RPA in the finance sector

Advantages of deploying RPA in the banking sector

Today’s economy requires speed and efficiency which is hardly possible without extensive automation. RPA offers several benefits to the banking industry, not the least of which is the reduction in human error, and increase in productivity and efficiency. Initially, RPA was used to automate intensive processes such as accounts payable and receivables, account closure, report automation, deposits, etc. When combined with AI and ML, RPA can extend to a wide range of applications in banking. This type of intelligent automation is expected to do away with more than 40 per cent of service desk operations by 2025.

With RPA, banks can scale up operations and manage an increase in requests during peak hours. Bots can work tirelessly to satisfy customer queries and requests. RPA software can connect with backend systems and front-end applications, and sits as an additional layer in the stack, without causing any major upheaval in the infrastructure. Full-time employees can focus on more productive tasks that cannot be done by machines. This results in increased staff engagement and improves resource utilisation. Due to the reduction of manual processes, there is increased productivity, reduced errors, and improved regulatory compliance. With intelligent automation, banks can provide personalised services and predict customer demands, thereby improving customer service and satisfaction. Customers have a consistent experience with lower turnaround times. Chatbots provide customer service and are available round the clock. Common queries can be handled by the bots, allowing staff to focus on more complicated issues.

Applying complicated rules, and improving the speed of operations, and quality are just some of the benefits. RPA also results in huge cost savings for banks. According to an estimate, a bot can cost one-tenth of a full-time employee in the USA, UK and Australia, and one-third of a full-time employee in India. Intelligent automation can also be used for complicated tasks such as budgeting and forecasting. A well-thought-out cognitive automation strategy is the way forward for banks to stay competitive against new emerging fintech.

How banks can leverage RPA

With high transaction volumes and repetitive activities, the banking sector becomes an ideal ground to implement RPA and intelligent automation extensively.

For instance, Accounts Payable processes can be automated with intelligent automation and Optical Character Reading (OCR) technology to read invoices, and validate data and credit amounts automatically. RPA software can be used for credit card processing to validate documents, customer credit history and applications to check eligibility. It can also be used to give the green signal to issue cards. Loan processing can be speeded up with intelligent automation which can validate loan documents, perform credit checks, verify employment status, check rules and regulations and disburse loans.

Banks need to adhere to several regulatory and compliance requirements for various purposes right from validating customers to reporting. Banks can employ RPA for Know Your Customer (KYC) validations, saving precious employee time and effort. By deploying RPA, customer information can be collected, screened and validated accurately and at lightning speed. Gathering data for internal and external reporting, onboarding customers, and account closures can be automated using RPA.

Intelligent bots can act as watchdogs by automatically detecting any potentially fraudulent transactions. Suspicious activity can automatically block account access, reducing any potential liabilities for the bank.

Cognitive Automation will lead the way forward

A scramble to simply automate routine transactions may not result in effective transformation. Launching several bots will eventually result in scaling problems and redundant processes. Instead, banks need to arrive at a cognitive automation strategy that will increase productivity and efficiency, and enable new value-added products and services to grow the business.

Banks need to have both a short and long-term vision for automation, with clearly defined objectives. Identifying the processes that need to be automated, and checking to see which processes need to be outsourced to vendors will help streamline functioning and keep the organisation agile. With the growth of AI, ML, natural language and cloud technology, several cutting-edge solutions are possible. Often these solutions may require relooking at workflows and processes for optimum efficiency. Large-scale cognitive automation can bring in process efficiencies, while at the same time requiring redefining workforce management. Human Resources (HR) needs to proactively identify the relocation, redeployment and retraining of employees. Needless to say, a robust IT infrastructure and platform* are necessary to enable complete automation, and a trusted IT partner to maintain the systems from the word go.

Conclusion

As with all transformations, large-scale automation of banking has many challenges - redefining processes, resistance from stakeholders, fears of job losses, and overhauling of legacy systems when necessary. Parallelly, banks also face competition from new-age fintechs, who are agile and can easily satisfy customer expectations with transformational products and services.

RPA accelerates process efficiency, improves quality, increases compliance and provides operational agility. RPA used in tandem with AI, ML and NLP results in intelligent automation that lets banks add value to their offerings, and spin new products and services to stay ahead in the game.

*For organizations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed on organizational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive, yet modular suite of services is doing exactly that. Equipping organizations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organizations that are innovating collaboratively for the future.