The Quick Wins for Robotic Process Automation
– Definition and Use Case examples

Processes that are classified as The Quick Wins for Robotic Process Automation

By Arnold Kinzel
Consultant | Advisory

Processes that are classified as the quick wins for RPA

Oct 28, 2019 | Frankfurt, Germany

What are Quick Wins? 

RPA solutions which are implemented fast and swiftly generate returns are referred to as Quick Wins. They bear low complexity yet still high reward potential. Low complexity automation projects can be implemented easily and do not need much customization afterwards. Some medium-complexity projects can still be defined as Quick Wins where data transfers between applications are required or they run on a Citrix environment.[1]

[1]Source: UiPath Academy, Business Analyst Training

With respect to the process assessment matrix illustrated above, quick wins can either be of low or medium complexity. If their complexity is low, benefits may be of medium size while a medium complexity process must result in high benefits to be considered a Quick Win for automation prioritization. Development will usually take between 1 to 2 weeks. Below are two Use Cases to illustrate Quick Win automation projects. While Invoice Processing is rather straight forward, the Know Your Customer (KYC) process does include more complex parts, however, can be separated into different procedures where Quick Wins can more easily be identified. 

Invoice Processing

This is one of the most common ways to generate quick wins using RPA in finance.

  • The robot extracts the required invoices from an email or folder.
  • It then reads out the necessary information from the files and updates the information in the ERP system.
  • It then verifies the details using information from databases e.g. vendor information. 
  • Finally, the system confirms the successful invoice processing.

KYC Process Automation

Banking institutions often must follow specific regulatory constraints for their business. The KYC process is one such example. It poses a strenuous process for banks and in case the requirements are not met by the deadline, the customer must be off-boarded. Besides the tight deadlines, it is also costly – according to Thomas Reuter, the average bank spends about $52 million per year on KYC compliance. 

However, many activities performed in a KYC can be automated. These include: 

Setting up customer data

Customer data that is entered manually from scanned documents is automatically entered into customer relationship management (CRM) systems e.g. by OCR technology.

Collecting and validated information 

During the onboarding process (and then again in regular intervals), data must be obtained from the customer which comes in paper form or digitally as PDF. This information can be processed by a robot and consolidated. In some cases, even validation is possible by accessing databases and extracting the required data.

Data consolidation

Information that is entered into separate systems e.g. savings account, brokerage, etc. can be compiled into one to provide a comprehensive overview. 


An integrated AI – RPA solution can screen for negative news online that would result in a disqualification of the customer. 

Read: Process Assessment Matrix

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