Client Background

Chetwood Financial is a dynamic financial services provider known for its innovative approach to banking. With a focus on digital solutions, Chetwood sought to develop a robust financial decision engine that would enable data-driven, automated decision-making across their card and applicant processes. They wanted a scalable solution that could seamlessly integrate with their existing infrastructure and securely communicate with internal and third-party APIs.

Project Scope

Our engagement with Chetwood involved developing a comprehensive financial decision engine capable of evaluating all decisions made within the organization. This included card and applicant decisions, covering a high-level flow that encompassed various stages: card/applicant recognition, pre-bureau rules, bureau data gathering, score calculation, provisional and affordability assessment, post-bureau rules, and credit strategy management.

Technologies and Solutions

1. AWS Infrastructure: To ensure scalability, reliability, and flexibility, we leveraged Amazon Web Services (AWS) as the foundation for the application architecture. AWS CloudFormation was used for resource provisioning, enabling us to automate the setup and deployment of the infrastructure. This approach allowed for efficient management of the cloud resources and seamless scaling as Chetwood's operations expanded. Decision Logic and API Development: The decision logic that is responsible for evaluating decision rules was written in Python and executed using AWS Lambda functions and AWS API Gateway. By leveraging the serverless architecture, we achieved optimal scalability and cost-efficiency. We defined the Decision Engine AP using the Swagger OpenAPI specification, ensuring clear and standardized communication between various components of the system. Secure Communication and API Management: The financial decision engine required secure communication with both internal and third-party APIs. To address this, we employed AWS Secrets Manager to securely store and manage API keys, credentials, and other sensitive information. This ensured the confidentiality and integrity of data exchanged between the decision engine and external systems. Data Storage and Processing: Decision evaluation rules were stored in Amazon DynamoDB tables, providing a highly scalable and fully managed NoSQL database solution. We utilized Amazon Kinesis Data Streams for real-time data processing, enabling Chetwood to ingest and process vast amounts of data in near real-time. Analytics and Reporting: To empower data-driven decision-making, we integrated Amazon Redshift, a powerful data warehousing solution. This allowed Chetwood to store and analyze large volumes of structured and semi-structured data, gain valuable insights, and generate comprehensive reports on their decision-making processes. Continuous Integration and Deployment:To ensure smooth and efficient deployment, we employed AWS Serverless Application Model (SAM) and AWS CodeBuild. These tools facilitated automated build, testing, and deployment processes, minimizing manual effort and enabling rapid iteration and updates.
2. Decision Logic and API Development: The decision logic that is responsible for evaluating decision rules was written in Python and executed using AWS Lambda functions and AWS API Gateway. By leveraging the serverless architecture, we achieved optimal scalability and cost-efficiency. We defined the Decision Engine AP using the Swagger OpenAPI specification, ensuring clear and standardized communication between various components of the system.
3. Secure Communication and API Management: The financial decision engine required secure communication with both internal and third-party APIs. To address this, we employed AWS Secrets Manager to securely store and manage API keys, credentials, and other sensitive information. This ensured the confidentiality and integrity of data exchanged between the decision engine and external systems.
4. Data Storage and Processing: Decision evaluation rules were stored in Amazon DynamoDB tables, providing a highly scalable and fully managed NoSQL database solution. We utilized Amazon Kinesis Data Streams for real-time data processing, enabling Chetwood to ingest and process vast amounts of data in near real-time.
5. Analytics and Reporting: To empower data-driven decision-making, we integrated Amazon Redshift, a powerful data warehousing solution. This allowed Chetwood to store and analyze large volumes of structured and semi-structured data, gain valuable insights, and generate comprehensive reports on their decision-making processes.
6. Continuous Integration and Deployment:To ensure smooth and efficient deployment, we employed AWS Serverless Application Model (SAM) and AWS CodeBuild. These tools facilitated automated build, testing, and deployment processes, minimizing manual effort and enabling rapid iteration and updates.

Results and Benefits

1. Enhanced Decision-Making: By implementing the financial decision engine, Chetwood gained a sophisticated and agile system that significantly improved the speed and accuracy of its decision-making processes. The automated evaluation of decision rules enabled Chetwood to process applications and transactions rapidly, leading to faster response times and improved customer experiences.
2. Scalability and Flexibility: The AWS infrastructure coupled with serverless architecture provided Chetwood with a highly scalable and elastic solution that will allow the system to effortlessly adapt to increased workload and business growth thereby ensuring consistent performance and minimal downtime.
3. Secure Communication: The team adhered to standard security best practices and policies to ensure that Chetwood's communication with internal and third-party APIs remained secure and protected against unauthorized access. This bolstered data confidentiality, mitigated potential risks, and ensured compliance with industry regulations.
4. Actionable Insights: The incorporation of Amazon Redshift empowered Chetwood with comprehensive analytics capabilities. They gained valuable insights into their decision-making processes, allowing them to fine-tune their credit strategies, optimize risk assessment, and make data-driven business decisions.

End Result

Our collaboration with Chetwood Financial exemplifies our firm's expertise in developing advanced IT solutions that drive transformation and deliver tangible business outcomes. By leveraging AWS services, employing serverless architecture, and utilizing industry-standard technologies, our team helped in developing a robust financial decision engine that revolutionized Chetwood's decision-making processes. This case study serves as a testament to our competence, innovation, and commitment to empowering organizations in the finance sector with state-of-the-art technology solutions. Contact us today to discuss how we can help your organization achieve similar successes in transforming your decision-making capabilities and driving growth.