Using Data to Elevate Employee and Customer Experience in Financial Services

If departmental silos constrict access to data and capabilities, financial institutions will not be able to achieve seamless omnichannel service. Across the organization, there must be a dedication to breaking down the silos that traditionally exist between business and IT, and a commitment to adopting a culture of innovation and thinking from the “outside-in” about the customer journey.

A clear vision based on research, patience and careful collaboration will promote innovation and new products designed to serve customers. The functional teams will be free to explore offerings in newer technologies like open APIs and Open Banking to increase financial transparency and widen the scope of applications and services that a financial institution can bring to its customers. For example, a culture of collaboration will allow teams to thoughtfully incorporate artificial intelligence and machine learning (AI / ML) for fraud detection, risk management, trading, lending, investment advice and other services — while carefully considering philosophical questions concerning whether a machine could ever simulate human intelligence and what the ethics of doing that would be.

Technical Debt

Technical debt reflects the cost of additional rework caused by choosing an easy solution over the right solution. It also reflects the lost opportunity cost that a financial institution incurs either by not developing a requisite application to take advantage of a market opportunity, or by creating an application that does not meet business requirements. The negative impact of technical debt is higher operating expenses, development delays, and reduced performance. To combat this, financial institutions need to look for new ways to accelerate application development using enterprise low-code development platforms that speed up the build process with robust but easy-to-use drag-and-drop visual design tools. With these platforms, employees will be able to spend less time maintaining legacy systems, and more time on creating innovative new tools to improve the customer experience.

Intelligent Automation

Intelligent automation combines the speed and power of business process management, machine learning, and robotic process automation with low-code development, and can improve the high volume and rules-based back-office functions. These functions require a lot of human support, and since they are not typically revenue-generation area shaving little direct interaction with customers, they are a prime candidate for intelligent automation.

There are also significant efficiencies to be gained in front-office processes around client on-boarding, transaction monitoring, fraud prevention and the contact center. Natural language processing (NLP) and sentiment analysis can add tremendous value to a financial institution’s contact center. The immediacy of the data available is much more actionable than what you could obtain from post-call surveys. The technology can help determine the future action of customers, and can be matched with purchase or churn data for continuous feedback into the overall health of the business. Successful financial institutions are realizing significant business benefits from a low-code platform strategy that includes intelligent automation for more efficiency, fewer errors, improved regulatory compliance, and increased customer satisfaction.