About Kirontech

The startup develops medical payment integrity software that utilizes data analytics to identify and prevent fraud in health insurance contracts. By streamlining claim management for insurers and third-party administrators, the platform enhances operational efficiency and ensures patients receive timely treatment funded by their insurance claims.

```xml <problem> Health insurers face significant financial losses due to fraudulent claims, wasteful practices, and abusive billing, leading to increased costs and reduced operational efficiency. Existing methods for detecting and preventing these issues often lack the accuracy and comprehensiveness needed to identify complex patterns of fraud, waste, and abuse (FWA). </problem> <solution> Kirontech provides an AI-driven payment integrity platform that empowers health insurers to optimize payment accuracy, improve health outcomes, and reduce costs. The platform leverages advanced data analytics and machine learning to detect and investigate FWA across all claims data, identifying previously hidden issues at the patient, doctor, and facility levels. By integrating seamlessly into existing health insurer ecosystems, Kirontech delivers actionable insights, automates workflows, and enhances the efficiency of payment integrity teams. The platform's comprehensive approach enables insurers to proactively manage risks, control unsafe practices, and ensure fair and accurate claim payments. </solution> <features> - AI-driven detection of fraudulent claims, waste, and abuse, affecting 10-30% of claims value - Data readiness through data understanding, cleaning, codifying, and unification - Refined doctor specialty classifications for precise and actionable insights - Peer group creation to establish regional and market norms for fair comparisons - Integration of curated international, regional, and proprietary reference data - Pre-built dashboards for an instant overview of members, doctors, specialties, and providers - Automated generation of text narratives, data, and plots to support findings - Algorithms that work at the active ingredient level to establish market norms for drug prescriptions </features> <target_audience> The primary target audience includes health insurers and third-party administrators seeking to reduce costs associated with fraud, waste, and abuse in medical claims processing. </target_audience> ```

What does Kirontech do?

Where is Kirontech located?

Kirontech is based in Cambridge, United Kingdom.

How much funding has Kirontech raised?

Kirontech has raised 7300000.

Location

Cambridge, United Kingdom

Funding

7300000

Employees

16 employees

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Kirontech

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Executive Summary

kirontech.com 500+

Crunchbase

Cambridge, United Kingdom

Funding

Estimated Funding

$5M+

Team (15+)

No team information available.

Company Description

Problem

Health insurers face significant financial losses due to fraudulent claims, wasteful practices, and abusive billing, leading to increased costs and reduced operational efficiency. Existing methods for detecting and preventing these issues often lack the accuracy and comprehensiveness needed to identify complex patterns of fraud, waste, and abuse (FWA).

Solution

Kirontech provides an AI-driven payment integrity platform that empowers health insurers to optimize payment accuracy, improve health outcomes, and reduce costs. The platform leverages advanced data analytics and machine learning to detect and investigate FWA across all claims data, identifying previously hidden issues at the patient, doctor, and facility levels. By integrating seamlessly into existing health insurer ecosystems, Kirontech delivers actionable insights, automates workflows, and enhances the efficiency of payment integrity teams. The platform's comprehensive approach enables insurers to proactively manage risks, control unsafe practices, and ensure fair and accurate claim payments.

Features

AI-driven detection of fraudulent claims, waste, and abuse, affecting 10-30% of claims value

Data readiness through data understanding, cleaning, codifying, and unification

Refined doctor specialty classifications for precise and actionable insights

Peer group creation to establish regional and market norms for fair comparisons

Integration of curated international, regional, and proprietary reference data

Pre-built dashboards for an instant overview of members, doctors, specialties, and providers

Automated generation of text narratives, data, and plots to support findings

Algorithms that work at the active ingredient level to establish market norms for drug prescriptions

Target Audience

The primary target audience includes health insurers and third-party administrators seeking to reduce costs associated with fraud, waste, and abuse in medical claims processing.