Graph Database Fraud Investigation Scope Expansion
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Solution Overview
Problem
Conventional fraud investigations in online banking are limited by manual analysis, making it difficult for analysts to identify all related transactions for investigation, especially when dealing with fraudulent activities.
Innovation Solution
A server generates a database of transaction entries from a transaction log, using a graph database to identify relationships between actors involved in transactions, allowing for the automatic identification of other transactions for investigation based on known fraudulent transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual analysis is used for fraud investigations, then analysts can investigate transactions involving a particular individual, but it is too difficult to find other related transactions for investigation
Solution Approach 1:
The patent introduces an intermediary system (the fraud investigation system with graph database) that mediates between the transaction data and the analyst. This system automatically discovers relationships between actors and transactions using graph database technology, eliminating the difficulty of manually finding related transactions while expanding the investigation scope.
Solution Approach 2:
The patent replaces the mechanical manual analysis process with an automated computer-based system. The system uses graph database queries to automatically identify relationships between actors and transactions, substituting the manual effort of analysts with automated computational methods that can efficiently explore large datasets.
2Loss of information
If manual analysis is used for fraud investigations, then analysts can investigate high risk score transactions, but the scope of fraud investigations is limited
Solution Approach 1:
The patent enables continuous automated investigation by systematically querying the graph database to identify all transactions involving marked actors or their associates. This continuous automated process replaces间断的 manual investigation, allowing the system to continuously discover related transactions without time constraints.
Solution Approach 2:
The patent creates a graph database copy or representation of the transaction data that can be efficiently queried. By working with this structured representation rather than raw transaction logs, the system can rapidly identify relationships and expand investigations without the time cost of manual analysis.
3Loss of information
If graph database technology is used to identify relationships between actors, then the scope of fraud investigations is expanded, but the system complexity increases
Solution Approach 1:
The patent makes the graph database system multi-functional by using it for both relationship discovery and transaction identification. The same graph structure and querying mechanisms serve multiple purposes: identifying actors in fraudulent transactions, finding their associates, and locating related transactions, thereby managing complexity through functional consolidation.
Data Source
AI summary
An improved technique involves identifying other transactions for investigation from entries in a database that involve a particular actor involved in a known fraudulent transaction. From a transaction log listing transactions, a server generates a database of transaction entries which identify transactions from the transaction log, each transaction entry (i) describing an activity and (ii) identifying a set of actors involved in that activity. Based on a known fraudulent transaction involving a particular actor, the server finds a set of transaction entries from the database which involve the particular actor. From the found set of transaction entries, the server identifies other transactions for investigation.