Contact us anytime to know more — Abhishek P., Founder & CFO CISIN
What is RPA?
RPA technology can be utilized within the banking sector to automate repetitive and time-consuming processes like account opening, KYC verification and customer service.
RPA provides a cost-cutting option while simultaneously streamlining operations. According to estimates, RPA could reach $1.1 billion by 2025. AI could also automate complex banking processes like fraud detection and anti-money laundering detection.
Why Is Rpa Important In Banking?
Bank employees often face large volumes of customer data requiring manual processes. Unfortunately, manual processing and extraction can lead to mistakes; bots can help validate customer data from two systems faster than manual processes by validating customer details in seconds instead of minutes and automating manual processes at 30%-70% less cost - freeing up human resources for more critical tasks within banks.
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Top 13 RPA Use Cases in Banking
RPA can be used in various ways to help free up human resources for more critical tasks. These processes include:
Customer Services
- Daily, banks field thousands of inquiries ranging from account details and application status updates to balance inquiries. Unfortunately, banks often find it challenging to respond politely to these inquiries.
- Over eighty percent of those who used chatbots to inquire about products within the past year would prefer visiting a physical branch instead.
- RPA automates rule-based processes to respond in real-time and decrease turnaround times to seconds, freeing up human resources for more critical tasks.
- RPA utilizes artificial intelligence to provide solutions that require decision-making. At the same time, Chatbot Automation employs natural language processing (NLP) techniques to enable bots to understand human speech and respond as though they were human beings.
Compliance
- Accenture's 2016 survey found that 73% of respondents believed RPA could help the banking industry meet numerous compliances, increasing productivity while improving compliance processes.
Accounts Receivable
- Accounts Payable in banking is a straightforward and monotonous task that entails collecting vendor data, validating it and processing payments. RPA can help by automatically performing these actions without needing human intelligence to process payments.
- Robotic Process Automation (RPA), with optical character recognition solutions, may offer a solution. OCR reads vendor information in digital form and passes it on to RPA, which compares it with system information to process payment while notifying the executive of any errors that arise.
Credit Card Processing
- Traditional credit card applications used to take several weeks for banks to process, verify customer information and issue credit cards. Customers were dissatisfied with this lengthy wait time, while banks paid for it in terms of increased costs for administration. Now, with RPA technology,robotic process automation finance banks are processing applications much more quickly; RPA can simultaneously communicate with multiple systems to validate information such as required documents, background checks, and credit checks before making its own decision on approval or rejection according to established rules.
Mortgage Loan
- Processing a mortgage typically takes 50-53 days in the United States. Approval involves various checks such as credit checks, repayment histories, employment verification and inspection; minor errors could further slow the process. RPA technology based on specific rules can cut this processing time from days to minutes.
Fraud Detection
- Fraud has become an increasing risk for banks with the advent of digital systems. While traditional banks struggle to monitor every transaction for potential fraud transactions, RPA can monitor transactions in real-time and identify suspicious patterns that reduce response times and speed up response time in certain instances by blocking accounts or stopping transactions.
KYC Process
- "Know Your Customer" (KYC) compliance is a bank requirement. This process typically involves 500 to 1,000 FTEs performing necessary checks on customers to complete it successfully. banks spend an estimated annual budget of over $384 Million on KYC compliance efforts.
- Banks have recently adopted RPA as an automated solution to validate customer data due to the high costs of manual processes. No longer must FTEs worry about FTE limitations, while processes can now be completed more accurately with minimal errors.
General Ledger
- Banks must update the general ledger with financial statements, assets, liabilities and expenses regularly to create financial statements that can then be viewed by stakeholders, the media and the general public - with too much information compromising a bank's reputation being read out publicly in these financial documents.
- Banks must update information across legacy systems that cannot be integrated and verify it for accuracy before updating new information. Managing such large volumes of information across different systems inevitably introduces errors, which is where RPA comes into its own: it works independently from technologies to bring together disparate legacy systems and present them all as one cohesive whole in their required format, saving time and handling space.
Reporting Automation
- Like other public companies, banks must prepare and present reports to their stakeholders to show them their performance. It is of such great significance that mistakes must not occur.
- RPA systems can automatically fill available report formats by using data provided in various formats, producing reports with minimal errors and time spent producing them.
Account Closure Procedure
- Banks typically receive requests to close accounts every month. There could be various reasons, but one likely cause for such closures could be that a customer has failed to submit all required documentation for account opening or maintenance.
- Robotic Process Automation makes it simple for banks to keep tabs on customers' accounts, schedule calls and notify them when documents such as KYC are due for submission. RPA also enables them to close accounts in rare circumstances when customers fail to provide necessary KYC documentation.
