Robotic Process Automation (RPA) Use Cases & Examples in banking

Rpa use cases in banking

To stay competitive in a gradually increasingly saturated market – particularly with the widespread acceptance of virtual banking – banking and financial industries need to find a way to provide their customers with the best possible customer experience. Internally, there is also the challenge of increasing efficiency and reducing costs while maintaining maximum security levels. To give a solution for all these demands, Robotic Process Automation (RPA) has become an effective and powerful tool.

A 30-Sec Summary on RPA

  • Robotics Process Automation is the next phase of technology, which solves many problems in the banking sectors. It is emerging as the most efficient way for banks to support their digital transformation efforts.
  • RPA will automate the tasks which are manual and more labor, and minimize the actual need for data reconciliation and repeated manual works so that humans can concentrate only decision-making, complex operations of banking, and human interaction.
  • RPA is a low-cost, high-productivity model, and it is currently disrupting all business-process-outsourcing models in all financial institutions, battling intense competition, disconnect from workflow and misreporting.
  • The secret of Robotic Process Automation’s success in the banking sector is its process validation only on a large scale.

Robotic Process Automation

Robotic Process Automation will automate the tasks which are manual and more labor, and minimize the actual need for data reconciliation and repeated manual works so that humans can concentrate only decision-making, complex operations of banking, and human interaction.
Robotic automation in the banking industry is a very low-cost and high-productivity model, and it disrupts entire process of business- redistributing models in all banking and financial institutions, which are struggling with huge competition, incorrect reporting, and workflow disconnect. The secret of Robotic Process Automation’s success in the banking sector is its process validation only on a large scale.

Gloabal rpa automation market 2016-2021

Examples of RPA automation in banking

Let’s have an eye at the below examples of back-office processes at Banking Industry which will be automated through RPA.

  • We can simply detect the fraud through the bank account tracking
  • adding new accounts details into the systems, transferring data and making multiple entries
  • Account reconciliation that means copying and moving information.
  • Report generation from one system to another system
  • Extraction E-forms by taking data forms and making system entries
  • Cumulative support by making and updating entries
  • Mortgage approval, i.e. calculating and moving data from one place to another
  • Credit card applications process from web-forms

Google trends of RPA

A Graphical analysis of google trends for robotic process automation
Recent RPA trends and forecasts expect that the market for robotic technology in knowledge-work processes would reach the US $29 billion by the year 2021. That is a drastic development from the US $250 million in the year 2016, when it has made its mark at first as a mainstream process-improvement tool.

Use Cases of Robotic Process Automation in Banking Sector


Recommended to read : 10 Use Cases & Examples of Robotic Process Automation in Banking

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Here, we focused on the top 7 banks in the US that are using AI applications to augment their banking processes.
We covered:

  • What kind of Ai applications are using by the US topmost banks like JPMorgan, Wells Fargo, etc.?
  • What kind of AI trends that have attracted them to invest heavily in AI technology?
  • How much capital is invested in AI by the United States leading banks?

Continue Reading to know the ! 

Top 7 US Banks That Are Investing In Artificial Intelligence

1 . JPMorgan Chase
JPMorgan was the biggest US bank in terms of its annual turnover. In terms of technology investments, also the company stood in the first place. According to its annual reports, it invested approximately $11.4 billion in AI technology in 2019. Such a huge investment in AI by the topmost leading US bank shows its interest in the technology inventions.
JPMorgan is majorly focused on how to improve its business performance and achieve operational Excellency using AI technology.
Where is JPMorgan using AI technology?
For conducting quick and automated internal document search, JPMorgan invested in AI technology and introduced Contract Intelligence (COiN). This Machine Learning (ML)-enabled interactive Chatbot system can retrieve required data from the vast database of legal documents in seconds.
JPMorgan also launched an innovative AI initiative, “Emerging Opportunities Engine”, especially for supporting the equity capital and debt capital markets

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2. Wells Fargo

Wells Fargo always eager to invest in the most popular technologies like artificial intelligence and machine learning. They are footprinted into AI with a Chatbot pilot project. Wells Fargo Chatbot application has built on AI technology and helping banking customers in clarifying all their queries related to banking services.
Accordingly, Wells Fargo also introduced an AI-powered mobile app that is developed using predictive analytics. This intelligent Smartphone application alerts customers if their billing payments exceed the limit.
In addition, it also suggests customer transfer money to other accounts, if their account has more money than average. Further, this AI tool for banking also guides you with a travel plan after purchasing a plane ticket.
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3. Bank of America

Bank of America is using AI-driven technologies with a major focus on increasingly expanding Chatbot, fraud detection, and trading functions.
Bank of America’s AI-enabled Chatbot named erica can understand texts and speech delivered by humans. In addition, the company’s other ML-based Chatbot can give the user advice and recommendation based on their financial spending. Accordingly, this Chatbot can lock or unlock the debit card of users on their request.

Every bank is rushing towards AI. Why don’t You?

4. CitiBank

CitiBank is using AI and its technologies to the fullest. With an aim to avoid Fraud actions and Anti-money laundering, it is investing in artificial intelligence technology.
Recently, CitiBank has announced its partnership with Feedzai, helping in the detection of fraudulence.
Feedzai software monitor customer’s payment conduct and location. If it notices a large number of transfers from different locations that the customer is not known too frequent, Feedzai software sends alerts to the fraud analyst before the transaction takes place.

5. US Bank

US Bank is using AI and its technologies to provide a personalized experience to their customers. They are providing a better solution to solve their customer financial needs.
The banks Expense wizard is an artificial-intelligence-based mobile app that makes business travel easy. It eliminates the need to use your personal cards and wait for reimbursement.

6. Bank of NY Mellon Corporation

BNY Mellon believes robotics (Robotic Process Automation) in the banking sector saves money, time, and reduces the manual process. The bank has placed 20 Chatbot in production by which they estimated that the fund’s transfer bots alone are saving $300,000 annually.
7. PNC Financial Services
According to its annual report in 2016, a famous bank holding company named ‘PNC’ has invested around the US $1.2 billion over 5 years into modernizing its core infrastructure with the goal of faster, more secure and more sustainable operations and services, and building operational and technical capabilities.
The firm’s initial focus is on the integration of its data centres and the major shift to the internal cloud environment. We can assume that the organization’s infrastructure upgrades facilitate updates will assist them with utilizing information and execute AI and ML.
PNC has reportedly partnered with Artificial Intelligence vendor’ Anaconda’ to implement it, and has worked closely with Vendor to streamline its data science infrastructure for languages like R and Python. As a result, Anaconda PNC built machine learning models at home inn2016, and turned their infrastructure into Anaconda Enterprise 5.2 in 2018.
Conclusion
As Robotic Process Automation has so many benefits, banks should consider using all of their functional areas to improve the customer experience and gain an edge over competitive banks. It may seem like an expensive investment, but considering the value, it provides to the business, it can offer a great ROI in a very less span.
To implement RPA technology successfully in banking sector, it is crucial to partner with the organization that has proven expertise in RPA technology and tools throughout the RPA implementation process.
This not only brings the profits that financial and bank institutions required but also advises them on how and when to switch from RPA tools and some other upcoming tools like CPA (Cognitive Process Automation), Artificial Intelligence (AI), etc.
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Comments
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