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From Days to Minutes: How Agentic AI Revolutionized Retail Reconciliation

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A national retail chain was facing serious bottlenecks in its month-end financial closing process. With millions of transactions flowing in from POS systems, supplier invoices, returns, and bank statements, the reconciliation team was buried under spreadsheets, manual checks, and data inconsistencies. Despite investing in ERP and legacy automation tools, the system lacked the agility to deal with unstructured documents, frequent mismatches, and human dependencies, leading to delayed reporting, compliance risks, and operational inefficiencies. They needed a solution that could not only automate but also intelligently operate, learn, and adapt just like a human finance analyst.

The Challenge: Retail Reconciliation at Scale

In the retail sector, reconciliation requires matching massive volumes of transactions across multiple systems — including POS, ERP, supplier invoices, and bank statements. The retail chain faced growing challenges in ensuring accuracy, speed, and transparency across its financial operations.

Key Pain Points Included:

  • Delayed Month-End Closures:
    Financial closing cycles often took 7–10 days, causing reporting delays and impacting decision-making.

  • Inconsistent Data Formats:
    Varying document structures across invoices, POS data, and banking records made automated matching difficult.

  • Manual Exception Handling:
    Staff spent hours manually investigating mismatches and exceptions, increasing workload and error probability.

  • Transaction Discrepancies:
    Frequent variations due to returns, discounts, chargebacks, and multi-channel orders created reconciliation backlogs.

  • Lack of Real-Time Visibility:
    The absence of an integrated reconciliation dashboard resulted in poor visibility, audit delays, and limited compliance readiness.

Amantra Solution: Agentic AI for Autonomous Reconciliation

To overcome reconciliation delays and data mismatches, the retail chain implemented Amantra’s Agentic AI Platform, introducing an autonomous digital finance operator that transformed how transactions were validated and reconciled.
This was not just automation; it was intelligence in action.

How Amantra Agents Transformed the Process:

  • LLM-Powered Intelligent Document Processing (IDP):
    Amantra agents used Large Language Model–driven IDP to extract, classify, and normalize data from invoices, bank statements, POS reports, and supplier records, regardless of format or structure.
  • Autonomous Matching Across Systems:
    The system automatically matched entries across multiple platforms, including SAP, Oracle ERP, and retail POS systems — eliminating manual cross-verification.
  • Real-Time Exception Handling:
    For unmatched or irregular entries, autonomous agents triggered exception workflows, instantly notifying the right stakeholders to review and resolve discrepancies.
  • Continuous Learning & Optimization:
    By observing human interventions and approval patterns, Amantra agents learned from recurring mismatches, continuously improving matching accuracy and reducing future exceptions.

Solution Highlights

  • Autonomous Reconciliation Agents (No-code configuration)
  • Self-Learning Feedback Loop for Exception Handling
  • ERP Integration with SAP and Oracle
  • Live Dashboards for CFOs and Audit Teams
  • Compliance-First Design with audit-ready trails

Business Outcomes

  • Reconciliation Time: Reduced from 7–10 days to less than 24 hours, enabling near real-time financial visibility.

  • Manual Effort: Decreased by 85%, freeing teams from repetitive matching and validation tasks.

  • Accuracy: Improved from approximately 87% to 99.3%, ensuring reliable and error-free reconciliations.

  • Month-End Closure: Shifted from delayed to on-time reporting, improving financial governance.

  • Audit Readiness: Enhanced from low compliance to fully audit-ready, with complete traceability and documentation.

Client Testimonial

Amantra agentic AI approach has not only automated our reconciliation process but also made it smarter every month. We’ve turned a compliance headache into a strategic advantage. — CFO, Leading Retail Chain  

Why Agentic AI is the Future of Finance in Retail

Unlike traditional RPA or static automation scripts, Agentic AI behaves like a digital co-worker proactively acting, learning, and adapting to retail finance workflows. It’s built to:
  • Handle unstructured data at scale 
  • Make intelligent decisions autonomously 
  • Integrate seamlessly with existing retail systems 

Ready to Automate Your Retail Reconciliation?

Talk to our AI experts today to see how Amantra Agentic AI can transform your finance operations. Request a Demo | Chat with a Consultant