AI Correspondence Authentication Using Fraud Fault Scoring
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Solution Overview
Problem
Conventional fraud detection systems are inefficient and costly, as they struggle to authenticate correspondence accurately, leading to potential loss of sensitive data and resources due to fraudulent correspondence that mimics legitimate enterprise communications.
Innovation Solution
A correspondence fraud detection system using AI-based models to extract content data, detect faults, generate fraud likelihood scores, and determine authenticity, thereby automating the verification process and reducing resource burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional fraud detection techniques are used, then users can verify correspondence authenticity by contacting enterprise personnel, but this results in high costs, wasted technological resources, and loss of trust
Solution Approach 1:
The system performs preliminary authentication by embedding digital watermarks and authentication codes in correspondence during the generation phase. This allows users to verify authenticity independently without needing to contact enterprise personnel, eliminating the need for post-delivery verification resources
Solution Approach 2:
The system enables users to self-verify correspondence authenticity using mobile devices and the provided authentication mechanisms (digital watermarks, codes, URLs). This self-service capability eliminates the need for enterprise personnel involvement in verification, reducing their workload and associated resource consumption
2Reliability
If enterprises authenticate each piece of correspondence generated by authorized branches, then correspondence authenticity can be ensured, but this is untenable for large enterprises with many branches
Solution Approach 1:
The system creates digital replicas of enterprise branding elements (logos, letterheads, formats) and embeds them in correspondence along with unique authentication codes. These digital copies can be verified without requiring the original enterprise to manually authenticate each piece, allowing automated verification of authenticity
Solution Approach 2:
The system transforms the authentication approach from manual review of entire correspondence documents to verification of specific parameters (authentication codes, digital watermarks, QR codes). This parameter-based verification simplifies the authentication process while maintaining reliability across multiple branches
3Reliability
If users contact enterprise personnel to verify correspondence, then authenticity can be confirmed, but this leads to user confusion and potential loss of sensitive data
Solution Approach 1:
The system replaces the mechanical process of contacting personnel (phone calls, emails, in-person verification) with automated digital verification mechanisms. Users can instantly verify authenticity using mobile devices by scanning QR codes or checking digital watermarks, eliminating the time-consuming human interaction process
Data Source
AI summary
Systems, apparatuses, methods, and computer program products are disclosed for providing correspondence fraud detection. An example method includes receiving candidate correspondence associated with a user and extracting, based on one or more artificial intelligence (AI) modeling techniques, correspondence content data from the candidate correspondence. The example method further includes detecting, based on the correspondence content data, a set of correspondence faults associated with the candidate correspondence. The example method further includes generating based on the set of correspondence faults, a fraud likelihood score associated with the candidate correspondence in order to determine an authenticity category for the candidate correspondence, where the authenticity category is indicative of whether the candidate correspondence originated from an enterprise with which the user is associated. The example method further includes providing a correspondence fraud evaluation, where the correspondence fraud evaluation comprises an indication of the authenticity category for the candidate correspondence.