Robotic Process Automation (RPA), Artificial Intelligence (AI) and Machine Learning (ML) are distinct yet overlapping technologies that can work in conjunction or independently to be the most effective in achieving a resolution.
This would be best explained using an example.
Let’s consider a loan company that uses a form of KYC scanning for documents to verify the identity of the people applying for loans.
RPA will scan the documents and pick up the information from the fields and process it into columns depending on the type of document scanned such as a driving licence or bank statement.
Machine learning will work with identifying the type of documents and based on the data points that it has learnt from considering the types and variations, will trigger the RPA process to follow the path required to do the task.
AI would be learning the information provided over time with a portion of it using reason and self-correction along the way and predict that people that provided a bank statement with larger transactions and from a particular neighbourhood would be most liable to pay back effectively on their mortgages.
Considering the example above, Ai and ML can be used in multiple scenarios in various combinations across industries to ensure the processes that require RPA can be more effective with a combination of RPA + AI or RPA+ ML or an amalgamation of all the three in capacities which can be the most productive.
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