RPA Automation in Finance: Case Studies on Cash Flow Forecasting and Bank Reconciliation

Implementing Robotic Process Automation (RPA) in finance is becoming a crucial element of companies' growth strategies. Automating financial processes enables time savings, reduces operational costs, and increases the accuracy of forecasting and data verification. In this article, we present three case studies that illustrate how the implementation of RPA, using G1ANT.Studio as an example, brought tangible benefits to companies. We focus on automated cash flow forecasting, automatic bank integration, and automatic payment reminders, which significantly increased operational efficiency and improved financial management.
Case Study 1: Automated Cash Flow Forecasting

Background:
Company X, a manufacturing firm that has been operating for 15 years, employs approximately 500 people. The company is headquartered in its home country but also has several international branches.
Managing cash flows was a significant challenge for this company, particularly due to the diverse revenue streams and expenses associated with production and distribution.

Before automation, the cash flow forecasting process was manually performed using spreadsheets (Excel) and data imported from an ERP system (e.g., SAP) and accounting software (e.g., QuickBooks). This process required collaboration from several finance team members and frequent consultations with department managers. Unfortunately, this led to numerous errors due to manual data entry and resulted in forecasts often being outdated or inaccurate, making it difficult to manage liquidity effectively.

Problem:
  • Time-consuming: Manual cash flow forecasting took employees an average of 8 hours per week. It required synchronizing data from different sources and verifying it multiple times.
  • Risk of errors: Manual data entry and analysis led to frequent mistakes, which reduced the accuracy of forecasts and could lead to incorrect financial decisions.
  • Low flexibility: Updating forecasts was time-consuming and not done regularly, causing delays in responding to changing market conditions.
Solution:
The company decided to implement RPA using G1ANT.Studio to automate the cash flow forecasting process. With G1ANT.Studio, the company automated the entire process, from extracting data from the ERP and accounting systems, analyzing historical cash flow trends, to generating forecasts for upcoming periods (monthly and quarterly).
The software robots were integrated with the SAP ERP system and accounting software (e.g., QuickBooks).
Automation included:
  • Retrieving and processing data on revenues, expenses, and financial liabilities.
  • Analyzing financial trends based on historical data.
  • Creating cash flow forecasts that were updated daily, allowing real-time financial monitoring.
  • Automatically generating PDF reports and sending them to relevant departments.
Results:
  • Time savings: The process that previously took 8 hours a week was reduced to just 1 hour, saving 87.5% of work time. Instead of engaging multiple people in manual data entry and analysis, automation provided quick, accurate results ready for managerial review.
  • Increased forecast accuracy: By eliminating manual data entry errors, financial forecasts became 15% more accurate. This allowed the company to better manage its cash flows, directly impacting its ability to meet obligations on time.
  • Improved liquidity: Better cash flow forecasting improved liquidity by 12% in the first six months after automation. The company could respond more quickly to capital needs, avoiding costs associated with payment delays or short-term loans.
  • Reduced operational costs: Automating the cash flow forecasting process reduced the need for additional finance staff. The company estimated savings of around $25,000 annually due to reduced time spent on manual data entry and forecast verification.
  • Faster decision-making: Daily, automated forecast updates provided the company with real-time insight into its financial situation, allowing faster decisions on resource allocation or investments.
Automating cash flow forecasting with G1ANT.Studio provided Company X with significant operational and financial benefits. Improved forecast accuracy, reduced work time, and financial savings demonstrated the great potential of RPA in finance. In the case of Company X, automation not only increased operational efficiency but also improved financial risk management, directly impacting the company's stability and growth.

Case Study 2: Automatic Bank Integration and Bank Statement Processing

Background:
Company Y, in the retail sector, operates both online and offline across multiple markets. The company manages several bank accounts in different banks, making daily financial transaction management a challenge. Previously, the process involved manually logging into the banks' online systems to download bank statements, which were then processed and reconciled in accounting software (e.g., Xero). This process required a full-time employee, and errors or delays in posting led to liquidity management problems.

Problem:
  • Manual data processing: Employees had to log in daily to multiple banking systems (e.g., HSBC, Chase) to download bank statements in different formats (CSV, XML, PDF). These statements were then manually entered into the accounting system.
  • Processing errors: Manual data entry often resulted in mistakes, causing accounting discrepancies and additional costs to correct them.
  • Time-consuming: Manually processing bank integrations took around 4 hours a day, equating to 20 hours a week dedicated to bank statement management.
  • Low scalability: As the number of bank accounts and financial transactions grew, the workload for the finance team increased, causing delays in accounting.
Solution:
Company Y automated the processes related to bank integration and statement processing, selecting G1ANT.Studio as the RPA tool for this task. The goal was to automate the entire process, from downloading statements from banks to processing and reconciling them in the accounting system.

