Today, the banking sector is under immense pressure to increase operational agility and profits and remain competitive in the saturated market. On the other hand, many banks are still operating on legacy systems, and banking employees are responsible for performing many routine processes, which results in a sharp increase in personnel costs.
In this context, the implementation of Robotic Process Automation (RPA) technology will enable banks to address these pressing challenges, reduce costs, and improve efficiency. RPA can be used as a valuable tool to digitize the front end (wealth management, sales, investment banking), middle office (the department responsible for managing risks and calculating profit/losses), and back-office (accounting, IT, regulatory compliance, etc.).
This article will discuss how RPA is beneficial for banks and how this technology can assist these institutions in addressing the "challenges of routine operations." We will also present ten RPA use cases most suitable for banks and deliver significant value at lower costs.
Challenges of Routine in Banking
Typical banking activities such as applying for a loan require data collection and structuring involving many employees and various internal systems. The employees would manually enter the information in Excel files. Then others would manually check this information for errors. There are chances of mistakes during the data entry phase; simultaneously, the examiners may also miss some of these due to the heavy workload. Then the processing time of such applications usually takes days, if not weeks.
The bank's internal resources are more involved in such routine and repetitive activities. Such tasks are very monotonous, which can lead to an increased risk of errors. Also, the employees may not have an opportunity to focus on higher-value activities, which leads to employee dissatisfaction and poor customer service. Another issue is the rising compliance costs, and assigning more and more resources to manage compliance is not a good strategy.
With the introduction of RPA, most of the banking work, which is routine, can be transformed, allowing banks to offer better compliance, eliminate manual efforts, mitigate risks, and improve the customer experience. By offloading such tasks that consume valuable time, employees will focus on important strategic tasks.
RPA in Banking: Advantages
The banking sector, among other industries, has been successful in implementing RPA projects. Banks have been able to save time, costs, and manual labor, reduce compliance risks, and at the same time make business processes efficient and free from errors.
RPA has disrupted the banking sector struggling with workflow disconnection, competition with the widespread adoption of virtual banking, and incorrect reporting. Let's take a look at the benefits of using RPA in banking, i.e., automating these processes will help:
- Generate audit trails for every process, reduce business risk, and maintain process compliance.
- Enhance customer service by effectively reducing the turnaround time.
- Make quick approval/disapproval decisions and validate customer's information necessary for critical processes such as credit card processing.
- Track all bank accounts and sending automated reminders to submit required documents necessary for account closure and other processes.
- Perform error-free data collection, reporting, and regulatory monitoring.
- Save time and cost for processes like data collection, verification, and entry.
- Freeing up bank employees from repetitive tasks and letting them put more focus on more value-added activities.
- Achieve high accuracy at a low cost as RPA in banks does not require any significant changes in the infrastructure.
- Bridge the gap between the legacy and new data effectively, and create better reports for business growth.
Ten Use Cases: Bots for Banking
Loan Applications Processing
The loan application process is an exceedingly paper and resource-intensive activity involving multiple databases, systems, and reports. It involves several manual tasks–data extraction from numerous forms, checking identification documents, assessing creditworthiness, and lends itself well to automation. Additionally, bank employees receive several forms and documents in several formats via email.
This activity is prone to data entry errors, lost documentation, and compliance violations, etc. Automating this process will help banks expedite it without compromising on quality and consistency while demonstrating full auditability. The bots will make the process more streamlined and reduce the extensive time required in secondary review.
The bots will perform these actions:
- Read emails, categorize and assign them to relevant employees.
- Read and extract data from multiple sources and formats, and enter it into the relevant system.
- Verify data from the source files (reconciliations and quality control/assurance).
- Verify the status of cases.
- Process the cases following rules.
- Execute the following steps, and maintain the sequence of operations (perform workflow management).
- Execute audit trials.
Back Office Functions
Automating back-office functions such as audit, quarterly/monthly closing, which involves reconciliation, could be easily entrusted to bots. These bots can also handle the checking of account information and transaction history of customers, send emails to managers and customers, and update the data in the internal system.
The bots will also assist the bank managers/client advisors with a "360" view of a customer's situation without opening several applications on their workstations.
