Executive Summary

A mid-sized insurance provider specializing in auto, health, and life insurance. Rising cases of fraudulent claims were causing significant financial losses and increasing operational costs. To address this, we developed a fraud detection system using Databricks to identify and prevent fraudulent activities in real time.

About Client

The client is a mid-sized insurance provider specializing in auto, health, and life insurance. With a strong presence across multiple regions, the company serves a diverse customer base, offering comprehensive policies tailored to individual and business needs. However, the rising volume of fraudulent claims was impacting profitability and operational efficiency, prompting the client to seek innovative solutions. Dedicated to maintaining trust and ensuring efficient claims processing, the company partnered with us to implement advanced fraud detection capabilities and enhance their claims management processes.

Problem Statement

The firm faced three primary challenges:

High Fraudulent Claims Rate

Approximately 5-7% of claims were fraudulent, resulting in significant losses.

Data Silos

Claims data, customer profiles, and adjuster logs were stored in separate systems, hindering fraud detection efforts.

Manual Fraud Detection

The review process relied on manual assessments, leading to inefficiencies and delayed claim processing.

Solution Overview

We implemented a fraud detection system using Databricks to enable:

Data consolidation and transformation for a unified view of claims.

Development of a predictive fraud detection model using machine learning.

Real-time fraud monitoring and visualization through interactive dashboards.

Key Components

#1. Data Consolidation & Transformation

Challenge: Claims-related data was fragmented across multiple systems, making it difficult to analyze patterns effectively.
Solution: Databricks was used to integrate data from policyholder profiles, transaction records, claim histories, and adjuster logs into a unified environment.
Tools: Databricks
Steps:

Extracted and cleaned data to remove inconsistencies and duplicates.
Standardized formats and engineered features such as claim amount, frequency of claims, and suspicious activity flags.

#2. Fraud Detection Model

Challenge: Manual detection methods were inefficient and prone to errors.
Solution: A Random Forest classifier was built using Databricks MLlib to identify potentially fraudulent claims based on historical patterns.
Tools: Databricks, MLlib.
Steps:

Trained the model on consolidated data, focusing on features such as claim amount, claim frequency, customer history, and policy age.
Evaluated the model using precision, recall, and F1-score to ensure high accuracy in detecting fraudulent claims.

#3. Real-Time Monitoring & Visualization

Challenge: Fraud detection needed to be actionable and integrated into existing workflows.
Solution: Tableau dashboards were integrated with Databricks to provide real-time insights into flagged claims and overall fraud risk.
Tools: Databricks, Tableau.
Approach:

Designed dashboards to display fraud risk scores for claims and identify trends in fraudulent activities by region, policy type, and customer demographics.
Enabled fraud investigators to prioritize high-risk claims for detailed review.

Results

25% Reduction in Fraudulent Claims

Significant decrease in fraud cases, saving millions in payouts.

Improved Operational Efficiency

Automated fraud detection reduced manual review time by 40%.

Enhanced Insights

Provided actionable data for proactive fraud prevention strategies.

Tech Stack & Tools

Data Integration & Transformation

Databricks

Fraud Detection Model

Databricks MLlib (Random Forest Classifier).

Visualization

Tableau

Team Composition

Data Engineers: 2
Data Scientists: 2
Business Analyst: 1
Tableau Specialist: 1

Testimonials

Our Slam Book

Tony Lehtimaki

DIRECTOR - AMEOS

Spain

Very professional, accurate and efficient team despite all the changes I had them do. I look forward to working with them again.

Antoine de Bausset

CEO - BEESPOKE

France

They are great at what they do. Very easy to communicate with and they came through faster than I hoped. They delivered everything I wanted and more! I will certainly use them again!

Vivek Singh

MARKETING & SALES HEAD - VARMORA

Gujarat

I really liked their attention to detail and their sheer will to do the job at hand as good as possible beyond professional boundaries.

Nimesh Patel

DIRECTOR - COVERTEK CERAMICA

Gujarat

Excellent work, and on time with all goals. Communication was very easy, and knowledge of work was excellent. Will be working with them on upcoming projects. I highly recommend.

Craig Zappa

DIRECTOR - ENA PARAMUS

United States

"I would like to recommend their name to one and all. No doubt" their web app development services cater to all needs.

Neil Lockwood

CO-FOUNDER - ESR

Australia

Aglowid is doing a great job in the field of web app development. I am truly satisfied with their quality of service.

Daphne Christoforidou

CEO - ELEMENTIA

United States

Their team of experts jotted down every need of mine and turned them into a high performing web application within no time. Just superb!

Talk To Us

Let’s Get In Touch

Contact number

+91 8487981277

+1 770 796 0077

Email Address

[email protected]

Say
Hello

Tell us about your project

Fraud Detection System for Insurance Agency

Industry

Insurance

Project Type

Location

Timeline

Team Size