Krungsri Data Scientists Finally Get Sleep With Informatica's Governance Platform

Thailand's Krungsri is addressing critical data silos that have historically fragmented the institution's analytics capabilities by implementing Informatica's enterprise-grade data governance platform. It is also building the foundational infrastructure needed for AI-driven banking operations.

The deployment centers on Informatica's Cloud Data Governance and Catalog (CDGC) and Cloud Data Quality (CDQ) solutions, both of which run on the vendor's Intelligent Data Management Cloud (IDMC) platform. For Krungsri, which is one of Thailand's largest financial institutions by assets and with over 19 million customers across ASEAN, this deployment is a strategic pivot. By moving toward a unified data architecture, the bank, also known as Bank of Ayudhya Public Company Limited, can support advanced machine learning workflows and real-time analytics at scale.

Hybrid cloud architecture drives data consolidation

The deployment leverages Krungsri's existing hybrid cloud infrastructure built on Amazon Web Services. By creating a distributed yet governed data ecosystem, it addresses the critical need for regulatory compliance across multiple jurisdictions when scaling AI/ML operations.

“Recognizing the pivotal role of data in the banking sector, Krungsri strategically adopts these advanced data governance solutions to enhance data quality, accessibility and integrity,” said Fred Roteseree, executive vice president and head of the enterprise data and analytics group at Krungsri. The focus on data quality pipelines suggests the bank is prioritizing feature engineering and model reliability which are essential components for production ML systems in financial services.

Addressing legacy data management challenges

The platform targets three core technical challenges, including automated data discovery across distributed systems, enterprise-wide metadata management and real-time data quality monitoring. Addressing these concerns are foundational for MLOps workflows as it enables data scientists and ML engineers to build more robust feature stores and maintain model performance in production.

Informatica's AI-powered approach to data governance enables automated data lineage tracking and anomaly detection within data pipelines. These are crucial when maintaining model explainability and regulatory compliance in banking apps. The solution's metadata management capabilities also support automated feature discovery and catalog management, accelerating time-to-deployment for new ML models.

Bottom line

The Krungsri deployment reflects a broader trend in Southeast Asian financial services, where financial institutions are investing heavily in data infrastructure to support AI-driven personalization, fraud detection, and algorithmic trading systems. The emphasis on hybrid cloud deployment also tackles data sovereignty challenges that are prevalent across ASEAN markets.

Steven Seah, vice president for Informatica ASEAN, India and Korea, emphasized the broader regional implications: “Krungsri's transformation journey demonstrates how strategic data governance, enabled through our partnership, can help large financial institutions to navigate complex data landscapes, accelerate innovation and realize meaningful operational value.”

The integration of CDGC and CDQ creates automated data quality checks within ETL/ELT pipelines. It ensures that downstream ML models receive clean, validated feature sets — vital for financial applications where model drift and data quality degradation can impact regulatory compliance and customer experience.

Image credit: iStockphoto/damedeeso