Robotic process automation (RPA) refers to the use of software robots, or "bots," that mimic human actions to automate repetitive tasks within business processes. RPA technology can interact with applications, systems, and data sources to automate procurement tasks such as data entry, document processing, and report generation.

Bank turmoil associated with recent bank failures has highlighted the importance of due diligence for managing financial risk, growing revenue, and retaining jittery customers. Regulators will likely ramp up their scrutiny–even after hitting financial institutions with a jaw-dropping $2.7 billion in fines in 2021 for failing to meet compliance and due diligence standards.

Your organization has an unstoppable digital transformation plan—at least that’s what you thought before you started encountering the disadvantages of data silos. Your teams were fired up and ready to go, but data separated by different systems created obstacle after obstacle to your digital transformation dreams.

The insurance industry is quickly moving into a digital-first future where emerging technologies will reshape the way policies are sold, claims are processed, and risks are managed, and where market leaders are automating critical workflows to deliver seamless experiences, enhance customer satisfaction, and unlock profitability.

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.

Large-scale enterprise modernization initiatives are taking place across the public sector, with agencies striving to gain efficiencies through better use of more modern technologies, such as low-code platforms, and employing data in novel ways in the decision-making process. These modernization efforts disrupt the business processes that have developed around the outdated solutions these efforts aim to replace.

Any organisation wanting to pursue digital transformation understands the value of good-quality data. Data is akin to digital gold, and it is immensely important to strategic decision-making. Ensuring that your data or BI team has everything they need is part of the challenge.

Process efficiency might not be flashy, but its impact is substantial. Improving process efficiency—from developing new applications faster to automating manual tasks—can amount to millions in savings. According to a Total Economic Impact™ (TEI) study, conducted by Forrester Consulting and commissioned by Appian, a composite organization comprised of interviewees with experience using Appian realized: How exactly are customers realizing these benefits?

Business Intelligence (BI) teams often face several resource constraints that can impact their ability to deliver their objectives effectively. They must run effective operations with limited time, resources, budget and people. The role can be incredibly challenging when multiple projects are highly prioritised, where data and reports were required yesterday. That said, there are ways to make these challenges more manageable.

Data is the invaluable currency of the digital age, holding immense importance in driving critical business decisions and guiding organizations towards success. Yet far too many neglect the mechanisms that manage our data. Data integration is one of the most important parts of digital transformation.