From business users to end consumers, automation technologies have become integral to our everyday lives. Be it in booking a cab, ordering a pizza, or shopping online for anything from essential groceries to sophisticated gadgets, we do it with a click of a button.
In the automation world, something that is gaining momentum, especially in the new normal is robotic process automation, also called, RPA. RPA is the use of software bots that mimic human behavior to perform tasks without manual intervention. Examples of RPA could be processing orders on e-commerce websites, categorizing customer service complaints, or routing them to the right representative,
What is RPA in business?
Robotic process automation in business uses rule-based software to automate simple tasks. RPA can take up huge volumes of tasks, free up human resources and improve speed and efficiency. These business processes could be anything like data transfer, payroll processing, website scraping, processing on orders for online business, handling simple customer queries, and so on.
Below, let’s look at the applications of robotic process automation services in different industries:
Robotic process automation in banking
Banking is one such industry that has been growing significantly over the past few years. Especially post the pandemic, when digital innovation is no longer seen as a differentiator but an imperative, owing to the convenience and new entrants, banks have started adopting technologies for increased customer experience and operational efficiency. RPA in banking can help banks in several ways. For example, customer service is at the heart of the banking industry. Banks may have to deal with various customer-facing processes such as loan applications, account opening, debit/credit requests, and so on. A simple chatbot can processes all such rule-based transactions and free up the representatives to focus on other critical tasks.
A chatbot infused with capabilities like AI (artificial intelligence), NLP (natural language processing), and ML (machine learning) can understand questions in natural human language and can take decisions based on historical conversations when trained on ML models.
Next on the list are fraud detection and KYC, which are one of the most critical processes. According to Thomson Reuters, banks spend a staggering US$ 384 million per year on KYC process compliance. In a traditional environment, the representatives upload the customer information onto the CRM manually, extract the data and may feed them into another software to verify the identity proofs against government records. These data should also be regularly verified and updated from time to time. The entire process involves many paper-based steps and consumes a whole lot of time, though it may look simpler. Instead, RPA can simplify the process. Given the heightened regulatory scrutiny and the increase in due diligence and regulations for anti-money laundering, financial institutions, and banks can embrace RPA technologies. RPA can automatically gather and upload customer information from various sources including structured and unstructured data, validate the customer information, perform risk assessments, regularly monitor the data collection, and flag any suspicious accounts or profiles instantly.
Robotic process automation in finance and accounting
Just like banks, robotic process automation services are being availed increasingly by a large number of finance and accounting firms. Reports indicate that over 78 percent of companies are already adopting RPA whereas an additional 16 percent are planning to adopt it over the next 3-4 years. In finance, there are many use cases that are potential candidates for RPA software. For instance, purchase order processing, financial reporting, invoice processing, auditing, procure to pay, risk assessment, payroll processing, accounts receivable, expense reporting, and the opportunities don’t end here.
Purchase order processing: RPA bots can create a purchase request in the ERP system, collate vendor information from different sources, manage inventory, automate the approval workflow. The system can be programmed to route the purchase orders to the appropriate approver and send reminders if there is any delay. RPA can also generate reports on purchase orders, including information such as order volume, vendor performance, and delivery times. This information can be used to identify areas for improvement in the purchase order process. Overall, RPA can streamline the process, reduce errors and improve the efficiency of the entire process.
Accounts payable: According to studies, automation in finance departments can save approximately 30-40 percent of a full-time employee’s day. In this process, the RPA bot can help organizations get rid of mundane, time-consuming tasks and provide employees more time to focus on other value-added activities. The accounts payable (AP) team may receive invoices via different routes and they may have to be approved by the finance personnel. In an RPA-enabled system, the bot can extract the details and auto-route the bills, match the invoices with their corresponding purchase orders and receipts, automate the payment processing on time, and manage vendor information. The bot communicates with the vendors regarding the payment status. Thus, RPA bots contribute to creating a smooth, automated end-to-end process that reduces friction in supplier relationships. RPA brings in increased transparency and visibility.
Other important use cases for RPA in finance include ledger, compliance, financial reporting, compliance, account reconciliation, and more.
Robotic process automation in healthcare
Automation technologies are becoming a great booster tonic for the healthcare industry, which is reviving with several innovations. There is a big uptick in the number of patients looking for digital support. To cater to such patients and provide them with a satisfying experience, RPA can be the perfect fit. Robotic process automation in the healthcare industry can be used to automate a wide range of administrative and clinical processes. Some examples include:
Patient scheduling and medical records: Clinical staff may no longer need to manually enter and verify patient data, and manage medical records. According to studies, the industry collectively spends $2.1 billion on error-prone manual data management. RPA can automate data entry in a centralized database management system. It ensures that electronic records adhere to privacy protocols. Next, RPA bots can automatically set up appointments based on the patient’s relevant data such as symptoms, doctor, location, time, etc. This could greatly reduce errors and free up staff time for focusing on critical tasks.
Revenue cycle management: RPA can automate revenue cycle management tasks, including coding, billing, claims denial management, and accounts receivable management. In all these tasks, RPA improves efficiency and reduces the risk of errors. All the back-office responsibilities like health plan enrollment, expensie reporting, claims processing, claims follow-ups, and so on could be automated with RPA.
Final thoughts
The future of RPA looks promising and is expected to evolve to become more intelligent, efficient, flexible and secure. It could evolve to include process discovery which will use data analytics and machine learning algorithms to identify rule-based processes. Similarly when combined with intelligent automation technologies such as machine learning, artificial intelligence, and natural language processing, RPA can handle more complex tasks that require cognitive abilities, such as decision making and problem solving.
