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Altair – Robotic Process Automation in the Banking and Insurance Industry2023-02-15T19:25:44+05:30

Altair offers a competitive edge and higher RoI by encouraging automated processing to coexist without influencing daily operations. It provides an easy to visualize analogy to improve productivity by handing end-to-end operations without any human intervention.

Business Overview

We created Altair to provide our client with the ability to validate each of their activities with embedded robotic automation.
Multiple automated rules were integrated with each service as per requirement by correlating multiple data points.
Improved data mining, data processing and response time of financial and non-financial activities without affecting the regulatory compliance through Altair bots.

The Challenge

Developing machine-encoded optical character recognition features that scan PDF and paper documents.
Ensuring Altair automatically updates itself with the changing service guidelines without increasing manual efforts.
Triggering appropriate responses after collating data and integrating them with various data systems that are disparate.

Our Approach

We analyzed every process at every stage in detail to make sure that data points created are understood by Altair irrespective of the quantum of data fed into the system.

USP of our Project

Data Type Creation

Classified all finance and insurance-based data into appropriate numerical and categorical groups to create data points.

Queueing Process

Predicted the number of application submissions and use data science to monitor application queuing to reduce errors and mistakes.

Data Validation

Constantly check the accuracy and quality of data by using data cleansing techniques like data code and data range validation.

Cloud Computing

Leveraged advanced cloud services to build a one-stop place for all datasets and tools that can be easily accessed for data mining.

Data Pipeline

Developed data pipelines from scratch to process data in real-time and cater it to the requirement and combat latency.

Risk Modelling

Regulated all financial and insurance-related activities to evaluate them with the power of data for making data-driven decisions.

Project Highlights

Predict the red flags in fraudulent insurance claims and alert banks with unwavering specifications.
Forecast future potential customers through time series analysis and customer profiling via the data collected.
Personalize marketing strategies by utilizing behavioural, demographic and historical data.

Results – A journey from Ideas to Success

Proactively helps in increasing the per-customer profitability with appropriate budgeting under regulatory compliance.

Improves customer lifetime value by providing a 360-degree overview of each customer.

Technologies we used

Python

Python

Blue Prism

Blue Prism

Apache Hadoop

Apache Hadoop

Amazon RDS

Amazon RDS

Client Testimonial

“I believed that automating multiple financial and insurance services would be nearly impossible. Data Scientists from SoluLab created an awesome program that has helped in taking our business to the next level.”

Alexander Batanov
Data Architect, Insight Data Science

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