Robotic Process Automation

Robotic process automation: The future that banks should bank on!

Banking is an extremely competitive industry, which is facing unprecedented challenges in staying profitable and successful. This situation demands banks to focus on cost-efficiency, increased productivity, and 24 x 7 x 365 lean and agile operations to stay competitive. As such, financial systems are witnessing dramatic transformation through the deployment of robotic process automation (RPA) in banking, which helps banks tailor their operations to a rapidly evolving market.

According to a McKinsey study, up to 25% of banking processes are expected to be automated in the next few years. Similarly, banking RPA software and services revenue is expected to reach a whopping $900 million by 2022. These indicators place RPA as an essential ingredient in the future of banking; banks must consider how strategic implementation of RPA could become the wind beneath their wings.

How banks have seen tangible success with RPA applications?

Here are just two examples of successful RPA implementation in banking:

  • A major Japanese bank cut down 400,000 hours of manual labour for employees.
  • In one instance, a Singapore-based multinational banking and financial services corporation reduced the turnaround time of re-pricing loans from 45 minutes to a mere minute.

Various other investment banking and financial services companies have optimised complex processes by implementing banking automation through RPA.

Benefits of RPA in banking

As complexities in financial functions grow, banks can adopt RPA to reap the following advantages:

  • Cost-effectiveness:

    By automating repetitive tasks, banks and financial institutions can save up to 50% of processing time and cost.
  • Improved customer service and satisfaction:

    By adopting RPA to take over repetitive tasks, employees can shift their focus on core business functions and provide customers with a consistently superior experience.
  • Growth with legacy data:

    RPA implementation combines essential legacy and new data into one system, thereby bridging the gaps between processes. Furthermore, this enables banks to create faster and more insightful reports to help grow their business.
  • Increased operational efficiency:

    Implementing RPA improves multiple internal processes and activities, making them faster, accurate, productive, and more efficient.

RPA use cases in banking

RPA has a growing number of well-defined use cases in banking. These include:

  • Customer and employee onboarding:

    Using optical character recognition technique (OCR), RPA assists in quick verification and onboarding of customers. This eliminates manual error, reduces waiting period, and eases redressal, thereby improving customer experience. Similarly, new employees are onboarded through automatic creation of their email IDs, welcome mails, and so on.
  • Credit card and loan processing:

    Traditional credit card and loan application processes could take weeks to validate and approve. RPA accelerates the process of gathering customer information, credit checks, and background checks, as well as enables quick decisions on the eligibility of a customer.
  • Fraud detection:

    With fraud and cybercrime costs predicted to reach $6 trillion by 2021, the liability on banks to protect financial data is enormous. RPA eases this burden by applying an ‘if-then’ method to track, inspect, and report any red flags for investigation to the concerned department. In case of delay in response from the department, bots can be further configured to block suspicious transactions.
  • KYC processing:

    KYC compliance is a crucial and data-intensive process that costs banks at least $384 million annually. Implementing RPA to collect, screen, and validate customer data helps improve the process cycle by saving both time and costs.
  • General banking ledger management:

    For accurate preparation of financial statements, the general ledger — which includes interest incomes, expenses, assets, liabilities, and other financial data — needs to be accurately recorded, updated, and error-free. Bots can connect with multiple systems and applications and retrieve legacy as well as new data, thereby delivering the required financial information.

More use cases abound, but what matters is knowing the extent of profitable automation and where exactly can RPA help banks reap maximum benefits. And that’s where we come in.

Infosys BPM approach to RPA in banking

One of our successful partnerships helped a North America–based banking and financial service MNC with load balancing and backlog prevention through operations planning and RPA. We helped the client achieve:

  • Process accuracy of 99.5%.
  • Increase in overall efficiency by 40%.
  • Reduction in average handling time by 50%.

You can read more about how we won the NASSCOM Customer Excellence Award 2018 by overcoming the challenges for the client on the ‘Big Day’. Contact us to discover our platform and technology-agnostic approach to automation that focuses on ensuring metrics improvement, savings, and ROI.

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