10 Intelligent Automation "industry-wise" use cases you should know....!

RPA has tremendously impacted many industries without a hint of doubt, but only RPA can’t be your savior. It needs AI to optimize its possibilities, and this combination is often called ‘Intelligent Process Automation.’


Intelligent Process Automation (IPA) systems can learn from complicated processes and make them more flexible. Companies and industries are deploying IPA across segments and achieving impactful results.


Intelligent Automation has dominated almost all the industries of the world today. There is no industry in the world today that does not use automation. There are various industries like banking, finance, manufacturing, transport, e-commerce, education, etc., that use IPA.


The below use cases can help you to understand how it can help your industry/process/functionality,



Manufacturing


Bill of Material (BOM) Processing


Bill of material is the document that contains each raw material, component, and instruction required to manufacture or repair a product. Any errors in BOM can lead to adverse chain impact on the remaining production cycle and result in a loss.


IPA can automate Bill of Material processing with the support of OCR and deep learning-based data extraction technologies.


Safety Measures automation


Manufacturing units have numerous safety gears and measures, by avoiding any measures can result in huge accidents. IPA can monitor these work practices through CCTV and can analyze real-time to generate automated reports on objects, people, and work practices in the production lines through AI (Facial recognition).


The safety ignored accidents can be reduced through machine learning and machine vision.


Furthermore, with Intelligent process automation, industries can monitor their energy costs and can also optimize their production hours.


Insurance


Digital Claim



Insurance companies receive numerous manual requests for claims, and it consumes more manual hours of the agents. The inconsistent processing, varying data formats, and changing regulations are huge hurdles for the agents to process the claims.


Unstructured data in forms can be extracted as structured data and be processed as claims based on pre-defined rules. And rules can be updated with regulatory changes, without any need for training, immediately ensuring compliance.


Banking


KYC Automation



Banks are mandating KYC (Know-your-customer) for enhanced banking and for more security purposes, but it takes a huge manual intervention to extract these details, as it also includes biometric data.


Biometric data can be captured and processed through NLP (Natural Language Processing) and Artificial Intelligence. The data capturing processes can be automated, resulting in zero error and no manual interventions.


Loan Processing


The loan processing requires many manual processes to be completed to verify the loan applicability, but without RPA, it may take weeks, even months to validate the data.


Complex business logic can be embedded in bots automating loan decisions and the manual processes that follow the decision.


Telecom


SIM Upgrade


Assigning a new SIM to a user. It could be due to a change of SIM format or a case of lost/stolen SIM.


The rules can be pre-defined in the system, which can save a lot of manual hours and the cost involved.


Also, companies are making use of sentiment analysis to analyze the feedback provided by the customers. This makes use of natural language processing to analyze texts and online surveys. Fraud Detection, which is the central role of machine learning in industries, is tailored for finding fraud merchants and frauds in wire-transfers.


Healthcare


Appointment Scheduling


The huge database of doctors/clinics for scheduling an appointment is a mundane task and can be very confusing and time-consuming.


The IPA bot schedules patient’ appointments based on diagnosis, doctor availability, location, and other variables, including financial statements and insurance information.


Improved patient care through Analytics


The data of patients should be put to use through analytics for providing a much more sophisticated user experience.


IPA bots collect various medical data and can analyze the patient data to third party healthcare analytics service for delivering an accurate diagnosis and improved patient care without restricting any confidentiality regulations.


Retail


Returns Processing


The traditional returning system requires the involvement of customer service agents, logistics partners,s and supply chain teams, which takes a lot of collaboration and accuracy. This might lead to inconsistencies and more manual hours.


Automating returns can improve customer satisfaction and reduce manual intervention. IPA bots can be used to automate manual returns processes such as checking customer purchase records from the system.


Supply chain and Inventory Management


The database requires a manual update of data on the low stock alert or high availability. These processes should be automated for reduced cost and time.


IPA bots can perform regular checks on these systems providing insights on key metrics like items with low stock levels or rapidly changing stock levels.

In the end, we conclude that Intelligent process Automation has created a vast impact on all applications. Several industries like banking, transport, e-commerce, healthcare, and many more are using automation to better their products.


IPA is a vast field, and therefore, its applications are also enormous and diverse. Industries need automation to move forward, and therefore, it is an essential aspect of all industries today. I hope you liked our article. If you have any questions related to Intelligent process Automation applications, ask freely through the mail given below. We will definitely get back to you.


For more details on the use cases or deployment, get in touch with our RPA expert at dave@digitalleaf.io

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