Credit Cards Statements’ Automated Management

        Credit Cards Statements’ Automated Management

        Quick Facts

        Intetics developed an unattended RPA solution to leverage invoice data processing workflows

        The Client reported sufficient ROI enhancements among other business benefits

        Staffing received an opportunity to perform more sophisticated tasks due to the RPA adoption

        Objective

        Improve operational efficiency in financial transactions’ processing by its automated accumulation, categorization, and uploading of processed data to Zoho book.

        Challenge

        The Client’s main activities are aimed at providing personally developed software technologies able to speed up and simplify the process of buying products of interest to certain circles of consumers. Their focus lies in collaboration with the best global retailers, agencies, and technology partners and their mutual integration by means of proprietary featured products that can help evolve digital strategy and optimize it for success.

        The Client requested an efficient solution intended to increase the processing speed of credit card statements’ transactions and be able to assist the accountant with transactions prioritizing based on prepared categories.

        Intetics’ specialists also proposed to extend its functionality to the following operations and added 20% to the total efficiency:

        • Accumulation of processed transactions to improve the quality of future processing;
        • Automated requests to cardholders about additional transaction info

        Client’s core services are closely related to processing creditor invoices, month-end cost analysis, posting/recording payments, and payment/payroll processes’ management. After
        a thorough analysis, it was suggested to implement an RPA approach for this transaction –project-based instead of a software solution from scratch. Hence, they significantly required the RPA solution to automate their document processing workflow.

        Initially, the process flow included a stage of transactions’ categorization where each transaction was to be referred to as the right expense account.

        Among two types of such transactions they were the
        following:

        1. Transactions consisting of already processed before and already categorized based on historical data;
        2. Brand new transactions’ categorization
        3. In the second case, the team suggested on Google Search-based approach and comparison of results under the search based on keywords.

        Solution

        Being faced with this task, the team of two developers and a business analyst suggested to achieve up to 80% of categorization accuracy, where only 20% of transactions were meant to be worked out by a human.

        To implement it properly and on-time, the Agile approach was chosen to guarantee quick updates and step-by-step functionality testing, and the UiPath platform and Google Search as main technology instruments were also adopted.

        It was suggested for the process to convert pdf reports to CSV format instead of using online service to convert pdf to Excel and save as CSV files. Because the previous approach was not stable, excessive in the process and required a paid subscription, Read PDF Text, Replace, and Matches UiPath activities were used for this process instead.

        #1 Robot converts PDF report to plain text and then extracts transaction information using a set of regular expressions.

        #2 After the automation was implemented, up to 80% of unique new transactions were categorized automatically and 20% still processed by the accountant as exceptional cases because of low informative transaction descriptions.

        #3 Such a high level of speed and accuracy was achieved by the team using Google search service and a knowledge base on mapped pairs. The further categorization appeared to be possible due to the custom algorithm created based on the features mentioned above.

        With the help of an automation solution implemented by Intetics’ team, about 90% of manual work was shifted to the robot. Basically, new transactions were categorized automatically enabling to minimize errors, time, and offering the employees to focus on more revenue-centered activities.

        Benefits and Results

        • Intetics developed the first-generation Assisted RPA solution with the purpose to increase the accountant’s productivity by assigning up to 90% of the work to the Robot.
        • The automated process was cyclical in nature, thus being an ideal case for robotization. As a the result, the efficiency has been improved due to the processing accuracy, speed, stability, and saved an accountant’s working time.
        • Business benefits of this Intelligent Automation (IA) process were in:
          • Financial transaction process’s automation
          • Improved productivity of the Accounting team
          • Redeployment of accounting staffing resources to more judgment-intensive tasks
          • Elimination of human input errors

        Case Study

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