In many ways, we’re in the golden age of data, where companies have more data across their organizations than ever before. Yet some firms are still in the dark. Their legacy systems have kept data inaccessible, inaccurate, and isolated.
To thrive in this data renaissance, financial services need to make a fundamental shift in how they extract value from data. Modern innovations are fueling this movement, enabling firms to uncover the game-changing insights they’ve longed for.
For some financial institutions, getting access to data may still feel like living in the dark ages. When it comes to gaining visibility across the business, financial services firms often have a lot of data to work with. But problems stem from the technology that many finserv companies continue to use—data warehouses—which are meant to store and organize the plethora of information drawn from operational and core processing systems.
As these firms know, creating a report or conducting a financial analysis requires extracting data from the data warehouse. Here’s the rub: the data in the data warehouse is only accurate at the time it was loaded and refreshed from legacy systems. Business intelligence tools access the data warehouse to create reports or perform financial analysis.
As a result, the data in the reports or analysis has a high likelihood of being out-of-date. This makes the insights from those reports unreliable.
Many financial services firms have turned to “bolted-on” custom software solutions as a way to make data extraction from their legacy systems as close to real-time as possible. But those workarounds only add more roadblocks. Custom solutions require continuous maintenance to keep up with the changing needs of the business. In other words, financial services firms end up running (and paying) just to keep up, at the expense of investing in better technology that leverages data for insights.
In the current landscape where changing business needs are a constant, nimble access to real-time data (and, more importantly, to the insights it can provide) is a must. Leaders should be focusing on understanding and applying the insights found in the data, not maintaining an aging system that treats data as a commodity stored for future use.
To thrive in this data renaissance, financial services need to make a fundamental shift in how they extract value from data.
Here are some of the key technologies that are making insights transparent and accessible across lines of business:
Cloud computing. A cloud platform enables companies to connect and scale their data capabilities and operating systems without the worry of physical limitations. And having systems on a single platform eliminates the reconciliation issues that occur when data and systems are on separate platforms.
Financial services firms are starting to take the leap into the cloud. Jerry Silva, research director for IDC Financial Insights, discusses this trend in a webinar about elevating the role of the back office in financial services firms. Silva explores the drivers behind the adoption of cloud in financial services and the cloud infrastructure—public, private, or hybrid—under consideration at financial institutions.
Open APIs. In financial services, open APIs (application programming interfaces) are often discussed in the context of open banking, where banks are opening up internal data to external applications. It’s how banks are evolving their services to meet customer demands. For example, open APIs enable an investing app to connect to a user’s bank account without compromising the security of the account holder’s financial institution.
Workday Cloud Platform leverages open APIs to help companies extend their Workday data ecosystem and drive additional value for the business with third-party applications. Erin Yang, vice president of platform technology product and strategy, highlights how Workday customers are using APIs on the Workday Cloud Platform to build applications and benefit from solutions created by other Workday customers and third parties. Among those examples include a financial services company, which built an application that allows employees to request tuition reimbursement for training courses prior to registering. As a result, the application did more than eliminate the need for the HR services team to manually update a tracking spreadsheet—it greatly improved the employee experience.
Artificial intelligence and machine learning. Simply put, artificial intelligence (AI) and a subset of AI, machine learning (ML) are game changers for analytics. These technologies modernize the way companies gain insights from data. AI and ML enhance the discovery of insights in data by quickly detecting patterns, identifying trends, and offering predictions. Sayan Chakraborty, executive vice president of technology at Workday, describes more ways ML has changed the way we work, including how it speeds up business processes.
For example, finance typically spends extended amounts of time reconciling the monthly close. But ML helps to reduce that review time. So, instead of combing through numerous accounts to find discrepancies, an ML-augmented financial management system can send alerts about anomalies in the general ledger.
In the current landscape where changing business needs are a constant, nimble access to real-time data (and, more importantly, to the insights it can provide) is a must.
The speed of making these discoveries accessible across the organization is how financial services firms can gain a competitive advantage—the faster the insights, the faster your organization is able to make an impact based on the data.
And ML isn’t just for financial management—automation and regulatory compliance are other ways financial services firms are leveraging AI and ML, says consulting firm Aberdeen Group in its “Financial Services: Making Informed Decisions with Improved Transparency” report.
The data renaissance has set the stage for further improvements. Powered by the cloud and newer technologies like AI and ML, the best business intelligence tools make data discovery widely accessible to anyone in the organization, even those who don’t have a formal data science background.
The traditional view of data, a resource that should be controlled and have limited accessibility, is no longer a fit for the changing world of business.
In other words, teams across the organization—from finance to HR and more—can own the end-to-end process of discovering trends and using those insights to make investments that drive the business forward. That’s the motivation behind Discovery Boards, a Workday capability that leverages advancements in data and analytics to quickly deliver insights with data visualizations. HR leaders in banking and insurance can leverage Discovery Boards to understand areas of the business that are growing and potential skills gaps, while financial planning and analysis (FP&A) or accounting teams can use the tool to uncover trends in revenue or expenses. And those are just a handful of ways businesses can leverage data to chart their own path in a changing world. Pete Schlampp, executive vice president of product development at Workday, shares more examples of applications of using Discovery Boards.
The traditional view of data, a resource that should be controlled and have limited accessibility, is no longer a fit for the changing world of business. Just like how the printing press accelerated the dissemination of knowledge, modern innovations have also furthered the power of data. The financial services industry is in the throes of this data renaissance, and the path to discovering game-changing insights is already laid out. It’s all just a matter of taking the first steps.