The Power of Self-Service Data Analytics in Financial Services
Banks and credit unions must move beyond using customer data for development of great reports, to the use of data for great customer experiences. Providing departmental access to data allows for better insights, faster processing and improved targeted activities.
Financial businesses collect a vast amount of data and are, understandably, incredibly protective of its integrity and security. Because of this, data usage is generally tightly restricted to the department for which it is collected, and sharing across the larger organization is historically limited and painstakingly slow.
Banks and other financial institutions are further held back by the complexity of legacy IT infrastructures, often comprised of a series of incompatible systems siloed by lines-of-business or product, making it extremely difficult and time-consuming to extract data and, more importantly, glean insights. But to remain competitive in a customer-centric landscape, marketers at banks and credit unions must develop strategies to harness their data in a smart, secure way.
According to a report from the IBM Institute for Business Value, Analytics: The Real-World Use of Big Data in Financial Services, 26% of banking and financial markets have not begun big data activities. Of those using big data, only 55% are focusing their activities on customer-centric outcomes. To build loyalty, confidence and excellent customer care, banks and financial institutions must recognize the changing habits and preferences of the banking population and adjust their product and service mix to meet consumers’ needs.
So how can marketers within the financial sector create these valuable customer experiences? The answer lies in self-service data analytics, and it requires a revolution in the way banks and financial institutions use their data to inform decision making.
Banks and credit unions of all sizes realize the tremendous potential for data, but many struggle with turning that data into something they can take action upon, quickly enough for it to make a difference. Legacy approaches and tools for analytics have simply slowed organizations down even more.
In the Harvard Business Review white paper, The Untapped Power of Self-Service Data Analytics, it was found that 62% of organizations require others within their firm to perform some steps in the analytics process, resulting in 69% not being satisfied with the quality of the output and 81% not being satisfied with the speed of the output. With line-of-business departments such as sales, marketing, and finance exhausting point solutions, they have grown tired of having to depend on data scientists and specialized staff for data prep, blending, analytics, and sharing of insights.
Self-service analytical tools provide departmental-level analysts with the unique ability to easily prep, blend and analyze all of their data using a repeatable workflow, then deploying and sharing analytics at scale for deeper insights in hours, not weeks. Empowering departments like marketing with data analytics, without writing any code, will help them gain a complete picture of all customer interactions and enable them to target and retain customers with total accuracy.
