Three Applications of RPA in Banking

Robotic Process Automation (RPA) refers to technological solutions relating to business process automation using software bots or artificial intelligence workers. Traditionally, workflow automation is carried out by a software developer who creates an action list and writes code or uses software APIs to automatically run internal tasks according to a pre-defined sequence. As with all things AI, however, this rules-based coding process is automated in RPA. RPA systems watch the user perform the task in the application GUI and simply repeat those tasks there directly. Implementing RPA in businesses has the potential to effect significant cost savings for organizations, and is, hence, worth considering as a possible solution for the right use-cases.

Implementing RPA in businesses has the potential to effect significant cost savings for organizations.

Banking is one industry vertical that has plenty of possible applications for RPA. Here are three of the possibilities:

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Here are three possibilities for RPA to be applied to banking.

Automating Data Accumulation

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Data Entry can be a dreary and labor-intensive process in the banking business, and Robotic Process Automation can help simplify the process. RPA integrated into the data entry pipeline can speed up the manual data accumulation process. It can also be automated to numerous other tasks in a cost & time-efficient manner. Some of the more specific mechanisms in which RPA can assist with data accumulation are: reducing data entry headcount, speeding up the time allocation, automating the data cleansing & pre-processing requirement, and enhancing the error checking & data correction capabilities of the organization.

Uninterrupted Internal/Customer Service

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The banking industry, like most other verticals, has salaried employees who can only be employed for a specific duration each day. Customer banking, however, is a 247 endeavor, meaning customer service may be necessary even during non-office hours to resolve issues and make customers feel valued. AI-enabled RPA chatbots can help with this requirement, as they can be made available online throughout the day and can be taught to handle requests and send automated messages/alerts to customers when necessary. Internally, however, bots can also be used to automate banking processes that may require significant time-investment, such as setting up new accounts, creating new lines of credit or providing investment advice.

Credit Application Processing

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Processing applications for credit cards is another time-intensive process the banking industry is consumed with, and that is understandable from a manual standpoint given the extensive list of documents required and the customer background check necessary. However, this can cause major inconvenience from a customer perspective, and goes against any business’ core requirement of needing to serve its customers well. This gap can be addressed by RPA solutions, which can employ Neural Network-enhanced Optical Character Recognition for document processing and Machine Learning techniques to decide whether the customer should be approved for the application or not. This level of automation can dramatically shorten the processing period from weeks to just a few hours, and could hence be a tremendous boost to efficiency and productivity in the banking industry.

These are some of the examples where RPA has the potential to make an impact in banking. The future of the banking industry looks an increasingly automated one, where AI & RPA tools complement human workers by automating low-level, repetitive tasks and free them to focus on complex, higher-order responsibilities.

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