Intelligent Robotic Process Automation and Its Uses in the Industry

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As mentioned above, intelligent RPA consists of artificial intelligence and machine learning. Hyperautomation is used to help organizations identify, review, and then automate many jobs and processes. Its goal is that artificial intelligence and RPA can work without human intervention. That means automating everything in an organization that can be automated. Hyperautomation explores business processes and can create bots for those processes. In this context, intelligent automation is part of hyperautomation.

According to Gartner, hyperautomation is among the top 10 technology trends, which is why it is necessary today.

Robotic Process Automation works on structuralized data. Structuralized data is code that search engines can read in a specific format. Not every data can be in a structured layout, so you must process this data. AI processes this data using technologies, making it understandable for RPA. In this context, technologies such as OCR (Optical Character Reading), NLP (Natural Language Processing), Computer Vision (CV), and process mining are used.

Machine Learning allows the robot to adapt by learning big data. It collects and analyzes computer data, resulting in a robot capable of making decisions. The more data, the higher the accuracy rate. An example is Google Maps, which collects many data points every day and provides the fastest route when a user wants to find the location of a place.

Deep learning is a machine learning method. It allows artificial training intelligence to predict outputs based on the data set. An artificial neural network like humans is used.

Natural Language Processing enables machines to interpret human language. Siri and Alexa are the best examples of this.

As a result, while RPA only provides automation of repetitive tasks, what you can do with artificial intelligence is limitless. In a process designed with VooDoo RPA, it is possible to type the mood of a customer’s e-mail on different lines in excel. A robot trained with big data can then classify a customer review positively or negatively and type it into an excel file.

There are numerous automation needs in the fields of healthcare, banking and finance, insurance, e-commerce and retail, and human resources. To automate more complex tasks, it is necessary to integrate IRPA with artificial intelligence technologies.

There are many tasks in the healthcare industry that need to be structured, complex, short, and error-free. IRPA is required in many hospital areas, from Human Resources (HR) department to supply chain management and administration jobs.

Natural language processing retrieves data from various sources using speech and image recognition and can be saved in a database for later use.

The appointment scheduling system requires many data, from a patient’s credentials to insurance numbers. With intelligent RPA, the process of collecting data from the patient can be automated and made error-free in seconds. Then, considering the patient’s health status, intelligent automation can estimate the time of the appointment period. According to the estimate, it writes an appointment at an interval convenient in the doctor’s calendar. The created appointment information can be forwarded to the patient and the doctor by e-mail. This whole process can take place within minutes.

Inventory management is a job that needs to be constantly checked to provide a good service. Stock status should be monitored regularly, and counting should be done. Smart RPA can integrate with vendors to track stock levels and place orders when necessary.

Thanks to Machine Learning, a robot with advanced decision-making ability can make a specific classification by analyzing various reports, patient histories, and other factors. This makes it easier for the doctor to make diagnosis decisions.

The banking and financial sector was one of the first to adapt to RPA. Due to data consistency, the rapid progress of transactions, and security, customer and employee satisfaction is ensured with Intelligent RPA.

In banking, processes such as account opening-closing, loan application, and card activation, which take time but are urgent for the customer, can be solved quickly with high security and speed.

KYC (Know Your Customer) includes the controls that need to be done for each customer. According to a study, banks spend $284 million annually on the KYC process. Banks have started to use RPA to reduce this cost and speed up the process.

Keeping customer data up to date is one of the essential elements for a bank. Keeping up-to-date data constantly with a workforce does not create an efficient process. Intelligent RPA can continuously provide up-to-date data.

Investment companies must follow possible market developments, but most companies make predictions through Excel spreadsheets. These forecasts include stock ratios, financial demands, long- and short-term revenue forecasts, etc. Manual estimates are often inaccurate, which significantly reduces productivity. Artificial intelligence technology can objectively predict future developments by taking advantage of past data.

