasgupta, KX Systems https://www.purestorage.com/video/webinars/gen-ai-in-finance-ready-for-real-time/6375812645112.htmlAccelerate Breakout Replay: Leveraging the Power of AI to Gain Competitive Advantage in Capital Markets
See how Pure Storage + KX power real-time GenAI insights in capital markets, using ultra-low latency vector databases and fast data access. Speakers: Mike Russo Rob Glanzman https://www.purestorage.com/video/webinars/leveraging-the-power-of-ai-competitive-advantage/6375341256112.htmlAI in Finance Summit New York
AI in Finance Summit New York Pure Storage is a platinum sponsor of the AI in Finance Summit in New York on April 15th and 16th. Stop by our booth to learn about how Pure can help with your enterprise AI initiatives and be sure to check out Michael Cornwell's keynote address on the 15th. At the AI in Finance Summit, where cutting-edge research meets application in financial services, explore exclusive insights and advanced technical use cases presented by AI experts and data scientists from the Banking, Financial Services, and Insurance sectors.STAC Summit, London
STAC Summit - London Come visit us at STAC Summit London on April 29th! Pure Storage will be sponsoring and presenting so join our session or stop by our table. STAC Summits bring together CTOs and other industry leaders responsible for solution architecture, infrastructure engineering, application development, machine learning/deep learning engineering, data engineering, and operational intelligence to discuss important technical challenges in trading and investment. Topics tend to cluster in four areas: Quant technology. Architectures for big data and big compute workloads such as model training, strategy research & backtesting, tick analytics, alt data processing, market and credit risk, portfolio optimization, fraud detection, and compliance. Low-latency infrastructure. Architectures for fast decision making and trade execution, primarily in automated trading. Networks, FPGA, servers, software, and other technologies for market data, trading and matching algorithms, execution, and trade-time risk. Command and control. Monitoring of trade flows, time synchronization, and orchestration and management of on-prem and cloud-based infrastructure. AI/ML. Architectures and infrastructure for models and data exploration, training, and inference with deep neural networks (especially LLMs) and statistical machine learning on-prem and in the cloud. While applied AI may be part of quant technology and low-latency topics, there will be a separate, dedicated AI Track at the London STAC Summit that focuses on the AI infrastructure needs of finance, from banking and insurance to trading and investment —from the model to the metal™.
