Banking and finance are core business processes, supplying the lifeblood for economic activities to thrive and deliver. It has propelled the emergence of financial institutions to meet the demands acting as a fiduciary between a beneficiary and the trustee for providing such services necessary for smoother business operation.
Nevertheless, in the new economic context, which is underscored by the imperative to do more with less, financial institutions worldwide are under incredible pressure to reduce operating costs, eliminate redundancies, counter manual errors, and address repetitive tasks loads with increased efficiency. Interestingly, much of the inflated cost, security lapses, and associated predicaments can be ascribed to an outsized dependency on manual interventions. In fact, in its research, the Journal of Accountancy found that 87% of the finance professionals work overtime during the financial closure process.
In response, Robotic Process Automation adopts a strategic approach, replacing human bandwidth with machine-driven interventions, elevating the speed, precision, and quality of the outcomes. CFO in this article estimated that at least 70% of workloads across the finance sector offer scope for automation, and Gartner, in one of its recent studies, revealed that an RPA bot could effectively replace up to 30X the work of a human FTE.
Unsurprisingly, the global financial leaders and process owners are in a race to embrace automation, with 80% of the institutions in various journey stages. However, what exactly has been the motive behind this digitally enabled shift where 97% of the CFOs anticipate major transformations as early as the closing of 2021? Let us look at some of the persistent pain points that have been undermining finance and banking operations for decades.
What are some common industry pain points?
Resistance to change: The finance and banking sector is highly volatile to the ebbs and flows of global events. Factors like a global pandemic or a geopolitical crisis are bound to impact the key policy rates, setting the imperative for the organizations to alter the course of operations. However, institutions with hardwired, manually driven processes respond slowly to a stimulus. The failure to realize change with agility often makes these institutions lose valuable business opportunities.
Suboptimal compliance: It is by far one of the most formidable challenges and one of the most pressing concerns for the banking and finance industry globally. For institutions operating across jurisdictions, incorporating flawless compliance like anti-money laundering (AML) guidelines into operations is cardinal to business success, escalating the complexities of their processes. The divergence in regulation across geographies compels financial businesses to rely on human expertise, resulting in cost pressure heavily. Further, penalties due to poor compliance account for more than 10% of the operating cost.
Poor Data protection: With the ever-growing hawkish posture of the legislators on personal data protection, it is increasingly becoming a challenge for financial businesses to micromanage the vast plethora of factors associated with the integrity and privacy of personal data. Manually driving data protection regimes is labor-intensive and incoherent and leaves much room for exceptions, exposing the businesses to disruptions.
Lack of system integration: CRM and ERP stacks play a significant role in enabling the banking and financial sector outcomes, tying processes with the underlying business logic, and streamlining value delivery. Nevertheless, breaking silos by integrating systems and ensuring a free flow of information across the enterprise environment to elevate the functional experience and improve customer reach is a challenge in itself. A fragmented system landscape leaves a business heavily dependent upon unreliable reporting, allowing a considerable chance of erroneous processing and inflating OpEx.
Why is RPA important?
Despite the best intentions, in the new market economy, the growing volume and complexity of tasks, compounded by stringent regulatory standards, fast product evolutions, and intense competition, may put significant drags on the operational outcomes of the financial institutions. Such shortcomings often adversely impact one of the key performance metrics for financial and banking businesses: Customer Experience. While adding more and more human operators into the workforce to tackle these problems pushes up the OpEx and definitely runs contrary to the vision of non-linear growth for a lean and agile institution, process automation holds many promises to improve service delivery dramatically.
In fact, Mckinsey, in its research, found that RPA can “fully automate” 42% and “mostly automate” a further 19% of finance activities, accelerating over half of the current workloads in areas like account, loans, and fraud inquiries. Alongside improving the turnaround time for routine tasks, it also frees up customer service teams to spend more time on strategic roles like relationship building and advanced query solving, radically improving the overall service experience for the customers.
RPA’s proven operational benefits and relevance in elevating service delivery in the post-pandemic era make its industry prospects seem pretty bright. Business Insider’s Insider Intelligence’s “AI in Banking” report predicts that financial institutions’ implementation of intelligent automation could account for $416 billion of the total potential AI-enabled cost cuts across sectors and is slated to reach $447 billion by as early as 2030. Considering RPA as a meaningful investment for banks and financial businesses, Gartner expects the global RPA market to experience strong growth through 2024. Such an overly optimistic outlook is understandable given the diverse use cases that RPA can drive and the benefits they can derive for the finance and banking industry players.
What are the benefits of RPA?
Reduced time to insights: Institutions like investment banks, clearinghouses, and other financial businesses need access to actionable insights to be effective and profitable in the long term. With organizations perching on massive volumes of data today, there is a pressing need to extract insights through the analysis of Big Data. It helps the organizations to get the larger picture by connecting the dots and meeting the business requirements in real-time. However, manually doing this may call for never-ending paperwork, leaving much room for error and inconsistencies. Backoffice processes involve plenty of repetitive tasks that can be outrageously time-consuming and daunting. Instead, RPA bots can be deployed to automate such repetitive tasks and consistently deliver decision-ready data points for the management.