Underwriter Support
- Underwriting is a process used to assess the risk associated with financial transactions such as bonds, bank loans and insurance policies. Collecting data from different systems manually before inputting it into one central system for processing can be both time-consuming and taxing; RPA plays an essential part in automating this task and allows loan decisions to be made more reliably by using algorithms than human beings alone.
Cash Collection
- Cash collection and deposit are an ongoing challenge for banks and financial organizations, especially at various points of sale. Human workers do not have enough time to collect these tasks from various points of sale and move them accurately across branches. RPA can help banks consolidate all records into one centralized system for easy sharing and access while protecting transactions against money theft; alerts will also be sent out in case of suspicious activity.
Account Opening Process
Account Origination Process Is Time-Consuming, From Application to Underwriting and Disbursement Funds Staff at the Banking Service Desk must take time-consuming steps such as prequalification documents, application processes, underwriting processes, credit decisions, quality controls and initiating funding processes to initiate funding of accounts.
RPA makes loan processing faster, ensures regulatory compliance, and adheres to rules. RPA allows banks to accomplish more with less staff while reaping financial benefits.
According to PricewaterhouseCoopers' financial section survey, 30% of respondents had already initiated RPA trials or planned on adopting it enterprise-wide.
How to Implement RPA Banking?
After creating an Automation Roadmap, financial institutions should conduct a Proof of Concept exercise. This will allow them to showcase the benefits of automation while refining their approach.
Follow these steps to ensure RPA implementation successfully in your banking organization: Automation should begin in financial areas by creating a roadmap with multiple automation for implementation and finding and selecting providers with expertise to assist with designing and delivering the project. Finally, create an enterprise governance and delivery model that supports global businesses to maximize the effectiveness of operations.
Organize training sessions and devise a change management plan to promote efficient RPA adoption.
Automated Banking: RPA for Banking
CIS a provider of automation solutions across various industries, has assisted multiple financial and banking services providers to optimize workplace efficiency and business processes.
One such client was experiencing robotic process automation solution challenges with process inconsistency and high error rates, resulting in reduced revenues and higher operating costs. Processing a single loan application took 40 minutes, whereas using CIS RPA simplified this process drastically, decreasing it from 40 minutes to 20 minutes for processing loan applications through.
What Does Financial And Banking Robotic Process Automation Entail?
RPA (Robotic Process Automation) refers to using robotics applications in finance to augment or substitute human effort in the financial industry.
Automating repetitive manual tasks within accounting and banking departments, RPA allows employees to focus on more strategic tasks while giving companies an advantage over competitors.
Basic robotic process automation using rules has limited capabilities; it merely follows them to automate tasks without any variation, for instance, logging in, transferring files and signing out again.
Banks can enhance RPA software further with artificial intelligence technologies, including machine learning and natural language processing. RPA can easily manage complex processes while understanding human language, recognizing real emotions, and adapting accordingly.
Rpa Benefits In Banking And Finance
Robotic process automation (RPA) can be found across industries, including Insurance, Healthcare and manufacturing.
the global RPA market has reached $1.57 billion, and Gartner predicts its annual compounded growth to reach 32.8% between 2021-2028. Financial process automation offers several advantages over manual processes.
Scaling operations as required is easy, with robots working for longer without needing breaks and being able to meet increased demand volumes during peak times.
Time Savings. Time-saving apps can reduce up to 90% of the time required to complete a task. Reduce expenses. Deloitte estimates that RPA deployment could result in a 30% cost reduction.
Accenture forecasts an 80% savings with robotics for finance applications.
Reduce It Department Interference:
Employees can efficiently train themselves to use robotic assistants.No additional infrastructure costs are incurred as RPA implementation in banking and finance requires only minor infrastructure changes; instead, it acts as an overlay over existing banking applications.
Studies show that robots are up to five times faster at performing specific tasks than human employees, freeing people from mundane duties to focus on fulfilling ones and increasing employee happiness and well-being.
Financial RPA can minimize human error. By taking an organized approach to its tasks, Financial RPA improves output quality by eliminating human mistakes like not paying enough attention to an assignment.
RPA in Banking and Finance
Rpa For Report Generation
Financial RPA streamlines reporting tasks, such as monthly closings, reconciliations and management reports. Banks and financial institutions must present reports to their board of directors regarding performance and challenges they are experiencing.
Humans find these documents, containing large volumes of data, difficult to manage. Robotics in banking and finance can quickly gather this information from multiple sources before formatting it. Hence, it is easily understandable, producing error-free reports.
Societe Generale Bank Brazil has automated a process that was once taking up to six hours out of employees' workday.
