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Our predictive analytics platform assists payers in managing medical loss ratios, leveraging AI/ML to improve fraud surveillance and detection capabilities to save money through loss reduction.

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  1. / PayAssure



Detect. Prevent. Recover.

Move away from the pay and chase paradigm by shifting from a retroactive to a prospective approach to fraud detection. PayAssure employs the industry’s most comprehensive sets of analytics, tools, and services to assist you in eliminating fraud and abuse at every stage of the process, from detection to prevention to recovery.

Propensity scoring

ML-based anomaly detection for faster exploration and decision making on overpayment, fraud or manual errors.

Targeted review

Flag probable cases for immediate review and bypass the non-probable cases

Intelligent inference

Become proactive about payments using emerging Fraud, Waste and Abus (FWA) methodologies, fraud networks, and prioritized targets

Identify risks at different levels

Find malpractice at level of care using procedural codes and flag duplicate and overutilization claims

Prevent fraud and improve surveillance

PayAssure addresses payers’ increased fraud surveillance and detection demands with a holistic analytics-led strategy. Using the power of various entity risks and powerful AI/ML algorithms, we work to limit false positives and prioritize the highest risk claims.



Apexon in action

See how Apexon helps payers function efficiently, lowering time spent on manual processing, fraud prediction, loss identification, thereby enhancing medical loss ratios, saving expenses and maximizing payments efficiently.

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Fraud propensity scoring

AI/ML-based insights help in proactive claim scoring and review processes that lowers the risk of bad debt and minimizes revenue loss due to fraud.

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Quantitative outlier detection

Our Quantitative Scoring Claims algorithms assists payers in identifying outliers linked to quantity overutilization and detection if a duplicate claim is invoiced by the provider.

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Procedural outlier detection

Identify outliers connected to frequent billing of medically unnecessary treatment, less likely procedure codes, and inappropriate coding methods, and eliminate financial leakages for payers at the physician level.

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Predictive auditing

Our Predictive Risk Scoring model allows payers to audit only 10% of the most erroneous cases, saving time and effort over the manual approach while still collecting an equal number of errors.


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