Editor’s Note: The following is second in a series of blogs excerpted from a report published by Celent entitled Defining A Digital Financial Institution by Daniel Latimore and Zilvinas Bareisis . D3 Banking has licensed the content used for general distribution. For the full report contact Celent. The previous installment in this series dealt with the the need for financial institutions to provide customers with a personalized, consistent user experience across all digital channels.
Delivering a customized but consistent FI brand experience to customers across all channels and points of interaction, especially in real time, would be impossible without analytics and automation — two capabilities that represent the next layer of our framework.
Big data, data analytics, or simply analytics — there are many names for this capability, and much has been written and said about it, both by Celent and by others in the industry. Rather than replicating those insights here, we just want to highlight what analytics means to us in the context of digital. We argue that analytics play a crucial role in optimizing the delivery of a bank brand experience in real time for each customer based on a wide variety of data from different sources.
The Meaning of Analytics in Digital
Banks have always had a wealth of internal data about their customers — product relationships, transaction data, service interactions, and so on. However, historically they have not been very good at using that data. It is typically in silos, updated in batches, and often just poor quality. In recent years, the amount of data that banks can and do capture about their customers has proliferated; some financial institutions now seek to track data at the “atomic” level, i.e. click-by-click customer interactions to understand and optimize how customers engage with them.
Furthermore, most banks have always relied on external data, such as data from credit bureaus. Now, customers are also leaving a huge digital footprint via their connected devices on search engines, social platforms, and merchant sites. Some of this data, used appropriately, can be very interesting and valuable to banks. Finally, as the Internet of Things (IoT) continues to grow with more devices going online, financial institutions will have to decide if and how they can make use of that data. The use of IoT in banking to date has been limited mostly to device (e.g., ATM) monitoring and management. IoT and data from sensors hold a particularly great promise for the insurance industry.
Like analytics, automation is a not a new concept for banks. FIs have sought to automate tasks since computers were invented. However, in the past the focus of automation has been mostly on back office tasks and straight-through processing (STP) to reduce costs. While this remains important and many banks still have work to do to achieve their STP objectives, the focus of automation is shifting from back office to front office and customer engagement, and from mundane to sophisticated.
The Meaning of Automation in Digital
Workflow and business process management tools now not only orchestrate processes internally within the bank, but also trigger interactions with customers. Similarly, banks go beyond electronic statements when trying to get rid of paper and digitize documents. They invite customers to complete application forms electronically and utilize imaging and document uploading technologies to capture and store digital documents instead of paper.
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