mcredit

Mcredit Offers an Omnichannel Banking Experience with Data-Driven Transformation on AWS

2021

Modernizing the Lending Experience in Vietnam

Against the backdrop of Vietnam’s digital transformation, FinTech firms are disrupting the market and pushing banks to focus more on customer-centric business models. Lending is a leading FinTech category in Vietnam, with 80 percent of banks investing in strengthening their lending capabilities.

Mcredit is a joint venture between Vietnam-based Military Bank (MB) and Japan-based Shinsei Bank, operating across Vietnam. Until 2020, the company’s primary sales channels were direct sales and telesales. However, in the age of self-service and omnichannel marketing, Mcredit wanted to capitalize on the country’s digital momentum. It began investing in transformative solutions to grow its business and retain customers via multiple communication channels. The company specifically sought to increase its customer return and loyalty rates. Previously, Mcredit customers didn’t have a straightforward means to apply for secondary loans or contact the company after the initial sale over the phone.

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AWS supported us in quickly transforming our business model and technology backend, empowering us to speed up releases and time to market.”

Nguyen Manh Khang,
Chief Information Officer, MB Shinsei Finance (Mcredit)

Leveraging a Cloud-First Strategy to Reach Business Goals

A change in management in 2020 proved to be the catalyst for digital transformation at Mcredit, and the business set a goal to grow its customer base tenfold to 10 million customers by 2026. To help achieve this, management advocated for a migration from an on-premises data center to the cloud to boost agility and reduce reliance on manual processes.

Mcredit chose to migrate the critical business applications running on its data center to the Amazon Web Services (AWS) Cloud, given its market reputation and the recommendations of former Mcredit IT employees. AWS and its partners in Vietnam enabled Mcredit’s team and together, they migrated Mcredit’s mission-critical workloads in late 2020. “AWS supported us in quickly transforming our business model and technology backend, enabling us to speed up releases and accelerate our time to market,” says Nguyen Manh Khang, chief information officer at MB Shinsei Finance (Mcredit).

Focusing on Innovation with a Faster Time to Market

Mcredit completed its migration to AWS in March 2021. Its fully containerized AWS Cloud architecture relies on Amazon Elastic Container Service (Amazon ECS) and Amazon Elastic Kubernetes Service (Amazon EKS) for orchestration. It also uses Amazon Elasticsearch Service as a fully managed search solution across its technology stack. “As a bank, we are constantly innovating. The managed services and our Kubernetes architecture on AWS ensure swift deployment and a faster time to market for every project,” Khang says.

The business has 10 major projects scheduled for delivery in 2021, a level of productivity Khang says they could never have achieved running on premises. The time the process required, from creating proposals through to final infrastructure setup, has decreased from four months to three weeks on AWS, which facilitates companywide innovation. Within three months of migrating, Mcredit had launched a mobile app for customers to schedule and track their payments. The development team also added a new feature enabling customers to apply for new loans directly in the app, which is expected to improve the overall customer retention rate.

Stability and Security at Any Scale

AWS and its partners in Vietnam laid out a detailed data migration and security strategy to kickstart Mcredit’s transformation. The lender implemented AWS Direct Connect with native encryption controls to protect data in transit and Amazon Virtual Private Cloud (Amazon VPC) for a secure network connection. “AWS subscribes to the highest compliance controls such as [Payment Card Industry Data Security Standard] PCI DSS, and we have full confidence that our processes, systems, and solutions are secure and compliant,” Khang says.

Mcredit also reports higher availability and stability on the AWS Cloud, which allows the company to serve its customers at any time of day. The business previously faced frequent downtime with its data center, and its systems often crashed during peak load periods when compute resources could not scale. Post-migration, Mcredit implemented AWS Auto Scaling, which automatically adjusts capacity to maintain consistent system performance. 

Optimizing Resource Utilization for Data-Driven Tools

Mcredit benefited from an AWS Well-Architected review to optimize resource usage. In one instance, solutions architects helped rearchitect Mcredit’s Electronic Know Your Customer (eKYC) system for improved scalability. The eKYC system is one of several data-driven tools Mcredit employs. Its data team builds and deploys artificial intelligence algorithms for eKYC models as well as credit scoring and fraud detection.

Build and deployment time for machine learning (ML) models used to be slow in the data center, with limited scalability and memory capacity. On AWS, the time needed to create and deploy ML models dropped from four and a half months to three weeks. “The data ecosystem in AWS is more robust compared to our on-premises infrastructure. We required a lot of storage and compute for data processing and analysis that’s core to our business, and on AWS, we have limitless scalability,” says Khang.

Creating an Omnichannel Experience

Mcredit is using Amazon Relational Database Service (Amazon RDS) to manage its central database and is migrating its data warehouse from on-premises hosting on a competing vendor to Amazon Redshift. By shifting to a cloud-based data warehouse and database administration, the company has reduced its technical debt and converted to an operational expenditure (opex) model, avoiding the increased hardware and licensing fees it would have otherwise incurred on the previous database system.

The business is now focused on enriching its data lake and ML models on AWS. Khang concludes, “We plan to implement more advanced models relating to customer onboarding, retention, and cross-selling and up-selling as well as enhance our customer relationship management system to create a true omnichannel experience. Data will remain a cornerstone of Mcredit’s digital future.”

To Learn More

 To learn more, visit aws.amazon.com/financial-services.


About Mcredit

Mcredit is a joint venture between Vietnam-based Military Bank and Japan-based Shinsei Bank. Employing 4,500 staff members, the lender is undergoing a digital transformation to reduce manual processes and place data at the core of its operation.

Benefits of AWS

  • Reduces time to market from 4 months to 3 weeks
  • Improves availability and stability with automated scaling
  • Complies with PCI DSS and local data security regulations
  • Creates and deploys ML models in 3 weeks instead of 4.5 months
  • Reduces technical debt for administering databases and data warehouse
  • Launched mobile app in 3 months to improve customer retention rate

AWS Services Used

Amazon Relational Database Service

Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud.

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Amazon Redshift

No other data warehouse makes it as easy to gain new insights from all your data. With Redshift, you can query and combine exabytes of structured and semi-structured data across your data warehouse, operational database, and data lake using standard SQL.

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Amazon Elastic Kubernetes Service

Amazon Elastic Kubernetes Service (Amazon EKS) gives you the flexibility to start, run, and scale Kubernetes applications in the AWS Cloud or on-premises. 

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Amazon Elasticsearch Service

Amazon Elasticsearch Service is a fully managed service that makes it easy for you to deploy, secure, and run Elasticsearch cost effectively at scale. 

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