RPA technology can assist compliance officers in processing suspicious activity reports more quickly. Officers using software with natural language processing abilities to read lengthy documents instead of manually perusing each one; RPA will extract all the pertinent data needed and populate a SAR form with all required fields.
RPA for Accounts Payable
Manually handling accounts payable can be time-consuming. Employees must digitize vendor invoices, validate the data, and pay vendors.
Robotic process automation (RPA), combined with optical character recognition (OCR), can considerably simplify this process by extracting invoice data directly into payment processing robots for payment processing and validation - alerting bank staff in case of errors in processing payments.
Accounts payable is often exhausting when done manually by employees, as they must digitize invoices from vendors and validate the fields before processing payments.
With RPA enhanced with optical characters recognition (OCR) handling this task, however, this time-consuming task becomes significantly faster - the OCR extracts data from invoices before sending it to robots that validate and process payments; any discrepancies will alert bank staff immediately - creating a seamless payment experience and saving both parties valuable time and effort in processing payments accurately and swiftly.
Here is an example from our internal expert's portfolio: A company that manufactures baby strollers and car seats wanted to automate its accounts payable process, with each branch sending financial documents in their unique format to each department to verify if all information provided matches bank statements.
Performing such manual processing could become laborious.
RPA for Mortgage Processing
RPA use cases are increasingly prevalent within banking and finance. According to reports, banks can close a mortgage in 60 days.
Loan officers must undergo a series of steps, such as employment verification and credit checks. Even minor errors by either employees or applicants can delay this process considerably. In contrast, robotic process automation could shorten loan processing by up to 80%, providing significant relief for banks and their clients robotic process automation implementation.
Radius Financial Group used RPA to accelerate mortgage processing. Using this configuration, loan processors could easily manage up to 50 loans at once.
As a result, Radius was able to reduce loan processing costs by 70% using this solution.
Radius thrived even during the COVID era thanks to intelligent robotic automation. Their loan production revenue exceeded industry norms by 30% as measured by the Mortgage Bankers Association; their net profit was approximately 50% higher than industry norms for banking industry companies.
RPA in Know Your Customer (KYC)
KYC compliance for banks can be an extensive undertaking. This process may take as much as 1,000 full-time equals (FTEs) and 384 million dollars annually to comply.
Alert investigation takes time; up to 88% of daily alerts may be false positives, while 25% require review from level two senior analysts despite efforts made. Despite all their efforts, banks still lose EUR 50,000,000 per year due to KYC penalties.
By integrating robotic process automation (RPA) into the KYC process, errors requiring you to interact directly with customers can be reduced, resulting in quicker customer onboarding and improved customer experiences.
RPA will thus accelerate customer onboarding processes and enhance the customer experience.
Rpa Fraud Detection
Studies show that highly trained analysts tasked with uncovering crimes typically spend 75% of their time gathering data.
In comparison, 15% is used to enter it into systems. According to University of California Los Angeles studies, analysts spend 75% of their time gathering data. In comparison, 15% goes toward entering it into systems.
Both tasks could easily be automated so fraud professionals can focus solely on their primary tasks.
An "if-then method" to detect fraud can aid anti-money laundering investigations. RPA, for example, can use this strategy to detect accounts that have been utilized heavily within a short period and report these accounts to relevant departments.
Customer Onboarding
Banks face numerous regulatory requirements when onboarding new customers, from collecting personal and financial data through government-approved organizations to creating an account and monitoring and archiving processes, plus collecting it all themselves.
RPA systems can automate many of these processes to lower operational costs and risks and more rapid onboarding times of clients.
Compliance
Financial services are highly regulated industries. Banks must complete various reports and calculate expected credit loss (ECL).
Compliance officers also devote approximately 15% of their time to monitoring changes in regulatory requirements. RPA bots can quickly and economically collect data from various sources like government websites, federal agencies and news organizations and input it directly into a bank's system according to strict data structure guidelines - saving time and cutting costs simultaneously.
Loan Processing
Employee allocation to loan processing determines its volume. RPA technology can help banks automate many loan administration tasks, such as underwriting and verification using RPA.
RPA software consolidates relevant data from third-party systems and paper documents into appropriate systems so underwriters can analyze it further. RPA can also help transfer the information directly into these systems for underwriters to analyze further.
Customer Service
Banks understand customer service is of utmost importance, and Robotic Process Automation (RPA) can significantly cut processing times for low-priority queries within the banking industry.
Chatbots powered by RPA can automate simple processes, like checking account balances and blocking accounts as quickly as possible, monitoring mortgage application statuses and processing loan inquiries.
Accounts Payable
Paper invoicing remains commonplace, and documents have yet to be standardized, making accounts payable an arduous task that involves frequent copying and pasting.
