Banks and other financial institutions were not immune to the outbreak, and the fallout continues. Government stimulus initiatives have kept borrowers afloat, but have also left many financial firms with excess cash. As most physical branches have reduced their opening hours and in-person services, customers have migrated almost entirely to digital banking choices.

Financial institutions now play an important role in economic recovery, and the road has been bumpy as strains of the COVID-19 virus have generated transient increases in infection rates. While control of the virus remains fragile, additional difficulties such as supply chain issues and the Great Resignation are emerging, warning banks and other financial institutions that the future is still unclear.

Here are some of the things that could be transformed with RPA in banking:

Loan processing:

RPA can reduce loan processing processes from a month to 10-15 minutes. Important data extracted from documents submitted by clients can be validated using automation. Machine learning is used in systems to provide more decisive options based on data analytics, which are supported by simpler statistical procedures.

Customer integration:

Onboarding new customers to your bank takes effort and a lot of paperwork. Customer onboarding can be done digitally using robotic process automation and KYC document verification.

Account closure procedure:

The number of account closure requests that banks have to process each month is enormous. One problem is the inability of clients to meet deadlines for providing the required documents.

Robotic Process Automation helps banks manage this problem by simply tracking all these accounts and sending them an automated message and other reminders to submit the required documents.

KYC (Know Your Customer):

KYC is not only the most difficult compliance procedure for a bank, but it is also the most important. Banks spend a lot of money on KYC compliance every year. Banks are increasingly adopting RPA to collect, analyze and deep analyze consumer data to save money and resources. This allows banks to complete the KYC process with fewer resources and errors in a much faster time frame.

Processing credit card applications:

Previously, credit card applications required a waiting period of several weeks, which sometimes required applicants to cancel their applications. Banks, on the other hand, can use RPA to speed up the distribution of credit cards.

In just a few hours, the RPA software can collect all customer documents, perform credit checks with comprehensive background investigations, and make intelligent judgments based on pre-established criteria.

Fraud detection:

As the bank fraud landscape grows, banks are concerned about upgrading their fraud detection systems. Modern technology has only increased the number of financial scams. Therefore, banks cannot manually check every transaction to detect fraud trends in real time.

Read also | Artificial intelligence: the science behind the right customer experience

RPA uses an intelligent “if-then” method to detect suspected fraud and flag it for prompt resolution by the appropriate department.

Big general book:

In order to properly create financial statements, banks must maintain their general ledger with critical data such as revenues, assets, liabilities, costs, and revenues. Considering the massive amount of data from multiple platforms, the manual management technique is extremely error-prone.

In an increasingly crowded banking and financial market, it has become vital for banks and other financial institutions to continuously innovate, stay competitive, and provide excellent customer experience to users (especially with the counter-competition mass of FinTech and other virtual banking solutions). RPA will enable banks to ease this burden while optimizing expenses and efficiency.

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