Turning Enterprise Data into a
Strategic Intelligence Engine

Built a unified AWS data platform that integrates multiple banking systems to deliver real-time Customer 360 insights and a single source of truth.

360°
Customer
View
100%
Automated
ETL
Multi-Source
Data
Integration
Single
Source
of Truth
SCROLL
01
Challenge

A leading bank in Guam operated across multiple core systems — including FIS, credit card platforms, and sales systems — each with isolated data environments.

This fragmentation limited visibility into customer relationships, delayed reporting, and made it difficult to generate actionable insights. Business teams lacked a unified view of customer behavior, impacting decision-making across lending, marketing, and service functions.

02
Hyniva's Solution

Hyniva designed and implemented a real-time, cloud-native data platform to unify disparate data sources into a single, scalable foundation.

The engagement began with a comprehensive assessment of existing systems and data flows to define a long-term data strategy.

Leveraging AWS serverless technologies, Hyniva built an automated data pipeline architecture:

AWS Glue & PySpark for large-scale data processing and transformation
AWS Lambda to orchestrate and trigger workflows
Seamless integration across mainframe systems, flat files, and modern platforms

This enabled the creation of a centralized data warehouse supporting a Customer 360 view, capturing complete lifecycle insights — from account creation to transaction behavior.

The platform was designed to be real-time, automated, and future-ready.

AWS Glue PySpark AWS Lambda AWS Serverless Data Warehouse Customer 360
03
Benefits Realized
360°
Unified Customer Intelligence

A consolidated view of customer relationships, accounts, and transactions across all systems — enabling smarter decisions across business units

50–60%
Reduction in Manual Data Effort

Automated pipelines replaced manual extraction and reconciliation — freed up data teams for higher-value analysis

70%
Faster Reporting & Insights

Near real-time data availability significantly improved reporting speed — accelerated business responsiveness

Improved Cross-Sell & Personalization

Deeper visibility into customer behavior and product usage — enabled targeted offerings and better engagement

Scalable Data Foundation

Cloud-native architecture built for growth and advanced analytics — ready for AI, ML, and future digital initiatives

04
Outcome

The bank evolved from operating on fragmented data to running on a unified, real-time intelligence layer.

Data is now embedded into everyday decision-making — enabling faster execution, improved customer engagement, and a stronger foundation for digital growth.