If you're worried about the potential for heightened regulatory scrutiny in financial services, you're not alone. Business operations teams everywhere are focused on the end-to-end, client lifecycle management (CLM) process as they cope with ever-changing regulations governing how, when, and where client data can be stored and accessed. It's hard to stay compliant when customer data is spread across multiple operational silos.

The process of preparing and submitting labeling to regulatory authorities can be time-consuming and complex, requiring specialists’ input and careful coordination across organizations and functions to ensure the quality and safety of products going to market. This often causes delays that ripple across the supply chain, impacting profitability and patient care.

Organizations must constantly seek ways to improve their operations and drive efficiency. Two concepts gaining traction in this quest are process intelligence and process mining. While these terms may sound similar, they serve distinct purposes and can provide different insights into your processes. Understanding the differences between them is crucial for organizations aiming to enhance productivity and streamline workflows.

In the insurance industry, the claims process can often feel like a complex maze of manual processes for both customers and agents. However, new and advanced technologies are paving the way for smoother, more efficient claims handling. Claims processing automation at insurance companies can streamline routine tasks, reduce risk of errors, and enhance customer satisfaction. In this blog, we’ll explore three key areas to focus on for effective automation.

ERP systems are critical in government agency operations for integrating internal and external management information. They are intended to optimize processes, improve collaboration, and connect with customers, vendors, and partners. Government ERP systems typically include modules related to financial management, human resources, sales, procurement, inventory, and operations like contract and project management.

When AI first started to gain widespread adoption, it sparked a wave of fear. While much of that fear was overblown, we still need to remain cautious about any new technological innovation. Given AI’s potential to drive change on a massive scale, applying ethical principles to AI is not just important, but urgent. Every company must prioritize responsible AI—not only as an ethical responsibility but as a practical, strategic choice.

Many vendors have started calling their platforms “low-code” or “no-code.” Competitors often pit the terms against each other. But what do low-code and no-code really mean? And what's the difference between the two? Both platforms offer improvements over traditional high-code approaches. The biggest differences are the target user groups.

Banking automation has become a key driver of efficiency and innovation in the financial services industry. As the banking sector strives to meet the demands of customers while managing costs, they’re turning to technology to streamline operations. But what exactly is banking automation, and how does it work? Let’s break it down. Banking automation refers to the use of technology by financial institutions to perform tasks that would traditionally require human intervention.

Companies use a wide range of both artificial intelligence (AI) and automation tools, and each automation tool serves a different purpose, often working together to boost efficiency. In this blog, we’ll explore the differences between AI and automation, how they can complement each other through intelligent automation, and five real-world examples of how they work together. We’ll also highlight the benefits of using AI in business process automation.

Enterprises have complex IT and technology needs. To reach business goals, organizations must often stitch together a patchwork of software and IT systems. So, it’s understandable that the thought of adding yet another technology—low-code—might cause trepidation. But low-code excels at integrating seamlessly with any technology. Low-code tools speed up development work and enable rapid application development.