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CASE STUDY

Optimizing Financial Operations with Growexx’s AI-Powered Reconciliation Solution

Financial-Reconciliation-Inner-cover

Industry

Manufacturing

Work Done

Reconciliation, AI ML Development, Oracle Services,

Summary

This case study explores how Recogent, an AI-powered reconciliation solution by Growexx helped a leading manufacturer’s financial team reduce their reconciliation time by 80%, achieve 99% reconciliation accuracy, and close books faster.

About the Client

The client is a leading manufacturing company managing a high volume of transactions across different business units and subsidiaries.
They process thousands of transactions throughout different accounts including payable, receivable, general ledger, and fixed asset accounts.

Client’s Challenges

Despite using multiple ERP systems, the client’s reconciliation process was manual and inefficient, leading to:
  • Lengthy Reconciliation Cycles: Each cycle took 15–20 days, delaying the financial closing.
  • Delayed Issue Resolution: The finance team struggled to identify discrepancies on time, leading to delayed issue resolution.
  • High Risk of Errors & Fraud: Manual data entry errors, transaction mismatches, and compliance violations were common.
  • Increased Operational Costs: The finance team spent excessive time on error correction instead of strategic financial planning.

The AI-Powered Solution: Recogent by Growexx for Faster Reconciliation

Recogent seamlessly integrated with the client’s existing ERP financial modules (GL, AP, AR, Fixed Assets) and third-party systems to:
  • Offer AI-driven recommendations to resolve unmatched transactions.
  • Automate transaction matching across multiple records, reducing manual intervention.
  • Provide actionable insights for immediate anomaly detection.
  • Accelerate financial closing from 18 days to just 2 days, enabling finance teams to focus on high-value decision-making.

How We Implemented Recogent

We followed a step-by-step approach to ensure smooth integration and adoption of our AI-powered reconciliation solution:
  • Integration with ERP & Third-Party Systems: Integrated Recogent with the client’s existing finance management systems and external data sources, such as supplier, customer, and asset audit data.
  • Data Structuring & AI-Model Training: Structured and processed historical reconciliation data to train new AI models and get accurate results.
  • Automation & Testing: Implemented AI-assisted matching, error detection, and reporting workflows.
  • Customization & Dashboard Configuration: Created a custom dashboard to provide clear visibility into transaction discrepancies.
  • Training & Adoption: Provided finance team with hands-on training on AI insights and workflow adjustments.

Why Recogent Was a Clear Choice

The client was using traditional reconciliation methods that were slow, error-prone, and lacked proactive anomaly detection.
These inefficiencies led to delays, compliance risks, and financial blind spots.
With AI-powered automation, they not only streamlined reconciliation but also improved reconciliation speed, compliance, and accuracy.
Here’s what made Recogent stand out:
  • Seamless Integration: It integrated with the client’s existing ERP without disruptions.
  • AI-Powered Accuracy: Our advanced LLMs analyzed reconciliation patterns, detected discrepancies, and provided intelligent recommendations instantly.
  • Faster Financial Closing: It eliminated manual errors and significantly reduced their book-closing time.
Inner

Key Outcomes

Here’s how Recogent improved the client’s overall reconciliation process:
Challenges Outcome
Manual reconciliation took 15-20 days AI-powered reconciliation took less than 2 days
High risk of errors & compliance issues 99% accuracy with AI-driven transaction matching
Finance team burdened with repetitive tasks AI automation freed up resources for strategic initiatives
Limited and delayed visibility into reconciliation issues Actionable insights for faster decision-making

Technologies used

Oracle-Fusion-Cloud-logo
Oracle-Analytics
Oracle-Cloud-Infrastructure-logo
Llama

Struggling with slow and error-prone reconciliation?

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