This Case Shows Specific Expertise. Find the Companies with the Skills Your Project Demands!

You're viewing one of tens of thousands of real cases compiled on Many.dev. Each case demonstrates specific, tangible expertise.

But how do you find the company that possesses the exact skills and experience needed for your project? Forget generic filters!

Our unique AI system allows you to describe your project in your own words and instantly get a list of companies that have already successfully applied that precise expertise in similar projects.

Create a free account to unlock powerful AI-powered search and connect with companies whose expertise directly matches your project's requirements.

Scalable Credit Risk Assessment Platform Enhancement

scalosoft.com

Financial services

Information technology

Business services

Scaling Challenges with Increasing Client Base

The client's rapid growth in users and transaction volume has strained the existing infrastructure and processes supporting their credit risk assessment service. They need a solution to ensure the platform can handle increased load while maintaining performance and accuracy. Current scaling efforts focused on team expansion are proving insufficient.

About the Client

A fintech company providing credit risk assessment software to streamline business lending processes for entrepreneurs and lenders.

Project Goals

Enhance the scalability of the credit risk assessment platform to support a projected 10x increase in users and transactions within the next 12 months.
Improve the efficiency of the data processing pipeline to reduce latency in credit risk assessments.
Maintain or improve the accuracy of credit risk assessments as the platform scales.
Automate and optimize the model deployment and management process.

Functional Requirements

Automated scaling of data processing pipelines using Airflow DAGs and AWS Glue.
Real-time data ingestion and processing from various data sources.
Integration of Machine Learning models (xgBoost, Meta Store, Amazon SageMaker, DBT).
Improved monitoring and alerting using Coralogix, Datadog, and Grafana.
Enhanced model versioning and deployment capabilities.
Robust data governance and security measures.

Preferred Technologies

AWS (Glue, Sagemaker, Eventbridge/Kinesis, Iceberg)

Airflow

Meta Store

Datadog

Coralogix

Snowflake

Python

xgBoost

DBT

Rancher

Graphana

Required Integrations

Various data sources (e.g., financial institutions, credit bureaus)
Third-party data providers for real-time data enrichment
Existing CRM and internal systems

Non-Functional Requirements

High Scalability: Platform must scale horizontally to handle increasing data volumes and user traffic.
Low Latency: Credit risk assessments must be completed within acceptable timeframes.
High Availability: Platform must be highly available to ensure continuous operation.
Security: Data security and privacy must be maintained according to industry best practices and regulatory requirements.
Reliability: Data pipeline must be robust and fault tolerant.

Expected Business Impact

Successful completion of this project will enable Fintech Lending Solutions to scale its platform to meet growing demand, improve operational efficiency, reduce time-to-assessment, enhance risk management, and maintain its competitive advantage in the fintech market. This will lead to increased revenue and market share.