Oxford BioChronometrics' Behavior-based Lead Scoring, Fraud Detection & Compliance Solution analyzes user interactions with web forms to identify fraudulent submissions and score the likelihood of leads converting into customers. The solution operates by capturing behavioral features — patterns of interaction with a page and device — and grouping them into clusters. These clusters are then assessed to determine whether the behavior is consistent with a genuine human user filling out a form, a bot, or a human engaged in fraudulent activity (e.g., sweatshop-based form filling using stolen identity data). Key functions include: - Fraud detection: Distinguishes fraudulent form submissions from legitimate ones by comparing behavioral feature clusters against known human patterns, without relying on traditional signals such as device fingerprints, user agents, or IP blocklists. - Lead scoring: Assigns an "Intention Score" to each submitted lead, indicating the probability of conversion based on observed behavioral patterns. - Compliance support: Helps reduce exposure to TCPA violations and associated litigation by identifying leads likely submitted using stolen personal data, where consent was never provided. Results are delivered immediately upon form submission, either via automatic email notification or through an API. The solution targets organizations that rely on lead generation and affiliate marketing, and it is designed to address fraud that evades conventional bot detection tools.