Automated process included:
  • Automatically logging into banking systems (e.g., HSBC, Chase) through G1ANT.Studio robots.
  • Downloading bank statements in various formats (CSV, XML) and directly integrating them into the accounting system (e.g., Xero).
  • Automatically processing the statements and posting transactions to the appropriate accounts in accounting.
  • Generating daily transaction reports and sending them to the finance department.
Results:
  • Complete automation: The entire process of downloading and processing bank statements was automated, eliminating the need for manual logins and data entry into the accounting system. What previously took 4 hours a day now took just 30 minutes, all done automatically.
  • Cost reduction: Prior to automation, the company had to hire an additional employee to manage bank statements. After implementing G1ANT.Studio, the company saved approximately $7,500 annually in operational costs.
  • Increased accuracy: Automation eliminated the risk of errors from manual data entry. Bank statement processing achieved 98% accuracy, allowing the company to avoid accounting discrepancies and additional costs related to fixing errors.
  • Faster financial management: With automation, the company had daily visibility of its current financial transactions. Automated reports generated by G1ANT.Studio provided a complete picture of the financial situation, allowing faster decisions on liquidity management and expense planning.
  • Improved scalability: Automation allowed the company to handle the growing number of bank accounts and transactions without increasing staffing in the finance department.
Automating bank integration and statement processing with G1ANT.Studio brought Company Y clear benefits, including cost savings, increased operational efficiency, and improved process accuracy. This key process automation allowed the company not only to save time and resources but also to manage its financial liquidity better, contributing to financial stability and growth.

Case Study 3: Automatic Payment Reminders and Financial Obligations

Background:
Company Z, involved in large construction projects, worked with numerous material suppliers and subcontractors. These projects had long timelines, meaning the company had to manage many invoices and financial obligations over extended periods. Unfortunately, manual management of payment due dates led to frequent delays, as well as penalties that further burdened the company financially. Moreover, the company’s reputation with suppliers was damaged, making it harder to negotiate better credit terms and discounts.

Problem:
  • Payment delays: The lack of systematic reminders for payment due dates meant invoices were often paid late. The company incurred penalties of up to 5% of overdue invoices.
  • Costly interest and penalties: In the previous year, the company paid over $12,000 in penalties for late payments, negatively impacting its operational margin.
  • Difficulty managing obligations: The company struggled to control payments, leading to liquidity shortages at critical moments for ongoing projects.
  • Inefficiency: Employees had to manually track payment due dates, search the accounting system, and remind different departments about obligations. This was time-consuming and inefficient.
Solution:
The company decided to implement an automated payment reminder system using G1ANT.Studio. The goal of the automation was to improve control over payments and ensure that all invoices were paid on time without employees having to monitor financial obligations manually.

The automated process included:
  • Integration with the invoicing system (e.g., NetSuite), which collected all data related to the company’s invoices and financial obligations.
  • Automatically generating reminders for upcoming payment due dates based on data in the accounting system.
  • Sending email and SMS notifications to the appropriate individuals (finance department, project managers) to remind them of approaching deadlines.
  • Monitoring whether payments were made and sending additional reminders in case of no response.
Results:
  • 85% reduction in payment delays: Before automation, the company regularly delayed payments, resulting in penalties. After implementing RPA, the number of delayed payments decreased by 85%, significantly improving relations with suppliers and business partners.
  • $12,000 annual savings: Automated reminders eliminated the financial penalties the company regularly incurred for late payments. In the first year of implementation, $12,000 was saved on interest and penalty costs.
  • Optimized cash flow: Automatic payment reminders allowed the company to manage cash flow more effectively. On-time payments reduced the risk of project delays due to financial shortages, which had previously posed a significant operational challenge.
  • Increased work efficiency: Manual monitoring of obligations and payment reminders was time-consuming and inefficient. With automation, employees could focus on more strategic tasks, while G1ANT.Studio handled the entire operational side of payment due date monitoring.
  • Improved company reputation: Thanks to on-time payments, the company rebuilt its reputation with suppliers. This led to better trading terms, such as longer payment terms or better discounts.
Automatic payment reminders via G1ANT.Studio significantly improved the efficiency of managing Company Z’s financial obligations. The reduction in delays, financial savings, and improved supplier relationships are just a few of the benefits of implementing RPA. This solution allowed the company to focus on delivering strategic construction projects without worrying about financial risks caused by payment delays.

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