Online Fraud Detection System for Suspicious Transactions (Financial, Card, Internet Bank)

Product Introduction:

“Financial Raviyar” system has been developed with the goal of real-time monitoring and control of financial documents, providing banks and financial institutions with instant information about the flow of documents and financial transactions. Additionally, the system allows banks to prevent the issuance of specific documents that violate organizational policies.By providing realtime statistics on the financial status of accounts,branches, and immediate notification in case of issuing specific documents,and controlling the flow of documents based on predetermined conditions,the system helps banks maintain the efficiency of centralized banking systems and assists them in monitoring the financial flow of the bank and making immediate decisions.

”Modern Raviyar “ system is designed for detecting and preventing fraud and misuse of customer accounts based on online analysis of internet banking transactions. The system analyzes user behavior in interaction with the internet banking interface in real-time and reports suspicious activities to the internet banking system for immediate action. In addition to extracting the geographical location from IP addresses, the system also extracts device information and performs necessary analyses based on that data.

The objective of this system is to detect fraudulent card transactions and, if necessary, block them in real-time. The system identifies behavioral changes of entities involved in transactions using data mining techniques and reports them to the switch. Intelligent behavior analysis and detection of suspicious flows are performed in this module.

Technical Specifications:

Code Development Mechanism: Agile methodology

Advantages:

Financial Raviar

•Real-time dashboard presentation of financial flows of various dimensions

•Real-time deviation reports of financial indices from normal values

•Extraction of normal ranges for indices based on historical data of issued documents on account levels

•Definition of risk conditions for immediate notification in case of issuing documents with specific conditions

•Root cause analysis of abnormal conditions using momentary analysis

•Application of control policies on documents using conditional rules

•Control of document flow on account or branch level

Modern Raviar

•Real-time online analysis of user behavior (e.g., device changes, rapid geographical changes, transactions from new cities or countries)

•Real-time online risk analysis of IP addresses (e.g., control of successful/ unsuccessful transactions, detection of attacks, etc.)

•Real-time online risk analysis of card/deposit behavior (e.g., transaction amount, cumulative amounts, transaction repetition, transaction timing, etc.)

•Definition of conditional rules for transaction parameters, user behavior, IP,

and card/deposit

•Definition of blacklists and whitelists for users, IP, and card/deposit

•Online authorization upon identity verification in internet banking

•Online reporting of transaction risk status and scenario events

Raviar Card

•Modeling the historical behavior of cards, terminals, and destination cards

(traffic, amounts, etc.)

•Real-time online detection of normal behavior using data mining algorithms

•Definition of conditional rules for transaction parameters, card/terminal

behavior

•Definition of blacklists and whitelists for users, IP, and card

•Receiving transactions via standard web service from the card switch

•Utilization of unsupervised data mining algorithms for detecting suspicious behavior