Use AI to Detect & Prevent Insurance Fraud

At Xyonix, we design custom AI models that analyze your insurance claims to accurately identify and prevent insurance fraud.

Insurance fraud costs the U.S. $308.6 billion annually [1]. Machine learning can be used to find subtle patterns in your data and more accurately flag suspect claims. In addition, machine learning can be used to reduce false positive events and thus improve both operational efficiencies and your customers' experience.

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Customer Behavior Analyzer, A Case Study

Jul 20, 2021

Customer Behavior Analyzer

We worked very closely with executives of a major dental insurance company to help better understand their customers. We used historic data to predict future customer behavior and purchase selections. Our models predict which customers are likely to lapse, and which are likely to remain loyal. Our models are also explainable, so it is easier to understand which attributes of a customer are indicative of loyalty or lapse tendencies. In addition to understanding high level customer characterizations, our explainable models describe why a specific customer is predicted to be a lapser or loyalist. [Read more]

Jul 20, 2021

Companies who successfully explore and embrace these new technologies can discover significant competitive advantages. At Xyonix, we develop bespoke machine learning solutions for clients in the insurance industry. We take your claims and deliver insights that drive better business results.

Interested in using AI to automatically detect fraud? Contact us and let’s dig in together.

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Dec 22, 2021

“Xyonix’s most impressive characteristic is their passion for helping us solve our problems. They truly believe in what we’re trying to achieve — they’re excited about it. Their members see the value of our work and understand our vision.”

Sherri Engvall, IT Manager @ Delta Dental of Washington [more]

Dec 22, 2021

REFERENCES

1. Coalition Against Insurance Fraud: https://insurancefraud.org/wp-content/uploads/The-Impact-of-Insurance-Fraud-on-the-U.S.-Economy-Report-2022-8.26.2022-1.pdf