Reduced cost pressure: In the highly regulated financial sector, automation can accelerate repetitive tasks and attain up to 50% cost savings. Further complementing manual operators with RPA brings in speed, accuracy, consistency, and efficiency as additional benefits. Also, RPA implementation does not call for a significant revamp of the IT infrastructure due to its UI automation capabilities. In the case of cloud-based RPA constructs, the hardware and maintenance cost further go down. The savings improves the bottom-line performance for organizations and leaves much more leg-space to invest in digital transformation. However, far from being a tool for cost-cutting, RPA is a means to help employees function better and create value for the customers.
Scale to relevance: Modern financial institutions should perform at the speed of business and be able to scale as per the market demands. RPA solutions, unlike human workforces, are highly agile and can be easily scaled to manage high volumes during peak business hours or collapse during lean periods. Also, as low-code platforms, they can be used to drive service innovation and delivery at scale.
Impeccable compliance: Compliance with sectoral regulations like KYC norms, AML guidelines, data privacy standards, and audit management must be the top priority for financial and banking institutions. However, the need to stay constantly updated with the evolving legislation poses formidable challenges for institutions that believe in operating the old ways. In respite, RPA simplifies the process by generating and maintaining detailed logs for all transactions, making it easy to track and audit the business outcomes. Thus, with automation, businesses can be well equipped to handle even the stringent compliance requirements.
Faster implementation: RPA tools are primarily optimized for consumption by a non-technical user base, providing a simple drag and drop environment to automate day-to-day banking functions. With low code RPA platforms available today, it is easy to implement and maintain automated workflows with minimum or no coding experience.
Data monetization: RPA allows banks and financial institutions to integrate their legacy and new databases, allowing optimum dividends from their data assets. Establishing a single source of truth allows businesses to implement innovative solutions on top of them and extract multidimensional insights to fuel business growth.
RPA Adoption by Process
Automated reporting: According to the latest RBI insights, the private banks in India reported a rise of 21% year-on-year in banking frauds. Understandably the generation of compliance reports for frauds and Suspicious Activity Reports (SAR) is a crucial requirement for financial institutions. However, enforcing SAR requirements by conventional means is a highly repetitive task involving a lot of time and effort, with the compliance officers logging in all the information manually.
In respite, RPA embedded with Natural Language Processing (NLP) capabilities can run through the lengthy reports and populate the SAR forms with the required information. Further, the algorithms can be trained accordingly by the compliance teams for specific roles. Not only does it save significant operational cost but also improves the turnaround time for various compliance functions.
Rapid customer onboarding: Customer onboarding is mostly a significant grey area for institutions operating the conventional ways, mainly due to the detailed documentation requiring manual verification. Using optical character recognition technique (OCR), RPA can accelerate capturing and loading the information from the KYC documents directly into the enterprise systems, making them readily available for scrutiny by the onboarding teams. Once cleared, the information is automatically transmitted into the customer relationship management portal, commencing business as usual. The RPA-driven approach eliminates the chance for manual errors, saving a lot of repetitive tasks by the employees and mitigating reputational risks for businesses.
Account opening: Customer account orchestration is a complex process that can otherwise be simplified through RPA implementation. Automation can intuitively eliminate the data transcription errors between the Core Banking System and the New Account Opening proposals from the customers, improving data integrity. Here software robots can extract data from the forms and feed them directly into the various host applications, eliminating the chances for data discrepancies. The approach reduces the turnaround time of requests while ensuring rationalized operational costs and maximum accuracy.
Mortgage lending: Lending operations are a crucial income center for financial institutions. Nevertheless, mortgage lending is a highly time-consuming process that can be streamlined through RPA interventions, performing operations as per the clearly defined guidelines. RPA can expedite crucial mortgage requirements, including loan initiation, document processing, financial comparisons, and quality control, enriching customer experience.
Customer service: At present, the customer servicing teams of the financial institutions are under enormous pressure. The massive volume of queries directed to CS teams, ranging from balance inquiry to general account information, often makes it difficult for them to cope up effectively, affecting user experience in the process. RPA helps the banks and financial institutions to automate rule-based processes allowing teams to resolve queries with velocity while maintaining uniform service standards.
Credit card processing: The management of credit card applications is another labor-intensive operation for banks, consuming several days for verifying customer details before the request can be granted. RPA solutions integrated with internal and external databases across the financial and regulatory ecosystems can intuitively pull customer data into a single source of truth and take action on credit card requests using rule-based approaches.
How can Percipere bring in the value?
Undeniably, robotic process automation is an exceptionally agile and adaptive technology that can deliver much value for banking and financial institutions in the present competitive climate. However, since the use cases, business realities, and technology context varies significantly between organizations, embracing RPA with relevance requires the assistance of a subject matter expert and an experienced process integrator. It should be able to scope the business requirements, validate the opportunities, estimate the baseline operating costs to ensure affordability, standardize the workflow and procedure, implement, and deliver hyper care as required.
To ensure this, we at Percipere have partnered with UiPath, a global leader in RPA platforms, to deliver on the exceptional promise of banking and financial services automation. We are a full-cycle RPA innovator, trusted industry-wide for infusing efficiency, speed, and precision into legacy banking technology landscapes with minimum intrusion. As an end-to-end RPA innovator, Percipere’s interventions range from Advisory, Consulting, Implementation to Incident Response, backed by well-laid plans and an efficient change management culture to help you unlock productivity with your banking and financial services automation investments.
Author: Akshay Farde, Lead Manager (RPA)