Automating Business Intelligence for Fast Growing Credit Lending Platform

Automating Business Intelligence for Fast Growing Credit Lending Platform

Overview

This company offers a proprietary platform that matches small businesses to the best sources of capital. They have clients across the United States. Their network consists of 1.6 million users, credit rating agencies, and small business service providers that includes CPAs and lawyers.

The company was using multiple reporting tools to perform analysis because no single platform was able to meet their requirements. Also, all the services they were using delivered static reports with limited visuals. As a result, it was a tedious task for the data science and analytics team to collate and create all reports from different tools manually and then share them with senior management. There was no flexibility for the business users to interact with these reports for an in-depth analysis. They could not drill down or slice & dice the data in the report to view insights from different dimensions.

They needed a BI solution that could read data from multiple sources and collate all this data in different formats to unify the reporting process. Their analysts wanted advanced visuals on their data in the form of dynamic reports and dashboards. They wanted to automate the generation and distribution of reports to respective stakeholders.

Business Challenge

Multiple reporting tools made it difficult for the data science and analytics teams to obtain consistent, timely and consolidated information from their vast amounts of data. The team had to manually operate numerous platforms to create, verify and then publish reports. It was time-consuming; as a result, business users had a long waiting time for the information they needed. The dependency was so high that even for basic reporting operations like editing of values, fields, charts etc. they had to raise a request to the data science and analytics team.

The company needed an analytics platform that could:

• Unify their reporting and analytics process on a single platform
• Provide self-service reporting and analytics features
• Process years of collected data with the ability to append real-time data inputs
• Provide advanced visualizations so that business users could understand and interpret the data easily
• Automate delivery of dynamic reports to multiple stakeholders as per set schedules

Enable business users to access and interact with the reports and dashboards in real-time, without any dependency on the data science team.

Intellicus Solution

Intellicus empowered the organization to achieve a consolidated, 360-degree view of all their operations onto a single platform. Intellicus provided a superset of features and connectors to collate their vast amounts of data into OLAP cubes and derive a single version of the truth with interactive reports and dashboards across various business lines.

The company pre-aggregates their data inputs in the form of cubes to perform sub-second multi-dimensional analysis of various monthly performance, financial and marketing reports.

With Intellicus, their business users are analysing the performance of relationship managers, measuring their KPIs for the assigned accounts. Their team analyses borrower information collected from various channels, payment histories, credit ratings, loan sanction and disbursal processes.

They also generate real-time data insights with Intellicus smart view reporting feature. It has reduced their time-to-insights, from months to a few minutes.

Business users can slice and dice to get the most granular details from their data. Self-service capabilities in Intellicus empowers them to perform basic to advanced analytics. It has reduced their dependency on the data science and analytics team. Their team leverages the scheduling feature in Intellicus to automate reports delivery to end-users and stakeholders. Also, they have automated delivery of portfolio status reports to their key customers.

Intellicus provides features like machine learning based analytics, what-if analysis, geospatial analytics and helps the data science and analytics team to perform advanced analytics on their data.

As the next steps, their data science team plans to automate the creation of ETL pipelines in Intellicus for faster processing of insights.