RPA in banking utilises advanced automation tools to streamline repetitive tasks, enabling employees to prioritise customer-centric activities and add more value to their work. In short, RPA emulates human actions, interacting with the software while exponentially increasing efficiency.
In this blog, we will understand "RPA in Banking," exploring its nuances, benefits, and the pivotal role it plays in reshaping banking operations, and also study some of its use cases.
Power of Automating in Banking
RPA is a transformative solution that enables banks and finance companies to streamline processes, enhance compliance, mitigate risks, and improve overall customer experience. What sets RPA apart is its ability to achieve these goals without the need for additional infrastructure and its low-code approach.
RPA in the banking industry focuses on automating repetitive tasks, boosting productivity by engaging customers in real-time and harnessing the benefits of robotic efficiency. While implementing RPA involves extensive training, structured inputs, and governance, once set up correctly, these automation robots can take control of various system actions, from clicking and opening applications to sending emails and copy-pasting information across banking systems.
Comparable to an Excel macro, these RPA-based robots operate at the individual data field level, ensuring seamless functioning across banking software systems.
Hence, RPA emerges as a game-changer, offering a cost-effective and efficient solution to the challenges posed by compliance operations in the banking sector.
RPA Use-Cases in Banking
Here are a few examples of RPA use cases in the Banking industry:
1.Automatic Report Generation
Banks and financial institutions routinely require compliance officers to generate reports for fraudulent transactions, commonly in the form of Suspicious Activity Reports (SARs). Traditionally, compliance officers manually review all reports, entering necessary details into the SAR form, resulting in a time-consuming and repetitive task.
RPA technology, equipped with natural language generation capabilities, reads lengthy compliance documents, extracts required information, and files SARs. To enhance performance, compliance officers can train the RPA software using their insights on document sections that align with specific report components.
This approach not only reduces operational costs but also saves time spent on task execution.
2. Customer Onboarding
Customer onboarding in banks typically involves a protracted process, mainly attributed to the manual verification of numerous documents. The utilisation of RPA can significantly streamline this process by employing Optical Character Recognition (OCR) to extract data from Know Your Customer (KYC) documents. Subsequently, this data undergoes comparison with the customer-provided information within the form.
Upon successful automated matching without discrepancies, the data is promptly integrated into the customer management portal. RPA automation in customer onboarding not only mitigates manual errors but also conserves considerable time and effort expended by employees.
3. Loan Processing
The loan processing procedure is somewhat tedious, and its capacity is constrained by the number of employees assigned to the task. RPA technology in banking adds significant value by automating various loan administration processes, such as underwriting and validation.
RPA solutions enable the autonomous consolidation of pertinent information from paper-based documents, third-party systems, and service providers. Furthermore, these tools can enter this data into the appropriate systems for further analysis by underwriters.
4. Customer Satisfaction
Customer satisfaction serves as an important benchmark for all businesses, including banks. Most customer requests in the banking sector involve simple data retrieval. Implementing RPA can significantly reduce the time needed to handle low-priority customer queries and nearly eliminate the necessity for human intervention in numerous instances.
For instance, RPA-powered chatbots can efficiently handle tasks such as checking account balances, initiating urgent account blockages, reviewing mortgage loan application statuses, and processing simple loan inquiries. This technology streamlines these processes, making them quicker and more efficient.
5. Fraud Detection
Banks possess extensive amounts of sensitive customer data susceptible to cyberattacks. Numerous machine learning-based anomaly detection systems and RPA-enabled fraud detection systems have demonstrated their effectiveness.
Rather than depending on human judgement and predominantly manual data manipulation, banks can employ RPA tools to consistently monitor customer transactions, identify anomalies using an intricate rule-based system, label them as potentially fraudulent, and dispatch alerts to human employees for additional review. Instead of dedicating valuable time to data collection, employees can apply their cognitive abilities where they are genuinely needed.
6. Account Closure
Account closure involves a series of sequential and frequently predictable tasks, such as sending emails concerning customer documents, validating a bank's records (e.g., confirming the existence of the relevant check-cashing agreement), and updating data in the internal system.
These rule-based processes can be automated using RPA, enabling employees to concentrate on more valuable and cognitively demanding tasks.
7. General Ledger
Particularly for mid-sized and large banks, the time-consuming and error-prone process of overseeing and updating financial statements, assets, liabilities, and expenses in disparate legacy systems can be streamlined.
