Big Data

Big Data

Implementation Story

A Successful Big Data Implementation for Inland Revenue Board of Malaysia

The Inland Revenue Board of Malaysia (LHDNM) embarked on a groundbreaking journey to modernize its tax management system, underscoring its unwavering commitment to providing exemplary tax services to the citizens of Malaysia. This transformative initiative hinged on the implementation of advanced analytics through the Tax Audit and Compliance System (TACS), a forward-thinking endeavor aimed at detecting fraudulent tax activities and understanding taxpayer behavior. Significantly, this initiative leveraged the power of Big Data, incorporating Artificial Intelligence (AI) and Machine Learning (ML) models to augment existing business intelligence strategies and align with LHDNM’s strategic objectives. 


How We Help Them

Real-time Data Processing:

The system’s architecture enables real-time data processing, ensuring that tax-related information is handled promptly, which enhances responsiveness to taxpayers’ needs. 

3M+ Entries Analyzed Daily

TACS, fortified by Microsoft’s Big Data capabilities and open-source technologies, processes an astounding three million or more entries daily, showcasing its scalability and ability to handle vast troves of tax-related data. 

14+ Advanced Statistical Models Deployed

The implementation demonstrates the sophistication and depth of analytics used, with over fourteen advanced statistical models strategically deployed, leveraging both open-source and Microsoft tools. 

Enhanced Fraud Detection

The combination of open-source and Microsoft-powered analytics enabled faster and more accurate identification of fraudulent activities, resulting in a significant boost in revenue collection. 

Enhanced Taxpayer Experience

The insights gained from both open-source and Microsoft’s Big Data analytics allowed LHDNM to tailor its services and communications to individual taxpayers, improving the overall taxpayer experience.