Leaders are taking a closer look at bank stress testing in the wake of recent bank failures. The significant impact of these collapses on the financial system, along with the government's extensive measures to prevent additional bank failures, is increasing the sense of urgency around enhanced regulatory supervision.
DBS Bank Head of Automation, Infrastructure for DBS Big Data, AI and Analytics Luis Carlos Cruz Huertas has a 1-on-1 discussion with Unravel CEO and Co-founder Kunal Agarwal about the convergence of DataOps and FinOps. The discussion, Leading Cultural Change for Data Efficiency, Agility, and Cost Optimization, was held at a recent Untap event in New York and revolves around best practices, lessons learned, and insights on.
Once upon a time, in a world of traditional banking, a young entrepreneur named Richa had an innovative idea for a new financial service offering. However, she realized that her idea was only possible if she could access financial data from various banks in real time. Frustrated by the slow and cumbersome process of obtaining this data, Richa began to explore the potential of open banking.
I’m a firm believer that banks rarely invest to drive revenue and elevate customer service. But I recently hosted a roundtable discussion in London with Appian, a process automation platform company, where leaders from mainstream and challenger banks in the UK gathered to discuss the challenges facing financial institutions when adopting new technology.
The banking and financial services industry is evolving rapidly with the advent of new technologies and digital platforms. To stay competitive, banks need to focus on providing superior customer experience to their institutional and retail customers. This should start with the initial Know Your Customer (KYC) process and continue through the entire customer lifecycle. Here are five keys to transforming practices for heightened customer experience in banking and finance.
Most organizations spend at least 37% (sometimes over 50%) more than they need to on their cloud data workloads. A lot of costs are incurred down at the individual job level, and this is usually where there’s the biggest chunk of overspending. Two of the biggest culprits are oversized resources and inefficient code. But for an organization running 10,000s or 100,000s of jobs, finding and fixing bad code or right-sizing resources is shoveling sand against the tide.
The software landscape at a modern financial services company is like a jigsaw puzzle, with many pieces that must fit together. For example: Software development can be more difficult in an environment that requires complex enterprise integrations. How do you create flexible, modern, and scalable applications that require technology integrations and data from dozens of sources?
IT and data executives find themselves in a quandary about deciding how to wrangle an exponentially increasing volume of data to support their business requirements – without breaking an increasingly finite IT budget. Like an overeager diner at a buffet who’s already loaded their plate with the cheap carbs of potatoes and noodles before they reach the protein-packed entrees, they need to survey all of the data options on the menu before formulating their plans for this trip.
