RPA automating banking processes

RPI

Banks and other financial institutions were not immune to the epidemic, and the fallout is still ongoing. Government stimulus initiatives kept borrowers afloat but also left many financial firms with surplus liquidity. As most physical branches curtailed hours and in-person services, customers migrated nearly entirely to digital banking choices.

Financial institutions are now playing a significant role in the economic recovery, and the road has been bumpy as COVID-19 virus strains generated transient surges in infection rates. As control of the virus remains shaky, additional difficulties such as supply chain concerns and the Great Resignation emerge, 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 the banking sphere:

Processing of loans:

RPA can decrease month-long loan processing processes to record duration of 10-15 minutes. Important data retrieved from customer-submitted papers can be validated using automation. Machine Learning is used in systems to deliver more decisive options based on data analyses, which are backed by simpler statistical procedures.

Customer Onboarding:

Integrating new clients into your bank takes effort and a lot of paperwork. Customer onboarding may be done digitally using Robotic Process Automation and KYC document verification.

Account closure procedure:

The amount of account closure requests that banks must handle each month is enormous. One issue is the clients’ inability to meet the deadlines for supplying the required documents.

Robotic Process Automation helps banks to handle this issue by simply tracking all of these accounts and sending them an automated message and further reminders to submit the required documents.

KYC (Know Your Customer):

KYC is not just the most difficult compliance procedure for any 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, analyse, and extensively analyse consumer data in order to save money and resources. This allows banks to complete the KYC process with fewer resources and errors in a much quicker period of time.

Processing credit card applications:

Previously, credit card applications required a several-week waiting period, which occasionally caused applicants to cancel their requests. Banks, on the other hand, can employ RPA to speed up the distribution of credit cards.

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

Fraud detection:

As the banking fraud landscape develops, banks are worried about upgrading their fraud detection systems. Modern technology has only increased the number of financial scams. As a result, banks cannot manually check every transaction to detect fraud tendencies in real-time.

Also Read | Artificial Intelligence: The Science Behind The Good Customer Experience

RPA employs a clever “if-then” method to detect suspected fraud and flag it for prompt resolution by the relevant department.

General ledger:

In order to correctly create financial statements, banks must keep their general ledgers up to date with critical data such as revenue, assets, liabilities, costs, and revenue. Given the massive amount of data from several 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 continually innovate, remain competitive, and provide a great customer experience to users (especially with the massive counter competition from FinTech and other virtual banking solutions). RPA will allow banks to alleviate this burden while also optimising expenses and efficiency.

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