What is RPA and Its Use Cases in Various Industries

Today there is much talk about RPA and bots. RPA is a technology for business processes automation with the help of bots. RPA bots learn what people do to solve working tasks and replicate those actions, which allows delegating monotonous repetitive work to bots.

Overall, RPA helps companies increase efficiency by streamlining processes, cutting down the expenses on routine tasks, accelerating business processes, decreasing the number of mistakes, eliminating the influence of the human factor, and saving employees’ time for more interesting and creative tasks. Along with the mentioned advantages, the RPA is also scalable, flexible, and can easily interact with different systems via integrations and screen scraping.

In this article, we take a closer look at what RPA is, what it means for various businesses, and how to easily implement RPA solutions.

What is Robotic Process Automation (RPA)?

Robotic Process Automation (RPA), or robotic process automation, is a technology for automating business processes using programmable software robots, also known as bots. The function of these bots is to collect information about the actions of employees on the computer and then analyse this data to find the best possible ways to automate work processes.

The term “robot” was coined by Isaac Asimov, one of the most famous science fiction writers, in 1942. For a long time this area was part of the unreal world, but later robotics has become a serious scientific discipline.

One of the possible functions of the robots is RPA. The history of Robotic Process Automation began in the 2000s. Back then, the software robots were applied in the social media industry, where they served as digital workers. Other technologies such as AI and screen scraping also spread at the time.

In everyday life we ​​often interact with robots such as chatbots. For online orders, the robots are our tireless helpers, located behind a front-end interface.

Today, examples of RPA are automated mail dispatch or programmed post placement – these options are now available to almost every Internet user.

Here are just several ideas on how RPA is utilized in different industries:

Banking industry

• Automatic report generation
• Customer onboarding and service
• Credit card processing
• KYC and anti-money laundering
• Account opening and closing
• Mortgage lending
• Loan processing

Financial industry

• verification acts automation
• tracking the occurrence of overdue receivables and notifying counterparties
• creation and distribution of reports
• data transfer between different information systems

Sales

• creation, confirmation, and correction of the customers’ orders
• stock check
• sending confirmation letters to the customers

HR

• application and documents processing
• searching for candidates online
• filling in timesheets
• sending notifications

What Benefits RPA Brings To Businesses?

RPA is particularly important for different businesses, as it can help them automate a significant part of their daily work while optimising business processes and free employees from tiresome routine work.

Significant benefits of RPA for businesses include:

• the optimization of processes
• Increased operational efficiency
• freeing employees from routine tasks
• the reduction of costs
• the rationalisation of data processing
• the acceleration of the services
• a better customer experience

What Are The Typical Functions RPA Robots do?

Typical tasks of Robotic Process Automation are the processing of online orders and inquiries, the maintenance of customer data or the updating of notifications, the implementation of data transfers, the administration of master data and billing.

Here is the list of daily tasks that hardly require human resources to complete today:

• Filling out forms and applications
• Creation of reports
• Processing of data from different sources performing calculations
• Logging in and operating electronic systems
• Processing of data from the Internet
• Copy, paste, and structure the data
• Opening and sorting of e-mails and processing of attachments
• Processing of log files
• Data maintenance in the ERP and CRM system
• Execute if-then commands
• Accessing social networks and websites
• Ticket processing and dispatching

Now let’s talk about the process of implementing RPA on the way to total workflow automation. Here we share our experience on it.

The RPA Implementation Process

Step 1: Data Gathering

The most important steps of process automation are data gathering and data analysis. The quality of repeated processes detection and accuracy of this job depends on how big the volume of your data gathered is, how it is encompassing the subject area, and how deeply you perform analysis. Data gathering can be done by a specialist by diving into the subject area and finding patterns of user behavior. But when it comes to multiple numbers of working places (10 computers or more) time costs begin to prevail. And here automation of data gathering comes into play. We created computer utility the main target of which is to run smoothly, gather all key metrics, and store them into the hard drive. It is run by a specialist at a specific time period when computer activity must be captured. For the grace of security, it doesn’t transfer gathered data to remote servers. Our approach is to keep data safe and anonymized.

Step 2: Data Analysis

After data has been gathered it’s time for a solid and accurate data analysis. Let’s explain how we do it by details and by what means.

1. The first goal is to determine activity timeframes. It can be done by a quick scan of the logs gathered together by examining the description operators provide. By doing that we cut data in big data activity portions on the first iteration.

2. After that these portions are compared with the help of machine learning techniques to get a set of patterns with a similarity map. In short, we define unique patterns both as big ones and small ones. Small patterns can be a component part of complex ones. Also, the similarity probabilities created for all patterns.

3. The next step is building visualization based on data from the previous point. This visualization helps to identify all the processes; to find the percent of similarities, differences between analogs; to setup what processes need to be automated with higher priority.

Data analysis helps to identify and set up priorities. It consults the customer if unusual rare patterns can be normalized to the patterns with bigger similarities. In this case, a high percentage of such patterns would be as automated as possible.

Automated data analysis solution is done on Python and uses the following data scientific libraries:

• Numpy and Pandas for manipulating data arrays;
• Difflib.SequenceMatcher for finding similarities;
• Sklearn for building machine learning models to help on the structuring of data;
• Seaborn for visualization of statistical data

Step 3: Automation

The most fundamental unit of automation is a bot. Robots can be run from employees’ desktops or from the cloud. Here are their key features:

Integrations

They are necessary for bot to work with your enterprise applications. It is also possible for the bot to screen scrape and still perform tasks. However, it is more reliable to have app integration as screen scraping tends to have a higher probability of causing errors. Most bots in the market work with legacy applications (though coverage depends from vendor to vendor), web applications, desktop applications and other major enterprise software including SAP, Citrix, Java and mainframe applications.

Programming Interfaces

They are required because bots need to be programmed. RPA programming is relatively simple compared to other types of programming and there are code-free ways to program RPA bots.

There are also orchestration modules that facilitate the management of bots and processes. It allows you to start/stop or schedule bots and analyze bot activity. Orchestrators highlight issues that bots encounter and provide a dashboard for the processes that are managed by RPA.

Step 4: Result

RPA bots can use the operating system applications like a human user. RPA is too flexible for us to
provide a full list of bot actions but here are some of the main things bots can do:

Launching and using various applications including

• Opening emails and attachments
• Logging into applications
• Moving files and folders

Integrating with enterprise tools by 

• Connecting to system APIs
• Reading and writing to databases

Augmenting your database by scraping data from the web including social media

Data processing

• Following logical rules such as “if/then” rules
• Making calculations
• Extracting data from documents
• Inputting data to forms
• Extracting and reformatting data into reports or dashboards
• Merging data from multiple sources
• Copying and pasting data

Bots can do these functions on virtualization solutions like Citrix or on the Windows environment. Most vendors do not support other OS environments like Mac OS or Linux. This is because most office work is conducted on PCs.

Conclusion

In the near future, it is possible that RPA technologies will soon show virtually limitless potential. In combination with Big Data and AI technologies, the adaptive robots can serve as reliable partners in decision-making. In the coming years they will certainly be further developed so that they can be used for various new areas of application. If you are looking for a reliable AI development company, SCAND can offer many partnership opportunities from IT outsourcing to the dedicated teams for developing the best RPA solutions.

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