Claims reviewers cannot feasibly analyze all claims data to catch fraud
Building an AI fraud detection system for insurance
Here's a look at how RapidCanvas AI tackles fraud detection in the insurance industry, broken down into steps
Data Gathering and Centralization
Data Gathering and Centralization
Collect data from various sources, including policyholder details, past claims, medical records (with proper anonymization), and external databases (with permission).
Extract relevant features from the data. This could involve pinpointing inconsistencies in claims, unusual patterns in customer behavior, or identifying suspicious links between policyholders and healthcare providers.
Train machine learning algorithms on historical data with confirmed fraud cases. These algorithms learn to recognize red flags and predict the likelihood of fraud in future claims.
Analyze new claims against the trained model. The system flags claims with a high probability of fraud, prompting further investigation by human specialists.
As fraudsters develop new tactics, the AI system must adapt. New data on fraudulent claims is fed back into the model, allowing it to constantly learn and improve its accuracy in detecting evolving schemes.
AI-led fraud detection provides major benefits over manual methods
Faster and more accurate fraud detection
AI spots complex patterns human reviewers would miss.
Significant cost reductions up to 50%
Preventing fraud before payouts produces major savings.
Reduced fraudulent claims
Allows accurate, real-time fraud detection at a scale saving billions per year.
Prevent fraud before financial damage
Ongoing monitoring flags fraud attempts early on.
Key Industry Metrics
Hear from Our Customers
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Detecting fraud without AI
High rate of fraudulent claims
Inability to detect complex fraud patterns
Inefficient manual fraud detection
High rate of fraudulent claims
Inability to detect complex fraud patterns
Inefficient manual fraud detection
High rate of fraudulent claims
Inability to detect complex fraud patterns
Inefficient manual fraud detection
High rate of fraudulent claims
Inability to detect complex fraud patterns
Inefficient manual fraud detection
High rate of fraudulent claims
Inability to detect complex fraud patterns
Inefficient manual fraud detection
High rate of fraudulent claims
Inability to detect complex fraud patterns
Inefficient manual fraud detection
See Rapid Time-To-Value
Address unique business needs without starting from scratch; state your business problem and the AutoAI discovery process will generate a matching AI solution within hours.
Build Expert-Led AI
Leverage the industry knowledge of data science experts, as required, to validate against industry benchmarks and ensure optimal AI solution performance
Access Actionable Business Insights
Create visual, interactive data apps, dashboards and reports to showcase business KPIs and outcomes, and monitor business performance
Use An End-To-End AI Solution
Achieve an end-to-end AI solution with an out-of-the-box setup for all steps from data orchestration, data preparation, transformations, model building and testing, through to model deployment and data apps
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