Machine Learning (ML) based Accounting Software -

ML-Based Accounting Software

Automated financial reconciliation using Machine Learning

Industry

Manufacturing &

Enterprise Finance

Expertise

Machine Learning

Financial Automation

Predictive Analytics

Reconciliation Optimization

Background

Arcelor Mittal NS, a global leader in steel manufacturing, faced challenges in manually reconciling a high volume of vendor and customer accounts. The company sought an intelligent system to automate the reconciliation process, reduce manual intervention, and predict mismatches before they occur.

Challenges

Time-consuming manual reconciliation of customer and vendor statements

High operational costs due to processing delays and resource allocation

Frequent discrepancies in payment records, leading to internal claims

Lack of early warning systems for predicting mismatches or variances

Solutions Provided

We developed and implemented a Machine Learning-based Accounting Software that automated the reconciliation process and introduced predictive capabilities. The solution included:

Automated Reconciliation Engine

Matched financial records efficiently and accurately

Balance Matching System

Ensured consistency across ledgers with real-time verification

Predictive Algorithm

Forecasted potential discrepancies, enabling early resolution

Smart Notifications

Alerted the finance team to deviations before they escalated

This ML-powered approach significantly reduced manual workload, enhanced accuracy, and enabled Arcelor Mittal NS’s finance department to focus on strategic tasks while maintaining clean financial records.

Copilot

MS Teams

Azure Cloud

Security & Compliance

Dynamic 365

Connect, Analyze & Automate

Data & Analytics

Telecom-Specific Services

Software & App Development

Cloud & Infrastructure

Remote Development

Platforms & Marketplaces

Artificial Intelligence

BI Analytics

Database

Internet Of Things

Mobile Apps

Software Development

Telecom Infra

Telecom OSS

VMWare

Automated financial reconciliation using Machine Learning

Industry

Expertise

Arcelor Mittal NS, a global leader in steel manufacturing, faced challenges in manually reconciling a high volume of vendor and customer accounts. The company sought an intelligent system to automate the reconciliation process, reduce manual intervention, and predict mismatches before they occur.

Challenges

Time-consuming manual reconciliation of customer and vendor statements

High operational costs due to processing delays and resource allocation

Frequent discrepancies in payment records, leading to internal claims

Lack of early warning systems for predicting mismatches or variances

We developed and implemented a Machine Learning-based Accounting Software that automated the reconciliation process and introduced predictive capabilities. The solution included:

Automated Reconciliation Engine

Balance Matching System

Predictive Algorithm

Smart Notifications

This ML-powered approach significantly reduced manual workload, enhanced accuracy, and enabled Arcelor Mittal NS’s finance department to focus on strategic tasks while maintaining clean financial records.

Industries We Serve

Quick Links

Sales Office (Canada/US)

Corporate Office

Tech Office

Reach Us

Artificial
Intelligence

Internet
Of Things

Software
Development