Automation, Fintech

Technologies of the modern digital age are swiftly transforming the banking experience. Features like digital banking, open banking business models along with a shift towards mobile-first financial services are an avenue of opportunities for the banks. This is an upgrade for banks who invested in following the restrictive LEGACY infrastructure when exploring and adopting new technologies. These investments include upgrading credit systems to approve loans more swiftly, making systems compatible with application programming interface (API) and open banking regimes, or finding ways to integrate more robust data analytics. While good, these incremental changes are unlikely to give traditional institutions the competitive edge they need to stave off new competitors.

Now the banking sector is using data, influencing customer’s trust, and using technology to attract customers online and upskill its experienced staff. Two technologies are having the most significant impact on banking organizations across the globe. These are automation and predictive analytics. Although either of the technologies seems easily adoptable due past reputation of script-based robotic process automation (RPA) and cloud-based SaaS applications to allay the process in manufacturing industries, things are not the same for banking scenario. For this legacy infrastructure composed of fragmented systems has to share data and support a smarter.

In a set of whitepapers by KPMG, The Future is Open: Reshaping the Banking Experience, the consulting firm speaks about how using automation and predictive analysis together can revive the customer experience (CX) model. Banks now are open to experimenting with these technologies to help their human employees become more strategic and provide a customer-centric experience. KPMG explains that need to strike a balance when approaching automation, especially in terms of Robo advisors, chatbots and automated customer services models. The first-mover banks and fintechsdiscovered that a ‘pure’ digital-advisory model wasn’t feasible. Further, margins were too low, customer acquisition costs were too high, and onlya few customers (particularly high-net-worth ones) were willing to engage with a bot.

Therefore, currently, with simple technologies at their dispose, banks are using digital dashboards to help customers and staff to find the ‘next best offer’ on digital platforms and in the branch. This allows banks toget more out of the relationship with customers quickly and also presents them an opportunity to test their predictive models built on customer data and behavioral segmentation. For example, banks are employing a more specified and personalized approach to sell their innovations and schemes that align with customer requirements. With predictive analysis at play, the above solution can see even better results. Thanks to sophisticated engines, the banks will focus ‘next critical need’ of their customers instead of highlighting their ‘next best offer’.

Apart from products, predictive analytics and automation are combined to deliver personal financial management tools intendedto help customers make better financial decisions. As per data based on a user’s stated financial goals and ambitions, and by leveraging APIs and visualizations, these tools are empowering customers forecast, understand and respond more effectivelytothe solutions streamlined as per their future financial needs.

Besides the delivery of customer insights, other applications for predictive tools, include, automating the prediction of ATM downtime, branch utilization models and operational performance.

The KPMG report also describes key areas where bank executives should aim at, to shift organization move towards more predictive models. First is by managing data to incorporate external data sources to achieve a more holistic view of their customers. Then by concentrating on connecting the ‘back end’ data and automation to the ‘front end’ human interaction to ensure excellent customer experience (CX)yielding positive results, both for the business and for its customers.Next ismaking sure that the bank employees are not resistant to automation adoption by building awareness of the value brought by the technology. Lastly, meticulously crafting data and technology ecosystem for maximized gains and maintain flexible market position.

Banks that recognize the profound shift required and act now to transform their organizations to keep pace will emerge more competitive and successful than ever. With only 12 percent fintechs in the mature stage of their digital transformation, there are plenty of opportunities to grab the market and improve customer experience (CX).