We are living in the world of automation and every industry, particularly the financial services industry needs to brace up with the challenges of labor shortages, profit generation, legal compliances, and customer satisfaction. Now, the sole objective of the financial services industry is to optimize efficiency and minimize costs – these have become mandatory attributes for any financial or banking industry to thrive in the current competitive world.
In the above context, Robotic Process Automation (RPA) has redefined how the time-consuming, tedious processes can be executed to improve the competitiveness of an industry. Though RPA has become a great savor for labor-intensive industries, however certain new generation automation solutions are generating greater benefits than expected.
Before the advent of automation, projects that involved customer onboarding, reporting, loan processing, account openings, and other Know Your Customer (KYC) tasks were cumbersome, error-prone, and time-consuming. Added to that, the compliance processes have become more stringent after 9/11, bringing in a new set of challenges. With RPA adoption, banks could easily automate all such tasks – direct such tasks to virtual assistants/workforce that could process these tasks quickly and with greater precision, without getting fatigued. This in turn had led to a high level of worker motivation, apart from cutting costs and improving the efficiency of the financial services.
McKinsey's survey found that RPAs can completely automate about 42% of financial activities, apart from automating another additional 19% of tasks. Currently, most of the companies in this segment are automating almost half of their business workflows, leading to higher-order efficiency with considerable savings in their time and resources.
RPA is no longer a game-changer
Though RPA is perceived as the most promising automation technology, unfortunately, it suffers from a few shortcomings. This implies cumbersome manual work, especially in the area of document processing. Though RPA can automate processes related to approvals and routing, however, a lot of manual work related to initial capture and data extraction has to be still accomplished manually, which means a worker had to get the right data format for RPA to process the required task. This again puts a lot of pressure on an organization and can even demotivate workers from completing vital, revenue generation tasks. This is particularly evident in projects involving customer support, email responses, and application approvals, impacting customer satisfaction.
Role of intelligence process automation to plug the loopholes
Intelligent process automation goes to the next level of integrating other technologies such as Machine Learning, Natural Language Processing (NLP), and AI. These technologies in combination with RPA can work wonders in the financial services industry and can process a wide variety of tasks that can seldom be accomplished by a stand-alone RPA. One of the technologies that are becoming more widespread is intelligent document processing (IDP) which could automate the input tasks. An IDP platform uses optical character recognition (OCR) to read virtually any kind of document (even images), retrieve data, and format it for processing by users or RPA agents.
An IDP platform can immensely benefit the financial industry since it can retrieve data virtually from any kind of document – PDFs, emails, Word, Excel or PPTs, digital forms, and more. Some of the advantages of using such a platform are outlined below:
- Categorize documents automatically with intelligent character recognition.
- Authorize transactions with a higher level of precision by eliminating manual processing
- Probe the intent of emails to quickly route customer requests and extract the relevant data
- Explore cross-selling and upselling opportunities for products such as mortgages and home insurance.
An intelligent solution should not only provide IDP functionalities but also serve as a comprehensive end-to-end solution that can probe into the data that it retrieves from documents to perform enhanced processing and routing. An intelligent solution’s advanced and deep learning AI can also provide additional functionalities to complete the entire document life cycle, apart from self-learning to enhance its capabilities over some time.
And the most important aspect is an intelligent solution should not disrupt an organization’s existing infrastructure or systems. It should complement and enhance the capabilities of the existing systems by seamlessly integrating with various systems including an RPA solution. This way, an organization should be able to derive the complete benefits of a full-fledged enterprise AI system with superior capabilities than any other stand-alone solution.
Though automating tasks in the financial and banking industry can be challenging, considering a complex web of compliance procedures, however, an enterprise AI system should seamlessly work and fulfill the obligations of the industry to ensure a seamless process journey, where employees and customers alike generate the best business outcomes.
To know more about this technology or to schedule a call with us to kickstart your process evaluation and RPA implementation, please get in touch with us today.