Background and context

A medium-sized company in the IT services industry was facing challenges in its finance and accounting department. The finance department was often overwhelmed with routine requests for invoices, financial reports and budget analysis. This resulted in delays in processing requests and reduced efficiency in completing key financial tasks.

Project objectives

The main objective of the project was to increase the efficiency of the finance department by automating routine requests and improving the accuracy and availability of financial information. Specific objectives included:

  • Reduce the average response time to inquiries.
  • Increase employee satisfaction by reducing repetitive tasks.
  • Improve the transparency and accuracy of financial data.
  • Ensure compliance with financial regulations and internal policies.

Solution Implementation

To achieve these goals, the API was integrated into the company’s existing internal systems. The implementation followed a clearly thought-out plan:

a) Analysis of the needs and planning:
  • Identify the most common requests and tasks: By analyzing the request data, it was determined that questions about invoicing, accounting information, and budget reports were the most common.
  • Determine the integration points: The IT department identified the relevant systems, including the accounting system (Xero) and the document management system.
b) Development and integration:
  • Creating the conversation workflows: Specific workflow scripts were created to handle frequently asked questions and requests. This included, for example, providing current invoices or financial reports.
  • Technical integration: The system was seamlessly integrated with Xero and the document management system.
c) Training and knowledge database:
  • Data import and structuring: Historical data on financial queries was used to expand the ChatGPT API knowledge base.
  • Regular updates: Regular updates and maintenance of the knowledge base were scheduled to ensure the accuracy and availability of the financial information provided.

Application example and process scenario

Scenario: Invoice request

  • Step 1: An employee makes a request for the most recent invoice via the internal chat system.
    – Employee: “Please send me the latest invoice for customer XYZ.”
  • Step 2: The API processes the request, searches the Xero system and retrieves the relevant information.
    – AI: “One moment please, I’m checking the database.”
  • Step 3: The API finds the relevant invoice and sends a copy to the employee.
    – AI: “Here is the last invoice for customer XYZ. Date: 10/01/2023, amount: €5000. Would you like to send this invoice by email?”
  • Step 4: The employee confirms and the invoice is automatically sent to the customer.
    – Employee: “Yes, please send the invoice.”
    – AI: “The invoice was successfully sent to customer XYZ.”

Results and benefits

After implementation, significant improvements were seen in the finance department:

  • Reduced response times: The average processing time for financial inquiries decreased by 60%.
  • Increased efficiency: Employees were able to focus on more complex financial analyses and strategic tasks.
  • Employee satisfaction: Reducing the burden of repetitive tasks led to higher job satisfaction.
  • Data accuracy: Automated data processing significantly reduced the error rate.

Conclusion

Integrating AI into the company’s finance and accounting process resulted in a significant increase in efficiency and satisfaction for both employees and internal customers. By automating repetitive tasks, valuable time was freed up that can now be used for strategic initiatives. Future extensions of the implementation could include implementing other advanced features such as automatic generation of financial reports or integrating other financial systems.