Retail Use Case: Daily Sales Reconciliation

Use Case: Daily Sales Reconciliation

Function: Finance

Industry: Retail

Challenge:

The client processes substantial volumes of cash, ACH and credit card transactions across multiple locations every day and the management team needs to interpret these transactions in order to deliver real-time analysis of the organization’s financial performance.

Journal entries for gift card transactions and credit card fee allocations often needed manual processing and spreadsheets were manually passed around for approval and review before posting resulting in a process that is time consuming for the team.

The finance department was receiving sales reconciliation documents from stores on multiple days of the week, either by courier service for shops outside of Riyadh or collected daily for the stores for those in Riyadh and submitted to finance. This was causing significant challenges around visibility and accountability in the financial close process.

Solution:

We implemented RPA bots to automate the existing processes, replacing manual spreadsheet-driven processes and automate account reconciliations, journal entries, transaction matching, task management and variance analysis.

The bots increased efficiency, without disrupting legacy systems and automated and standardize the entire reconciliation process. The bots were able to drive accuracy in the financial close with embedded controls and provide accountants with a streamlined method to verify their balance sheets through the following process:

  • Stores send cash data in pre-defined format through email
  • The bot downloads credit/debit/AmEx transaction data from Gidea portal
  • The bot logs into Outlook and downloads cash data
  • The bot posts the data by store and terminal

Soft Benefits:

  1. Instead of completing period-end accounting activities in a few days, work is performed in smaller batches. This means accurate information is always available and there’s more time to review, reducing risk of fraud or restatement.
  2. The management team can gain clear visibility into business data across multiple currencies in real time.
  3. The finance team can spend less time on transactional tasks and instead provide value-added services, interpreting the financial data to improve overall business performance.
  4. The bots can detect and correct errors to ensure financial statement accuracy, reducing the risk of accounting irregularities.

Realized Hard Benefits

  1. Volume of Transactions – 1Million+ per year
  2. Number of hours saved – 5000+ per year
  3. Value Saved – 1Million+ SAR per year