Background and initial situation

A medium-sized company operating in the IT services industry had challenges in the area of finance and accounting. The finance department was often overloaded with routine requests for invoices, financial reports and budget analysis. This led to delays in processing requests and reduced efficiency in completing key financial tasks.

Aims of the project

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

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

Solution implementation

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

a) Needs analysis and planning:
  • Identification of the most frequent requests and tasks: By analyzing the request data, it was determined that questions about invoicing, accounting information and budget reports were the most common.
  • Defining the integration points: The IT department identified the relevant systems, including the accounting system (Xero) and the document management system.
b) Development and integration:
  • Creation of conversation workflows: Specific workflow scripts were created to handle frequently asked questions and requests. This included, for example, the provision of current invoices or financial reports.
  • Technical integration: The AI was seamlessly integrated into Xero and the document management system.
c) Training and knowledge database:
  • Data import and structuring: Historical data on financial inquiries was used to expand the AI’s 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: Invoicing request

  • Step 1: An employee makes a request for the latest invoice via the internal chat system.
    – Employee: “AI, please send me the latest invoice for customer XYZ.”
  • Step 2: The AI processes the request, searches the Xero system and retrieves the relevant information.
    – AI: “One moment please, I’ll check the database.”
  • Step 3: The AI finds the relevant invoice and sends a copy to the employee.
    – AI: “Here is the last invoice for customer XYZ. Date: 01.10.2023, 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 has been successfully sent to customer XYZ.”

Results and benefits

After implementing the AI, there were significant improvements in the finance department:

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

Conclusion

The integration of AI into the company’s finance and accounting process led to a significant increase in efficiency and satisfaction for both employees and internal customers. The automation of repetitive tasks has freed up valuable time that can now be used for strategic initiatives. Future enhancements to the implementation could include the implementation of further advanced features such as the automatic generation of financial reports or the integration of further financial systems.