AI-Powered Fraudulent Detection

Educational institutions are inundated with applications each year, often making it challenging to process them promptly for the start of the school year. Many are unaware that a significant portion of these applications could be fraudulent, creating a strain on resources as staff work to discern legitimate from fraudulent submissions—a time-consuming and costly process. This inefficiency not only leads to financial losses but also allows fraudsters to misappropriate funds and take seats from deserving students, thereby impacting the institution’s mission to serve qualified applicants.

The LightLeapAI™ Fraud Detection Module offers a robust solution, purpose-built to identify and prevent fraudulent activity with accuracy and speed. By leveraging advanced machine learning algorithms, this module continually monitors applications and behavioral patterns in real-time, detecting anomalies and suspicious actions before they escalate. Customizable to the unique needs of educational institutions, it minimizes false positives, enhancing operational efficiency and ensuring a seamless experience. Equipped with tailored alerts and in-depth analytics, the module empowers institutions to uphold their integrity and secure their resources effectively.

By adopting the LightLeapAI™ Fraud Detection Module, institutions take a proactive stance on financial protection and reputation management. The module offers powerful safeguards against financial fraud, including FAFSA-related scams, by identifying unusual patterns swiftly and accurately. With configurable options specific to the educational sector, it allows administrators to focus on real threats, thus optimizing their efforts. Moreover, it reinforces compliance with regulatory standards, supporting transparency and trust. Through this advanced fraud detection technology, universities can provide a secure environment for students and staff, protect their assets, and foster a culture of accountability.

AI Fraud Detection Model Approach

The proactive model uses an API trigger (such as upon receipt of application data, or registration transaction) that calls the LightleapAI model to analyze and return a fraud score or "likelihood of fraud". Certain local actions, such as holds, can be placed based on the confidence score. The model returns a rationale for why a score would be flagged as fraudulent, to aid human reviewers, if required.

Using lightleapAI and the N2N Illuminate platform encourages collaboration within districts and with other CCCs. Sharing information on fraud patterns, bad actors, and blacklisted data (IP addresses, SSNs, phone numbers, etc.) enhances detection mechanisms across the California Community College system.

If successful, a future scaling scenario can create an enhanced network effect allowing lightleap to identify fraud once in a single institution, and then to detect and identify the same bad actors across institutions.

Key Fraudulent Identifiers

Collaboration & Sharing

Some clusters identified may be based on demographics or metadata, such as applications or registrations sharing an IP address or similar characteristics. Other clusters may leverage intelligence that links multiple accounts using metadata, behavioral characteristics, engineered data fields, and other information used to train the AI model.

Types of Clusters

  • Multiple Applicants from the same IP Address - Multiple applicants being created and sent from the same IP address.

  • Multiple Accounts from the same Application and Behavior - Multiple accounts being created with same behavioral patterns and across all applications with fraudster data

Leading Indicators of Fraud

  • Age

  • SSN Issuing State

  • High School State

  • Financial Aid References

  • Intended Major

  • GPA - Grade Point Average

Our Fraudulent Detection utilizes key indicators to detect Fraudulent applications

Cluster Identification

Fraud Capture Efficiency

The aim of LightleapAI™ fraud detection is to detect fraudulent applications before they receive financial aid to provide faculty and staff more time and capital to use their resources for what's most important.