Organizations can streamline processes like retrieving vendor data, checking it for errors, and initiating payment without human involvement. RPA software combined with optical character recognition (OCR) enables automatic data capture and reentry. It provides an audit trail, simplifying reporting on compliance.
Credit Card Processing
Banking digitization has made issuing credit cards faster, but it still requires human assistance. An RPA bot can approve most credit card applications independently, speeding up the process and increasing customer satisfaction.
An RPA bot can access various systems to verify applicants' identities, perform background checks, approve or deny applications and, in certain instances, direct customers directly to human employees for approval or denial decisions.
Fraud Detection
Banks can be particularly vulnerable to cyberattacks due to the amount of sensitive customer data they possess. There are various machine learning-based anomaly detection systems and RPA-enabled fraud detection solutions that have proven themselves as effective ways of combating this threat.
RPA can help automate data manipulation and human judgment. Instead of solely relying on humans for making decisions and manipulating data, banks can utilize RPA to monitor transactions continuously, identify anomalies using complex rule-based systems, flag them as fraudulent activity, and alert employees of these alerts for review - saving employees time while freeing their cognitive powers to focus on what truly matters instead.
Know Your Customer
Banks have increasingly adopted automation solutions due to the increased regulatory scrutiny and compliance costs.
Many do not wish to automate KYC because reconfiguring disparate but connected systems is expensive and complicated. RPA systems are attractive because they can easily integrate with existing systems with minimal disruption to workflow.
RPA automates rules-based processes like setting up and validating customer data collection and gathering and compiling it.
Account Closure
Account closure requires many routine and predictable tasks, including sending emails to customers, validating bank records (such as verifying that check cashing agreements exist correctly) and updating data on internal systems.
These rule-based processes can be automated with RPA, freeing employees to focus on more valuable or cognitively demanding tasks.
General ledger
RPA can help transform tedious and repetitive account reconciliation tasks for mid-sized and larger banks; updating financial statements, assets, liabilities, and expenses across disparate legacy systems is time-consuming and error-prone.
Banks can outsource most of these tasks to RPA bots, which automatically collect data from various systems while validating loans, verifying payments, reconciling general ledger accounts etc.
Read Also: Automating Business Processes with Robotics
Implementing Robotic Process Automation In Finance
one of our RPA experts, suggests following these steps to begin using robotic process automation: Select your robotic process automation software platform carefully.
Four tested and reliable options exist,. When searching for vendors, consider what kind of automation you wish to implement: essential without machine learning capabilities or advanced RPA solutions with computer vision capabilities, such as automated payment validation systems that prevent money laundering.
Finding vendors who can assist in integrating an RPA solution into your system is ideal. When searching for intelligent process automation providers, consider their experience, preferred technology stack and ability to go beyond RPA/AI to data science/AI (if required).
Prepare to Roll: Keep in mind that legacy systems can be challenging to automate, 43% of US banks use COBOL systems, an outdated language developed during the 1950s that does not correspond with modern technology.
Automated solutions must be available 24 hours daily, seven days a week. Ensure you have backup systems and are prepared to switch architectures instantaneously if required.
Be patient, as automation takes time; simple processes usually take three months. For instance, retrieving financial data from PDF documents and entering it in database fields takes roughly this long.
Complex processes may take one or two years.Assure that end users of automated processes can complete their work without extensive training sessions. Plan and implement multiple process scenarios. Automating only the most frequent processes may not suffice over time, as your employees may sometimes need to intervene.
Automation is a gradual process. No single program or task will ever become fully automated overnight. Instead, the part-by-part implementation may be undertaken before leaving employees to manage any remaining cases.
As your business expands, its financial RPA solution may no longer suffice - which is where A large bank with numerous small farm clients used an RPA solution that relied solely on automating paperwork to process financial documents and balance sheets for all clients despite different business environments; when that bank expanded into other sectors with different types of companies their RPA solution could not adapt quickly enough to process accounts payables/ receivables of new clients as quickly.
A bank requires an enterprise-class robotic process automation solution equipped with machine-learning capabilities for financial RPA. After deploying its robotic process automation system, employees experienced an incredible fourfold productivity boost.
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Final Note
RPA (Robotic Process Automation) is an exciting technology in finance and banking, providing basic chatbots with the capacity to execute highly repetitive tasks, such as helping customers order new cards or change PIC codes.
At the same time, intelligent automation performs more complex duties, such as analyzing client history data to detect suspicious transactions.
The banking and finance industries are experiencing increasing robotic process automation. However, one must choose their starting point carefully to make an effective start, as all processes cannot be automated simultaneously.
Here is his advice for taking steps toward automation:
