Case Studies



BankPro

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Netron and BankPro Collaborate to Open a New Chapter in AI and Financial Services

BankPro e-Services Technology, established in 2000, became Taiwan's first bank-invested FinTech company approved in 2016. Specializing in payment gateway integration, customized e-commerce solutions, and warehouse logistics management, BankPro provides comprehensive business application solutions. Through diverse system integration, the company assists enterprises in digital transformation and enhances operational value.

 
Currently, BankPro serves clients across industries such as banking, insurance, retail, e-commerce, and logistics. The company is dedicated to advancing the digital cloud economy and innovative applications, helping businesses break through existing frameworks and adopt cutting-edge technologies. By delivering optimal experience design for clients and users, BankPro collaborates to uncover potential business value!

 

Client Requirements：

 

With the Financial Supervisory Commission's ongoing revisions to cloud adoption policies for the financial industry, BankPro deeply recognizes the significance of this development. The future of financial industry clients will undoubtedly shift towards cloud adoption or migration to cloud-based infrastructure. Additionally, with the continuous evolution of artificial intelligence technologies and large language models, BankPro is actively exploring these cutting-edge fields.

To advance these initiatives, BankPro has sought the support of Netron Information Technology. This partnership aims to assist BankPro in mastering cloud migration technologies and leveraging the AWS architecture to develop AI-driven services and solutions. As an MSP (Managed Service Provider), Netron will also provide management and maintenance support, driving the collaborative growth of their business.

 

Solutions Provided by Netron Information Technology：

In addition to assisting BankPro with system deployment and migration, we also collaborate with them to develop an AI architecture using AWS as the infrastructure. This architecture is managed through an MSP model, with Netron taking full responsibility for end-to-end managed services.

  • AWS System Deployment and Migration
  • AI Architecture Using AWS as Infrastructure
  • Build 1 VPC
  • Build 4 Subnets
  • Build 1 AP Server
  • Build Up to 8 EC2 Instances
  • S3 Setup
  • Build 1 DB Server, Redis, DynamoDB

Solutions Map：

  1. High Availability:
    • The architecture incorporates multiple components designed for high availability, such as Kubernetes Cluster, Ingress Controller, and Load Balancer, ensuring service availability and fault tolerance.
  2. Scalability:
    • The Kubernetes Cluster can flexibly scale up or down based on demand, meeting the application requirements of various scales.
    • Ingress Controller and Load Balancer can handle high traffic loads.
  3. Security:
    • The architecture includes authentication (Auth) and authorization (AuthZ) components to control access permissions to applications.
    • The Ingress Controller acts as a reverse proxy and Web Application Firewall (WAF), providing security protection.
  4. Monitoring and Logging:
    • The architecture includes Monitoring and Logging components, enabling comprehensive system monitoring and log collection, which aids in troubleshooting and system optimization.
  5. Service Management:
    • As an MSP, the entire architecture can be centrally managed and automated via the API Server, improving operational efficiency.

金財通AI-Package架構圖

Results :

  • The previously high-cost AI services have become more efficient under the AWS architecture.
  • Cost estimates indicate that migrating to AWS can save approximately 15% in monthly expenses.
  • EC2 development and testing instances can be purchased as Reserved Instances (RI), offering savings of up to 60%.
  • With CloudWatch and SNS for system environment monitoring, the time spent on repetitive tasks by maintenance personnel is reduced by more than 60%.
  • The RDS backup time, compared to the previous on-premise database, has been significantly reduced to under 20 minutes, with the ability to apply automatic backups.
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