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ACEPlus 

As credit card use expands, criminal use of forged or stolen cards is also increasing. In order to further assure the credibility of the credit card business, we developed the ACEPlus fraudulent use detection system based on a score / rule system for such crime patterns, and further expanded its functions.
A new scoring system incorporates functions that judge customer behavior and past instances of illegal use. This system achieves highly accurate results that surpass those of conventional scoring systems.
Furthermore, the function for automatically analyzing past card usage data and proposing rules (data mining) has significantly reduced the work associated with finding and setting rules, which is regarded as a difficult part of rule-based systems.
By utilizing the advanced judgment function of the score / rule-based system, ACE Plus achieves high precision and strategically detects fraudulent card use.

Major Functions

■Flexibility to build a system environment in accordance with handling volume (from tens of thousands to tens of millions of card members)
■Extensive installations in Japanese credit card industries
■Functions to detect and monitor fraudulent card use in real time, online
■Automatic suspension function
■Function to manage information on customer card use
■Scoring function based on customer behavior model
■Function to support data analysis effectively utilizing a database
■Function to search critical alert data
■Flexible changes in screen display
■Work efficiency improvements by obtaining statistical information
■Data mining utilizing accumulated data

Scoring system

ACEPlus achieves highly accurate results that surpass those of conventional scoring systems.
This scoring system has achieved high cost performance and highly precise results, as well as minimizing damage, monitoring online credit authorizations from all over the world in real time, and sending warnings. .
 
Model analysis function
1) Creation of behavior items
Creates behavior databases from accumulated authorization data, based on the usage history of individual card members.
2) CS conversion analysis
Adds behavioral items to the accumulated authorization data. Conducts a CS conversion* analysis on these data, and creates a CS conversion table. In addition, uses this table to conduct a CS conversion of the data used for the CS conversion analysis.
CS conversion: Disclosed patent number applied by SURIGIKEN Co., Ltd.: Disclosed Patent
2004-334737
3) Logistic regression analysis
Performs a logistic regression analysis on CS-converted authorization data and creates a regression coefficient table.
4) Table reflection
Periodically reflects the CS conversion table and the regression coefficient table, which have been obtained by the analyses, to the scoring function.

Scoring function
1) Reception of authorization data
Receives authorization data from host and other systems.
2) Acquisition of member behavior data
Acquires member behavior data from received authorizations.
3) CS conversion
Matches received authorizations and member behavior information to the CS conversion table, and converts this information to probability-based logic values.
4) Application of logistic regression model
Applies the regression coefficient table to CS-converted data to calculate the score values.
5) Update of member behavior data
Reflects the received authorization information to member behavior.
6) Return of authorization data
Returns the score values to host and other systems.

Rule system

The ACEPlus rule system has enabled reliable responses to constantly changing patterns of illegal use. ACE Plus is developed to operate around the clock, and of course there is no need to re-boot the machine even when new rules are registered.
It is possible to set the degree of risk for each rule. When a rule has a high-risk profile, it is also possible to suspend transactions automatically. Several hundreds to tens of thousands of rules can be registered.
Moreover, the connection format with ACEPlus is free, and can be connected to suit the customer’s format. The system has earned outstanding plaudits, for both the ease of registering rules and for the operation of monitoring screens.

Rule-Based Detection Function

1) Authorization data reception
Interlocks with authorization data from the authorization system in real time, and converts it to ACE Plus data at the data gateway.
2) Rule engines
Rule check data are transferred through the data gateway to rule engines to conduct a variety of real-time checking.
3) Real-time checking function
Conducts rule checking in real time. It is also possible to check by using the ACE Plus score system points, making the rules even more reliable.
4) ACE PlusDB update
Updates the database ACE Plus administers, after the rule checking is implemented. Allowing ACE Plus to have a unique database makes it possible to manage and refer to data centrally.
5) Data output
The authorization data that correspond to the rules is transferred to warning output, and displayed on the monitor screen in real time. Normal data are transferred to the data gateway.
6) Return of authorization data
Converts data to suit the authorization system and returns the authorization data. Creates behavior databases from accumulated past authorization data, based on the usage history of individual card members.

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