Advanced Analytics Framework for a Consumer Financing and Loan Servicing Company in the USA

Case Study: Advanced Analytics Framework for a Consumer Financing and Loan Servicing Company in the USA

About the Client

The client provides alternative financing for career schools, technical schools, and other training providers. They have established innovative solutions that traditional lenders do not offer, allowing education to individuals with lower or limited credit histories.

The Business Challenge

The education lending function concentrates on financing individuals to fulfill their educational and financial needs. Nowadays, individuals & businesses have numerous options to choose from when it comes to getting loans. Therefore, financial institutions must differentiate themselves from their competitors by providing competitive products, world-class services, and a superb digital channel experience & adoption.

To ensure financial institutions are on the right track, they must regularly measure their Key Performance Indicators (KPIs). For example, financial institutions could measure various parameters such as quality, cost of products offered, risk, or customer service. Moreover, by measuring this could ensure that the goals of financial institutions are completed smoothly in the long run.

Earlier KPIs were monitored using traditional Ad Hoc Analysis using markdowns and notebooks. Therefore, the data flew from hundreds of raw sources and had various cleaning and transformation that needed to be done. But, the entire process was manual, which was very time & resource consuming.

The goal was to transform and analyze the data seamlessly to gain actionable insights into the various metrics. So, the client wanted to have an advanced analytics framework with data lake integration, enhanced analytics, improved KPI reporting, and dashboard visualization. In addition, the entire pipeline needed to be completely automated to reduce manual efforts, and enhance monitoring of the Application Process, Approvals, Loan Originations, Loan Pool Performance & Other Initiatives. Therefore, this would improve and accelerate analytics-driven decisions and reduce the time for data analysis, data analytics, and data reporting on structured and unstructured data.

What Aptus Data Labs Did

Data Lake

We built enterprise data lake architecture on the AWS platform. Additionally, this solution included AWS data lake architecture for scalable warehouse and AWS data lake architecture for structured and unstructured data. Also, the raw unstructured data would flow from various sources and get stored in the data lake, which would then be cleaned and processed for analytics.

Advanced Analytics

We wrote advanced analytics scripts to clean, preprocess, transform, and store unstructured raw data. In addition, we wrote scripts to calculate key performance indicators and other ad-hoc analytics of business use cases and demands. Hence, analytics and monitoring were done based on different segmentations, such as customer credit eligibility, pool vintages, etc.

KPI Dashboards

We built intuitive dashboards for visualizing key performance indicators and daily monitoring for stakeholders. Furthermore, the dashboard was divided into various tabs for different business areas. In addition, it had various control parameters to filter the dashboard across different segments, report dates, etc. Therefore, the dashboard involved monitoring the conversion funnel and understanding loan application trends, approval rates, and loan performance, among few.


The entire pipeline starting from procuring raw data from various sources to rendering intuitive visualizations was completely automated with different refresh schedules.

The Impact Aptus Data Labs Made

The advanced analytics platform enabled the client to quickly process, analyze, and report structured and unstructured data with better analytics-driven decisions. As a result, it helped increase productivity, reduced manual efforts and better KPI monitoring. Therefore, this solution also helped the client to reduce IT costs and improve business performance.

Personas for Dashboard

Dashboard Flow

There were various visualizations and some of the important ones were:

All the dashboards had different control parameters to set various filters on the dashboard reports such as Date Filter, CScore Filter etc.

The Business and Technology Approach

Tools Used

Python, R, AWS S3, AWS RDS, AWS EC2, AWS Lambda, AWS CloudWatch, AWS Quicksight, AWS Glue, Cron, PostGreSQL, Shell Scripting, DBeaver.

The Outcome

Related Case Studies

Case Study: Achieving Low-Latency API-Based Queries with MongoDB

Achieving low-latency API-based queries with Mongo DB

Performance analysis - MapR DB vs. Mongo DB - Tool Selection Process
Case Study: Revolutionizing Pharma Analytics with AWS Data Lake

Revolutionizing Pharma Analytics with AWS Data Lake

Enterprise Data Lake and Analytics implementation for a large Pharmaceutical Company in India on AWS platform
Case Study: Boosting Performance with Apache Spark Migration

Boosting Performance with Apache Spark Migration

Data Migration & Performance Improvement of large data processing

Unlock the Potential of Data Science with Aptus Data Labs

Don't wait to harness the power of data science - contact Aptus Data Labs today and start seeing results.

Get In touch with our  Experts

If you’re looking to take your business to the next level with data science, we invite you to contact us today to schedule a consultation. Our team will work with you to assess your current data landscape and develop a customized solution that will help you gain valuable insights and drive growth.