Advanced Analytics Framework for a Consumer Financing and Loan Servicing Company in the USA
About the Client
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
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.
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.
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
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
Python, R, AWS S3, AWS RDS, AWS EC2, AWS Lambda, AWS CloudWatch, AWS Quicksight, AWS Glue, Cron, PostGreSQL, Shell Scripting, DBeaver.
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