In today’s digital era, many industries rely on automated systems. This is mainly caused by technological developments that build faster corporate infrastructures and higher customer expectations.
Automated systems are faster, more reliable, and more efficient than conventional workforce structures. The most commonly-used automation technology, RPA (Robotic Process Automation), is easily adopted by many industries. Thanks to machine learning and AI, the adoption rates are becoming faster and faster.
Almost every industry relies on , which creates new use cases for the technology every day according to Gartner
In this article, we will analyze and its use cases to show that supported automation systems can be used in various sectors, not just in the software development sector. So, let’s start with the definition of it.
First Things; What is RPA?
Robotic process automation (RPA) is a software technology that makes it easy to build, deploy, and manage software robots that perform the tasks performed by employees. Briefly, allows that industries to automate tasks across various systems. A business that implements that can automate its entire repetitive workflow, infrastructure, and other backend processes, which are mostly labor-intensive and time-consuming.
Thanks to its ever-growing ecosystem and customizable nature, it has many use cases among countless industries.
Telecommunication companies should be fast, up-to-date, and spend fewer resources on services due to the nature of their work system and the highly-competitive environment. However, in this digital era, rapidly developing technology and changing society force telecommunication companies’ resources and push them to their limits. They can use RPA to reduce costs, improve productivity, and provide better customer service to prevent outsourcing their company. With RPA, telecommunication companies can develop first-call bots and solve a lot of problems without any real employee interaction. Also, these bots can work 7/24, reducing costs and offering better customer service.
In the banking sector, RPA may save labour and operational costs. Automated account management processes can reduce the real employee workforce and human error. In traditional banking, these operations require a lot of data processes done by the human force. In the data processing process, human-related errors can emerge, and they affect the customer experience badly. RPA prevents these errors with advanced data processing features supported by ML and AI.
Moreover, RPA carries out these operations faster than real employees, thus enabling more customers to join the bank. In addition to that, RPA could be useful in fraud detection since it is supported by advanced ML and AI. With RPA, banks don’t need to worry about fraud cases and securely make transactions with their customers, which also increases customer trust.
Like in the banking and telecommunication sectors, hospitals also do a lot of data processing tasks, such as maintaining medical records of patients, entry processing, and claim processing. These data processing tasks could decrease the efficiency of the healthcare industry if they are not performed and updated regularly.
On the healthcare front, RPA can create wonders when combined with AI. Since it has advanced and accurate analysis systems, it can make more accurate predictions about data according to patients’ symptoms.
However, these tasks require a lot of human workforce. If an RPA-supported automated system is used in these tasks, the healthcare industry can reduce costs and provide better customer service.
With RPA, the finance sector can use the automated task for various tasks such as managing customer accounts, creating various reports, migrating data between accounts, and updating loan and mortgage data. On the other hand, finance companies can develop trading bots for solving the problems of customers in real-time. These bots can solve problems by themselves, gather data about customer needs and send critical errors to developers. So, RPA increases the speed of transactions and customer experience while reducing costs in the finance industry, which makes it mandatory for the finance industry.
RPA can help streamline the process of recruitment considerably. Almost %80 of the recruitment process consists of repeated data analysis tasks such as organising applicants’ data, deleting irrelevant data, categorising applicants who have a chance to be taken, and more. These tasks are seemingly easy to do, but they take a lot of time when performed by the human workforce.
With RPA, companies can use bots to do these tasks and decrease the amount of workload from real employees. Thanks to these RPA-supported bots, companies can call more people to interview and increase the chance of finding the correct employee.
In today’s digital era, customers want fast and correct responses. To catch the times, companies take advantage of RPA and develop customer service bots to give faster, better, and errorless service. Customer service tasks are low-level and require little skill to do. Therefore these skills can be done by bots easily. Using an RPA-supported bot allows customer needs to be fulfilled faster, less costly, and without error, improving the customer experience.
7- Data Collection & Analysis
The data analysis part is the most significant part of all sectors. Without data, most of the sectors can’t develop anything or provide any service. Therefore, a lot of sectors invest in data analysis teams, apps, and platforms to get the most advanced data analysis. However, this process is very costly for most companies because of the high maintenance cost and time needed. RPA contains ML and AI technologies; therefore, it can analyse any type of data faster than apps and humans. RPA obtains data from different data types, such as handwriting, CSV, and image recognition. Therefore, with RPA, companies increase their data processing power and work more efficiently.
In the insurance sector, automated systems are critical since most tasks are repetitive. These repeated tasks decrease the company’s efficiency and may cause the loss of future customers. Therefore, using RPA in insurance can increase the efficiency and success of insurance companies. They can use RPA in processing claims and form registration processes. RPA-supported bots can do these tasks much faster than employees and increase customer satisfaction. So, using RPA in insurance companies provides a better customer experience and increases the company’s profit.
Meet Autom Mate
RPA is very powerful, but the real magic happens when it is combined with AI and ML. As a company that’s obsessed with automation technologies, we brought RPA one step closer to the future with AI and ML.
With Autom Mate’s drag-and-drop, web-based interface, almost every branch in a company can leverage the latest automation technologies. The best part is that Autom Mate’s marketplace contains hundreds of ready-to-use, proven-to-work automation flows.
Autom Mate aims to create an autonomous system for all processes in business tasks. In short, Autom Mate provides an automation robotics solution to business processes to increase the efficiency, success, and speed of the company with fewer costs. See how Autom Mate integrates and automates many business processes on our website.