Banks can leverage RPA to shift these responsibilities, enabling bots to automatically gather data from multiple systems, validate payments, verify loans, and reconcile general ledger accounts. This approach not only enhances efficiency but also minimises the risk of errors in financial operations.
Real-life banking RPA case studies
1. Postbank, a prominent bank in Bulgaria, has embraced Robotic Process Automation (RPA) to streamline 20 loan administration processes. Among these processes was a seemingly straightforward task that required human employees to distribute received payments for credit card debts to the correct customers. Despite its apparent simplicity, this task involved various checks across multiple systems.
Before the implementation of RPA, seven employees had to dedicate four hours daily to complete this task. The custom RPA tool, built on the UiPath platform, performed the same task 2.5 times faster without errors, only requiring human intervention in 5% of cases. Postbank extended automation to other loan administration tasks, encompassing customer data collection, report generation, fee payment processing, and information retrieval from government services.
Benefits of RPA in Banking
RPA in Banking offers numerous benefits, some of them are:
Enhanced Efficiency
RPA streamlines banking operations by automating manual and time-consuming tasks. This results in a significant boost to operational efficiency, enabling banking professionals to focus on more strategic and value-added activities.
Error Reduction
Human errors can have serious consequences in banking. RPA eliminates the risk of errors in routine tasks, leading to increased accuracy in data entry, transaction processing, and compliance-related activities.
Cost Savings
Automation through RPA translates into cost savings for banks. By reducing the need for human intervention in repetitive tasks, banks can optimise resource allocation and achieve substantial cost reductions in the long run.
Increases Speed and Scalability
RPA operates at unprecedented speeds, completing tasks in a fraction of the time it would take a human. Moreover, it offers scalability, allowing banks to handle growing workloads without a proportional increase in staffing.
Improved Customer Experience
The efficiency gained through RPA contributes to a better customer experience. Faster processing times for transactions and quicker response to customer inquiries enhance overall satisfaction, building trust and loyalty.
Regulatory Compliance
The banking sector is highly regulated, and compliance is non-negotiable. RPA ensures that processes adhere to regulatory requirements, reducing the risk of non-compliance and associated penalties.
Data Security
Security is paramount in banking, and RPA provides a secure framework for automation. Access controls, encryption, and audit trails are implemented to safeguard sensitive information, mitigating the risk of data breaches.
24/7 Operations
Unlike human employees who have limitations, RPA bots operate 24/7 without breaks. This continuous operation ensures that critical tasks are completed promptly, contributing to an always-on banking environment.
The Future of RPA in Banking
The future of RPA in banking is expected to witness further expansion as the industry evolves. Anticipated developments involve integrating artificial intelligence (AI) and machine learning (ML) with RPA, thereby creating intelligent automation systems capable of handling complex decision-making processes.
Chatbots and virtual assistants powered by RPA are already transforming customer interactions. These bots can provide real-time responses to customer queries, execute transactions, and offer personalised recommendations, thereby enhancing the overall customer experience.
Exciting prospects include the implementation of end-to-end automation across various banking functions. From front-office tasks like customer engagement to back-office processes like risk management, RPA has the potential to revolutionise the entire banking value chain.
Conclusion
In conclusion, RPA in banking is not just a technological trend; it's a seismic shift that is reshaping the very fabric of how financial institutions operate.
Embracing RPA is no longer an option but a strategic imperative. Banks that understand and leverage the use of RPA gain a competitive edge by unlocking efficiency, reducing costs, and elevating customer satisfaction.
If you're ready to embark on a transformative journey, discover the possibilities of RPA in banking with our tailored solutions. Contact us to explore how RPA can revolutionise your operations, drive innovation, and position your bank as a leader in the rapidly evolving financial landscape.
Frequently Asked Questions (FAQs)
1.How RPA is used in banks?
RPA in Banking automates repetitive tasks such as data entry, account reconciliation, and compliance checks. Additionally, RPA is used to streamline customer onboarding processes, reduce human error, and improve operational efficiency within banking institutions. The technology can also assist with fraud detection and risk management, making it a valuable tool for maintaining security and compliance standards.
2. How to use AI in banking?
AI is used in banking to enhance efficiency, security, and customer experiences. It automates routine tasks like data entry and fraud detection, reducing operational costs. AI-driven chatbots provide 24/7 customer support.
3. What are the benefits of RPA?
The benefits of RPA include cost and time saving, increase ROI, eliminate human error, increase compliance, increase employee satisfaction and more.
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