Ways Robotic Process Automation Has Disrupted Banking

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The banking industry is reaping the huge benefits of technological innovations! One of the most promising developments is happening in the field of Robotic Process Automation (RPA). This technology is changing how banks work.

Automating manual, repetitive and rules-based tasks, RPA tools enable teams to prioritize more critical and valuable activities. Banks can now provide even better service, while employees can focus on tasks that make a difference!

According to the report, RPA in Banking & Financial Services Make Workplace More Productive with RPA and AI by Automation Edge,

RPA and AI by Automation Edge

Also, AI can automate complex banking processes such as fraud detection and anti-money laundering when used with RPA.

Let us see the use cases of RPA in detail.

Use cases of RPA in Banking

1. Customer Service

Banks face the challenge of handling a large volume of queries every day. These queries can range from questions about account data to the status of applications. Sometimes, when there are too many queries, it becomes difficult for banks to respond promptly.

Robotic Process Automation (RPA) automates processes by following predefined rules. This can result in faster response and significantly reduce turnaround times, sometimes even to just seconds.

This means valuable human resources can be freed up for more critical tasks. RPA combined with AI can even assist in investment decisions.

2. Streamlining Accounts Payable with RPA and OCR

Accounts payable is a banking process that verifies and processes vendor data to make payments.

This task can be automated using Robotic Process Automation (RPA).

The issue of manual data entry is resolved by using Optical Character Recognition (OCR).

OCR reads vendor data from digital copies of physical forms and provides it to the RPA system. RPA then checks this data against its database to ensure accuracy before payment processing.

If any errors occur during verification, RPA automatically flags the issue and notifies designated executives for immediate resolution. This seamless integration of RPA and OCR eliminates manual data entry errors.

It thus significantly reduces processing time and frees up human resources.

3. Fraud Detection

Today, when transactions happen at lightning speed, fraud is one of the biggest concerns for banks. Tracking millions of transactions daily to identify suspicious activity is a huge task. It often leads to delayed responses and, in some cases, can cause significant losses.

RPA can monitor transactions and identify patterns that might indicate fraud. Here’s how it works:

Real-time Tracking: One of the critical advantages of using RPA in the banking industry is due to its ability to analyze vast amounts of data in real-time. It can almost instantly search for anomalies and suspicious patterns in transaction behavior.

Flagging Suspicious Activity:  On detecting potential fraud, RPA immediately alerts the bank’s security team, allowing for a swift response. The response can involve freezing accounts, blocking transactions, or contacting the account holder for verification. This helps flag suspicious activity and prevent financial loss or damage.

Proactive Prevention: In some cases, RPA can even prevent fraud altogether. Again, the ability to recognize established fraud patterns drives this activity.

RPA can automatically identify and block suspicious transactions or accounts, effectively stopping criminals before they can inflict damage.

For banks, maintaining an accurate and up-to-date general ledger is crucial. Shareholders and regulators scrutinize the ledger and the financial statements. Any errors in these statements can severely impact the bank’s image and reputation.

4. General Ledger

In the past, updating the general ledger was a tedious and error-prone task. It required manually extracting data from legacy systems. This data would often be incompatible and siloed. The extraction process was time-consuming, especially considering the large amount of data involved.

However, RPA can now offer an intelligent solution to this problem. It can seamlessly integrate with multiple legacy systems, regardless of format or structure.

It then extracts the necessary data and presents it in a standardized format. Now, the data is ready for integration into the general ledger.

Automating manual data tasks can eliminate errors in critical financial records.

RPA can automate data validation and verification tasks, improving accuracy and efficiency.

This ensures transparency, which helps strengthen the bank’s image and reputation among stakeholders.

5. Reports Automation

Banks are answerable to their stakeholders just like any other public company. They need to provide transparent and accurate reports on their performance in a timely manner. Even a minor mistake in these reports can have severe consequences. 

RPA transforms how banks handle reporting. It is an effective tool that automates report generation, helping banks to achieve greater efficiency, accuracy, and transparency.

As a result, it helps to build stakeholder trust, facilitates informed decision-making, and contributes to the financial success of banks.

6. Streamlining Account Closures with RPA

Managing a high volume of client accounts comes with its fair share of challenges. Delays can happen due to missing documents or exceptional circumstances. RPA offers a powerful solution to streamline this process:

  •  Tracking Accounts: RPA bots can automatically identify accounts pending closure due to missing documentation. This ensures no closure is overlooked, leading to faster resolution.
  •  Automated Notifications: RPA triggers automated emails or SMS reminders to clients, prompting them to submit the required documents. This saves time and effort for both the bank and the client.
  •  Scheduled Calls: RPA can schedule personalized calls to clients who have not responded to notifications. This proactive approach increases document collection rates and speeds up closures.
  • Exceptional Scenarios: RPA can handle unique cases, such as accounts with missing KYC documents. Bots can flag these accounts for review, prompting human intervention for a smooth and compliant closure.

Benefits RPA provides for Banks:

  •  Faster account closure process
  • Reduced manual workload
  • Improved customer service
  • Enhanced compliance
  • Increased efficiency

7. RPA making Underwriting in Banks

Underwriting, the backbone of financial transactions, involves assessing risk before issuing loans or insurance policies. Collecting data from various systems, analyzing it, and inputting it into the central system takes time and effort.

Also Read: Robotic Process Automation (RPA) in Finance: Driving Efficiency and Productivity

Here’s how RPA can transform underwriting:

  • Streamlining Data Collection: RPA automates data collection from multiple sources, eliminating manual effort and ensuring accuracy. This significantly reduces processing time and allows underwriters to focus on more complex tasks.
  • Algorithmic Risk Assessment: RPA enables automated loan decisions based on predefined algorithms, removing human bias and subjectivity. This ensures consistency and fairness in the underwriting process.
  • Reduced Errors and Misinterpretations: By eliminating human intervention in data entry, RPA minimizes the risk of errors and misinterpretations, leading to sounder risk assessments.
  • Faster Processing: Automating repetitive tasks frees underwriters from administrative burdens, allowing them to process loan applications significantly faster. This translates to improved client satisfaction and quicker access to funds for borrowers.
  • Enhanced Compliance: RPA ensures adherence to regulatory requirements by automatically checking for missing documentation and flagging potential compliance issues. This decreases the risk of regulatory penalties and fines.
  • Greater Efficiency and Cost Savings: Streamlining the underwriting process with RPA leads to increased efficiency and cost savings. This allows banks to offer competitive rates and improve their bottom line.

One of the major advantages of RPA is its ability to improve accuracy. It is critical when assessing loan applicants’ creditworthiness. Additionally, by reducing processing times, RPA is streamlining the loan application process. It can make it faster, more efficient, and fairer for everyone involved.

Bineesh Mathew
Bineesh Mathew
Bineesh Mathew is an accomplished senior writer with 10+ years of experience in multiple domains. With a proven track record, he has specialized in writing for business strategies, marketing technologies. Currently, Bineesh is working as a Senior Content Writer with TalkCMO. Bineesh is an English Literature graduate who has mastered the language with excellent editing skills. As a writer, he has contributed exciting writing pieces for various topics such as digital marketing, cybersecurity, and different latest technologies, including Artificial Intelligence, data analytics, machine learning, and much more.

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