The banking industry has grown increasingly competitive as institutions work to meet the demands of modern customers. Today’s banking customers are highly sophisticated, looking for fast and personalized experiences wherever they are. Rising expectations combined with the development of disruptive technologies like Fintech and blockchain are urging traditional institutions to rethink how they operate.
Hear from two experts in the financial services industry, Jennifer Smith, global marketing lead at HPE, and Kevin Levitt, global business development lead at NVIDIA, as they discuss these trends and how to address them.
Even with these advantages, managing a DevOps environment is a complex and compute-intensive task. Vast amounts of data produced by banks and banking customers have made it difficult for DevOps teams to effectively capture and apply information in real-time. Many teams lack the speed and flexibility to isolate critical insights from streams of data while grappling with unreliable access, which slows time-to-value.
Banks built on outdated technologies are struggling to keep pace with the data requirements of DevOps workloads. In order to succeed, banks must shift to next-generation solutions that can collect data from numerous sources and harness it for immediate intelligence, enabling teams to focus on increasing performance and fueling banking innovation.
Transforming banking with AI
The future of banking will be driven by artificial intelligence (AI). Today’s banks are exploring the capabilities of AI to become more effective and customer-centric by harnessing deep insights from their data.
AI technologies play a crucial role in how DevOps teams develop, deliver, and manage banking applications. With the help of AI, DevOps teams can test, code, and monitor software more efficiently to dramatically reduce development and operation cycles. AI can also expand automation, so teams can quickly identify and resolve issues to improve customer satisfaction and loyalty.
AI-enabled DevOps is pioneering a new era of banking, as AI capabilities merge with DevOps software to enhance functionality and accelerate data-driven results. These advancements are boosting performance in four main applications—fraud detection and identity verification, conversational AI and speech recognition, robotics process automation (RPA) for document processing, and recommendation engines.
Risk management is a top initiative which includes security, regulatory compliance, fraud, anti-money laundering (AML), and know your customer (KYC) guidelines. Fraud detection and identity verification are used to mitigate as well as help prevent cyberattacks and other criminal activity. Banks are now employing AI to augment DevOps and enhance security by recording threats and running machine learning-based anomaly detection. These applications execute real-time calculations of risk and fraudulent exposure to flag anomalies in milliseconds.
Conversational AI and automatic speech recognition are used to deliver better customer support experiences. Instead of taking notes and feeding information back into the system, banks can transcribe call center events in real-time. This enables teams to analyze video and audio content instantly to learn from every customer engagement.
AI provides the much-needed capability to streamline routine and repeatable tasks. Banks utilize AI-enabled RPA to extract meaning from documents, regardless of the language, layout, or document type. RPA is much more than simple document processing. It is an integral and sophisticated tool that allows banks to automate workflows to interpret documents and make data-driven decisions. This eliminates the time and costs of processing events manually and frees up teams to focus on business outcomes.
Recommendation engines are designed to further enhance customer experiences. Using AI and machine learning models, recommenders use information provided by customers to offer personalized suggestions. The models process troves of data to learn which profile features may be warning signs of risk. AI enables recommendation engines to process larger models and more data at once, for faster time-to-insight and efficient allocation of resources.
MLOps teams are leveraging AI to uncover game-changing insights in banking. However, many banks are unsure how to scale AI and unleash the full impact across their operations. To overcome this hurdle, banks must build an infrastructure that can support and facilitate a new breed of intelligent applications.
Introducing AI banking solutions
HPE and NVIDIA are collaborating to empower banking insight on demand from edge to cloud. The HPE AI platform features cutting-edge solutions that are designed to enable faster, smarter, safer banking.
NVIDIA-Certified HPE Apollo 6500 systems and HPE ProLiant DL380 servers built on industry-leading NVIDIA GPUs deliver unmatched power and speed for your banking applications. These robust systems are NVIDIA-Certified to ensure accelerated computing is simple to deploy and scale as your business grows. For even greater efficiency, we offer Cray ClusterStor E1000, a parallel HPC storage system that is purpose-built to deliver maximum throughput to your GPU nodes, making it easy for teams to manage AI workloads at scale.
HPE Apollo 6500 Gen10 and HPE ProLiant DL380 Gen10 powered by NVIDIA GPUs are validated to deliver top performance on AI software. This makes it simple to build and deploy intelligent applications to identify critical insights in vast amounts of data, calculate risk, and automate routine tasks—all at unprecedented speed and scale. Banks can configure DevOps and MLOps software to fit their specific requirements, so data scientists can focus on data science—such as orchestration, job scheduling, version control, and deployment. Supported by a robust ISV banking ecosystem, all software tested for integration and functionality with NVIDIA GPUs to create new efficiencies and achieve faster time-to-value.
Now, banks can choose to deploy these AI banking solutions on-premises—in conjunction with virtual desktop infrastructure (VDI)—or as a service. Beyond traditional financing and leasing, HPE Financial Services and HPE GreenLake give you flexibility in how you acquire and consume IT. HPE GreenLake offers AI as a service, a pay-per-use consumption model with the security and control of on-premises IT. HPE GreenLake for VDI expands these capabilities by making your applications and data accessible anywhere, on any device. VDI as a service (VDIaaS) is secure and scalable, making it simple for banks to buy and scale VDI without the need for costly upfront investments or continuous upgrades.
HPE Pointnext Services offer expert guidance to help you plan and implement your AI strategy. Pointnext specialists work with you to define your banking goals, MLOps requirements, and potential roadblocks and determine the best technologies and services to help you succeed in AI.
Entering the future of banking
HPE and NVIDIA can help you discover the benefits of AI-enabled banking applications. The HPE AI platform provides exceptional intelligence and performance with your choice of deployment model. Your ideal solution is expertly engineered to increase productivity, expand services, reduce risk, and dramatically improve customer services, all while driving down your TCO.
Wherever you are in the AI journey, these breakthrough solutions will enhance your banking operations from edge to core, so you can tackle today’s challenges and evolve for tomorrow’s requirements.
Let us help you achieve better banking outcomes on demand through the value of AI.
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