The Future of Finance Is AI
Massive datasets. Perpetual market fluctuations. Remote workforces. Intelligent technology can address critical challenges within the modern financial services industry. With AI—including deep learning, machine learning, and natural language processing—Institutions can boost risk management, improve data-backed decisions and security, and enhance customer experiences.
1.Building the AI-Powered Bank
Financial institutions are adopting AI to deliver smarter, securer services. GPU-powered AI solutions can centralize data to drive deeper, more holistic insights, offload routine tasks from employees with automation, accelerate risk calculations and fraud detection, and enhance customer service with conversational AI and more accurate recommender systems.
2.Accelerated Computing for Trading
Faster processing results in smarter trade strategies, more successful trade execution, and increased revenue. GPU-powered hardware acceleration decreases time to insight, allowing operations to remain competitive.
In STAC-A2, with OpenShift set new records for market risk calculations, including fastest calculation time, delivering over 3X the throughput of peer systems. With technology, financial institutions can harness the power of AI and high-performance computing (HPC) to learn from vast amounts of data and respond quickly to market fluctuations.
3.AI in Finance from Data Center to Cloud
Unprecedented Acceleration at Every Scale
In today's fast-paced markets, the ability to test and simulate model hypotheses with speed and accuracy can create revenue opportunities for financial institutions. The A100 Tensor Core GPU delivers acceleration at every scale for AI, data analytics, and HPC to tackle the toughest computing challenges in finance.
4.Powerful Computing for Data Centers
Financial services customers require AI infrastructure that improves upon traditional approaches, which involves slow architectures that siloed analytics, training, and inference workloads. This approach created complexity, drove up costs, constrained speed to scale, and wasn’t ready for modern AI.
From edge to data center, Tensor Core GPUs are available from every major computer system and server manufacturer to accelerate AI training. DGX™ A100 and DGX™ systems are equipped with the DGX software stack for rapid AI deployment.
5.Democratization—from Data Center to the Cloud
NVIDIA GPUs are available in all major cloud platforms worldwide. And NVIDIA’s software libraries and software development kits (SDKs) create a scalable solution that enables customers to deploy AI in the cloud, on their servers, or at the edge. These SDKs include NVIDIA® TensorRT™ for inference, TAO Toolkit for tuning deep neural networks (DNNs), and the NGC catalog for GPU-accelerated software containers. RAPIDS enables financial institutions to execute end-to-end data science and analytics pipelines on GPUs for better prediction accuracy. And with GPU-accelerated data science, organizations can run an exhaustive array of simulations, testing the robustness of their models and creating new financial opportunities
Transferring money to friends and family. Paying bills online. Using your phone to check out at the grocery store. Payments—online, mobile, in-store, business to consumer (B2C), and business to business (B2B)—power the global economy.
AI can help banking firms better detect and prevent payment fraud and improve processes for anti-money laundering (AML) and know-your-customer (KYC) systems. With GPU-accelerated machine learning and deep learning platforms, data scientists can deliver results in days, instead of the weeks more traditional methods require. Dmitriy Efimov, vice president for machine learning at American Express, attests, “For our production environment, speed is extremely important with decisions made in a matter of milliseconds, so the best solution to use are GPUs.”
AI in payments enables greater security and more transparency, creating a better experience for both firms and customers.
AI in Finance from Data Center to Cloud
1.Unprecedented Acceleration at Every Scale
In today's fast-paced markets, the ability to test and simulate model hypotheses with speed and accuracy can create revenue opportunities for financial institutions. The A100 Tensor Core GPU delivers acceleration at every scale for AI, data analytics, and HPC to
Firms are moving beyond traditional claims management by embracing digital opportunities and adopting a fully analytics-driven approach. This includes using AI to automate claims handling for simple and clean cases, implementing AI-powered services to fast-track complex cases, and creating new digital services to increase customer satisfaction.
Fintech is driving global innovation that is transforming how companies, consumers, and money interact across industries, from financial services to retail to transportation and beyond.
Utilizing AI, fintech interactions are more personalized with recommendation engines, self-service is improved via conversational AI, and transactions are more secure because of deep learning fraud detection models. And that’s just the beginning. ai server ai station nvidia dgx a100
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