Cyber fraud is an essential issue in the financial industry. Due to rapid technological developments, attacks are increasing day by day. Platforms such as ERP (Enterprise Resource Planning) are vulnerable to various software attacks. By protecting customer data, artificial intelligence also eliminates the damages that the security vulnerability may cause.

E-commerce is one of the sectors developing rapidly today and needs to keep up with technology. Communication with the customer is essential, and the customer must always be satisfied. With smart RPA, customer complaints can be eliminated by communicating with the customer 24/7. Stock levels can always be checked. In addition, fast shipment and package tracking are processes that can be automated with RPA.

E-commerce platforms that sell millions of products should ensure that the customer finds the product they are interested in in the easiest way. The product should be categorized so that the customer can easily find it. An RPA robot integrated with artificial intelligence can organize products according to customized rules.

RPA can perform the entire shipping and order tracking process with high security and speed. Manual order and invoice entries are automated. Answers the questions about the order from the customer in a short time. All data can be easily transmitted to supply chain partners. Inefficiency can be identified with data analytics capability.

The return process can be a nuisance for every e-commerce and retail industry. By automating this whole process, the process can be facilitated. These steps include sending a confirmation message to the customer when the return is received, never leaving the customer unanswered in this process with the help of the chatbot, keeping the inventory up-to-date, and refund-invoice transactions can be easily performed.

In e-commerce companies with many products, keeping product information up-to-date and adding new product listings is repetitive and time-consuming. Intelligent RPA pulls information from various designated data points and can enter it into the right areas.

Jobs that are automated using RPA include hiring, developing, remuneration, and many more HR activities.

A resume scan is a time-consuming process. Research shows that it takes three days to manage a single hiring process. With RPA automating the process, resumes can be collected, scanned, verified, and even compared the information to the relevant job request. Intelligent RPA can create an analysis by comparing the demands and applications in the job posting. This improves the quality of the recruitment process.

The new hire has new user accounts, an e-mail address, and some IT (Information Technology) requirements. Smart RPA does all these account opening processes and sends the necessary documents to the employer and the employee.

The monthly burgundy process is a rule-based process that requires much data. Delay in inaccurate or incomplete data or payments reduces the quality of service. As a result, automating reduces process time and error to almost zero.

Surveys and inspection reports are essential processes and require effort. It is necessary to create dashboards and keep them up to date constantly. Thanks to intelligent RPA, it is possible to generate automatic reports.

In companies with many employees in the corporate dimension, it is essential to get a record of leave days and time worked. By regularly checking this information, the RPA robot can notify when it encounters a problem.

One of the clients of an RPA company has installed an RPA robot to inspect physical mailboxes. The RPA robot combines with computer vision to send an e-mail to the relevant person when a package or letter falls into the mailbox. It is possible that this sample process can be applied anywhere.

For example, the claims process can be automated in the insurance industry. The RPA robot can extract the relevant data from the request and check the fraud status of the request. In addition, it detects damage from the vehicle’s image with computer vision to predict the damage.

Equinix, an American company specializing in internet connectivity and data centers, uses RPA with the integration of computer vision to automate accounts payable transactions. OCR technology is used to extract data from a PDF-based file. This way, the company can perform secure data extraction, increasing efficiency.

Since a bank needs to verify each document, the bank monitors the secure file transfer system to check for errors and non-compliance. If he encounters a problem, he asks the customer to send a new file. This process will be faster and more reliable like this.

VooDoo RPA products can analyze the sentiment of the comments in the e-commerce sector. When the machine-learning-trained robot pulls the necessary words from the site, it can classify a comment as positive or negative. After classification, it can send the data saved in the Excel file to the authorized person as an e-mail.

Finding the desired product in seconds rather than browsing hundreds of pages is very easy in an RPA robot. It is possible to find the product with the best price-performance by scanning it from many different sites.

For e-commerce, products can be classified by classifying images with machine learning. With the intelligent RPA robot, pictures can be classified and named.