2024-0160 - RFP KFAM 2024-0160 - FAMLI Fraud Analytics Solution

The Colorado Department of Labor and Employment (CDLE), Division of Family and Medical Leave Insurance (FAMLI) is seeking a contractor to work with FAMLI in its effort to implement a fraud analytical system.  The fraud analytical system aims to protect valuable resources by reducing fraudulent claims, thereby ensuring that benefits are extended only to those who genuinely require them.

The fraud analytics system will be hosted in a new infrastructure designed specifically for data analytics to improve service quality through informed decision-making and refined resource allocation. 

The primary objective of this RFP is to acquire a robust commercial fraud detection and prevention solution for the FAMLI program to reduce fraudulent claims, improve compliance, and boost program integrity.

A successful solution shall will include:-

• A fraud detection solution that shall improve the detection of fraudulent claims.
• Leveraging business data from MyFAMLi+ and MyFAMLi+Employer as the primary sources for business datak, and have the ability to leverage additional FAMLi+ data housed in the  FAMLI's data analytics repository after it's deployed and operationalized.
• A fraud detection solution that shall be extensible and able to accommodate additional data sources within the CDLE/State or external.
• A fraud detection solution that shall be configurable and the contractor shall create multiple algorithms that identify patterns and anti-patterns to identify anomalies. The Agency may provide additional parameters and search patterns to be implemented by the Contractor within the solution without a separate change order.
• A fraud detection solution that shall leverage, at a minimum, supervised machine learning, at go-live, and shall incorporate unsupervised machine learning models to identify changing fraud schemes, within 12 months of go-live.
• A fraud detection solution that must incorporate all applicable technical, managerial, and operational security controls, both current and emerging, to guarantee data security and conformity with federal and state regulations.