Sanction Screening System Using Electronic Signatures for Fraud Detection

Solution Overview

Problem

Current payment transaction anti-fraud systems are inefficient in automating the review of transactions that require manual verification, leading to high costs and errors, especially with the rise of cryptocurrencies like Bitcoin, which pose challenges in auditing exchanges into FIAT currency for anti-money laundering and fraud detection.

Innovation Solution

The system uses electronic signatures based on user attributes such as browser fingerprints, computer fingerprints, IP addresses, and typing patterns to uniquely identify users across transactions, allowing for automated authentication and fraud detection, reducing the need for manual review by building a database of transaction history and using hashes to identify known users without compromising personal information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual review of transactions is performed, then fraud detection accuracy is improved, but processing time and cost increase

Engineering Contradiction:

Improvefraud detection accuracyVSAvoidprocessing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary automated screening of transactions using multiple data sources and risk indicators before manual review. This pre-processing filters out clearly legitimate and clearly fraudulent transactions, leaving only borderline cases for manual review, thus reducing processing time while maintaining detection accuracy

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an automated risk assessment system as an intermediary between initial transaction screening and manual review. This intermediary layer analyzes transactions using machine learning models, user behavior patterns, and external data sources to generate risk scores, enabling more efficient triage of transactions requiring manual attention

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If manual review of transactions is performed, then fraud detection accuracy is improved, but operational cost increases

Engineering Contradiction:

Improvefraud detection accuracyVSAvoidoperational cost

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system performs preliminary automated screening of transactions using multiple data sources and risk indicators before manual review. This pre-processing filters out clearly legitimate and clearly fraudulent transactions, leaving only borderline cases for manual review, thus reducing processing time while maintaining detection accuracy

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent implements self-service automation where the system autonomously processes and decisions on the majority of transactions using automated rule-based systems and machine learning models. Only complex or high-value transactions are escalated to human reviewers, enabling the system to serve itself for routine decisions and reducing dependency on expensive manual labor

Inventive Principle:

Principle #25Self-service

3Reliability

If cryptocurrency transactions are monitored for anti-money laundering, then compliance is improved, but system complexity increases

Engineering Contradiction:

ImprovecomplianceVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements a universal monitoring framework that handles multiple types of transactions (cryptocurrency, FIAT, cross-border) through a single integrated system. The same core architecture processes different transaction types by applying appropriate rules and data sources, avoiding the need for separate complex systems for each transaction type while maintaining comprehensive compliance coverage

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent introduces an automated risk assessment system as an intermediary between initial transaction screening and manual review. This intermediary layer analyzes transactions using machine learning models, user behavior patterns, and external data sources to generate risk scores, enabling more efficient triage of transactions requiring manual attention

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS10628828B2Systems and methods for sanction screening

Publication Date: 2020.04.21 ACUANT

AI summary

In some examples, a computerized sanction screening system may include an automated system for collection of sanction information, and a routine for analyzing additional available data related to sanction information entities. The system may also include an automated analysis summary routine for creating condensed information subsets or graphlets containing relevant information about sanction entities, some of which can be entities themselves, organized in a data retrieval system, such that an automated transaction system can check data from transactions and automatically identify and flag potentially sanctioned transactions. Then upon exceeding a preset contextual limit, a potential blocking warning is issued.