See how a bot can expedite one of these arduous processes– the account reconciliation process.
Know Your Customer (KYC)
KYC is a critical part of the customer onboarding process. It is a highly complex process that involves the manual verification of various identity documents and their compliance with the current regulations. KYC is important in banking regulations to prevent corruption, fraud, identity theft, etc.
Performing customer due diligence costs a bank millions per year. Banks can reduce this expense by implementing RPA technology. For instance, RPA (along with Optical Character Recognition-OCR) can fully automate the manual data extraction process and save employees' time and effort of working with hundreds of documents and application forms daily.
Account Opening and Closure
The registration process for new customers often requires a face-to-face meeting or telephone identification when a bank employee collects information from a customer and enters it into the internal system. To make the data entry process more efficient and error-free, you can deploy RPA.
Similarly, the process of closing accounts can be performed by bots who will verify whether the customer has paid the loans on time or if there are any outstanding payments and other details before completing the account closing process.
For banks, excellent customer service is a must-have as customers gauge the service through experiences. Thanks to automation tools such as chatbots, banks can meet the needs of their customers with less effort.
Banks can use RPA technology to provide quick, 24/7 responses to customer inquiries about account opening, transaction history, balance checking. Banking agents can use bots to centralize all customer data in a single place, so banking agents can keep track of all conversations, know the customer's context, and respond quickly to their requests. Banks can use this tool to offer higher customer satisfaction levels, retain and engage them with new offers.
RPA can digitize the monotonous Accounts Payable process by digitizing invoices. A bot can extract information from the fields of an invoice, validate it, and enter it into the relevant system. The bot will then send the invoice to the manager responsible for approval and then credit the payment to the vendor's account after validation and error reconciliation.
These bots can also send automatic payment reminders to the managers and compare the purchase data with the invoice to check for any inconsistencies.
Anti-Money Laundering (AML)/ Fraud Detection
The AML analysts invest most of their time and efforts in data collection, data entry and management, and then analyzing it. RPA technology can automate this time-consuming investigation process as it is difficult for analysts to check transactions and identify fraud patterns manually.
Based on set parameters, bots can identify and flag transactions and alert the relevant department. Similarly, a bot can identify a potential threat by examining the frequency of transactions made from an account (or any other rule) and notify the bank to scrutinize it for money laundering.
Credit Card Approvals
It takes several days for a bank to evaluate and approve a credit card application, which usually results in customer dissatisfaction. The unnecessary delays sometimes result in the cancellation of the request.
With the help of RPA, banks can speed up this process, cut costs, and improve customer service. Instead of several days, a bot will only take a few hours to collect documents, perform background and credit checks, and help the manager approve or reject a credit card application.
Banks can deploy bots on their websites to assist clients in enhancing conversational engagement and build long-term relationships. An investment chatbot will analyze the input from customers and present the best investment opportunities based on their preferences.
These bots are also helpful in lead generation and assist with securing new customers. They can answer questions around the clock, help with personalized suggestions, provide info on policies and promotions–they simplify the buying process for customers by offering guidance on financial advice, money management, etc.
New Employee Onboarding
This activity involves filling in a new employee's information and performing a series of steps such as collecting documents for verification, giving new hires access to systems and applications. Automating this process will allow the bank to automatically trigger all actions in a sequence without the IT and HR staff's involvement and complete this process quickly that used to take several days.
- Read and extract data from documents and enter it into the relevant system.
- Create a user account.
- Create an email address.
- Configure workstation and access to a telephone line.
- Deliver a badge.
- Make entries into the payroll system.
- Allow access to various applications.
This article presents ten RPA use cases that banks can use to deal with voluminous data, minimize errors, and increase productivity. Additionally, the digital revolution is changing the game for the banking sector, which must rethink how to respond to fierce competition from new entrants and ever more pressing regulations.
While banks would prepare a three to five-year plan to reinvent but still capitalize on the same old systems, digital acceleration and competition have forced them to present results within months. In this context, RPA technology should be the first option to be considered for a transformation journey.
Consider ElectroNeek as your guide in the automation journey. Book a demo to start!