TWI709923B - Behavioral model credit assessment system - Google Patents

Behavioral model credit assessment system Download PDF

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TWI709923B
TWI709923B TW107134983A TW107134983A TWI709923B TW I709923 B TWI709923 B TW I709923B TW 107134983 A TW107134983 A TW 107134983A TW 107134983 A TW107134983 A TW 107134983A TW I709923 B TWI709923 B TW I709923B
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TW202014941A (en
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林榮華
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臺灣土地銀行股份有限公司
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Abstract

A behavioral model credit assessment system has a communication module, a microprocessor, a scoring generation module, and a verification module. The scoring generation module is configured to generate a total credit score according to a first parameter corresponding to at least one sub-factor parameter of the at least one factor parameter of a corresponding evaluated object received by the communication module and a weight corresponding to the at least one factor parameter. The verification module is configured to obtain, according to the plurality of overdue data corresponding to the plurality of evaluated objects, updated first parameters of the at least one sub-factor parameters corresponding to overdue data. The verification module further obtains an update weight and a high-risk interval corresponding to at least one factor parameter of the over-discharge data according to the updated first parameter of the sub-factor parameter corresponding to overdue data, wherein when the total credit score is located in the high-risk interval, the evaluated object is a high-risk object.

Description

行為模式信評系統 Behavior Model Credit Rating System

本發明係關於一種信評系統,尤指一種可藉由行為模式進行信用評估的行為模式信評系統。 The present invention relates to a credit rating system, in particular to a behavior model credit rating system that can perform credit evaluation through behavior models.

一般民眾購買房屋或汽車等單價偏高的商品時,通常是無法輕易的單次付清所需負擔的款項。因此為了便利民眾購買類似商品,金融機構便提出了貸款的服務,以滿足相關的購買需求。 When ordinary people buy goods with a high unit price such as houses or cars, they usually cannot easily pay off their burdens in a single payment. Therefore, in order to facilitate the people to purchase similar products, financial institutions have proposed loan services to meet related purchase needs.

當民眾欲藉由金融機構進行貸款來購買高價商品時,為了盡量減少成為客戶的民眾發生逾放情事(未準時還款),習知的金融機構會先以授信5P(借款戶、資金用途、還款來源、債權保障以及授信展望)原則來進行核貸,判斷是否核准客戶的貸款申請或者決定最終核貸金額,以減少客戶發生逾放情事的機率。 When people want to use financial institutions to make loans to purchase high-priced goods, in order to minimize the occurrence of overpayment (not repaying on time) by the people who become customers, conventional financial institutions will first grant credit 5P (borrower, use of funds, The principle of repayment source, debt protection and credit outlook) is used to verify the loan, determine whether to approve the loan application of the customer or determine the final loan amount, so as to reduce the probability of overpayment by the customer.

習知金融機構藉由授信5P原則,仍難以降低客戶發生逾放情事的機率,因此本發明提出一種行為模式信評系統,藉由即時更新客戶的逾放情形與其行為模式之間的對應關係,有效藉由與客戶的行為相關聯的多種因子參數判斷客戶發生逾放情事的機率,進而有效減少核貸後發生逾放情事的機率。 It is still difficult for conventional financial institutions to reduce the probability of a customer's overpayment by the 5P principle of credit granting. Therefore, the present invention proposes a behavior model credit evaluation system, which updates the correspondence between the customer’s overrun situation and its behavior pattern in real time. Effectively use a variety of factor parameters associated with the customer's behavior to determine the probability of a customer's overpayment, thereby effectively reducing the probability of an overpayment after the loan is approved.

為達上述目的及其他目的,本創作係提供一種行為模式信評系統,其包括通訊模組、微處理器、評分產生模組以及驗證模組。評分產生模組與微處理器電連接,用以根據第一參數以及權數產生總信用評分,其中第一參數對應於與受評對象相關聯的至少一因子參數中的至少一子因子參數且由通訊模組所接收,且權數對應於至少一因子參數。驗證模組與微處理器電連接,用以根據多個逾放資料得到至少一更新第一參數,並以至少一更新第一參數得到至少一更新權數,再以至少一更新權數得到一高風險區間,其中各該逾放資料個別地對應多個受評對象的其中一者且由通訊模組所接收,至少一更新第一參數對應於與該等多個逾放資料相關聯的至少一子因子參數,至少一更新權數對應於與該等多個逾放資料相關聯的該至少一因子參數,其中當總信用評分位於高風險區間內時,受評對象為高風險對象。 In order to achieve the above and other purposes, this authoring department provides a behavior model credit rating system, which includes a communication module, a microprocessor, a score generation module, and a verification module. The score generation module is electrically connected to the microprocessor for generating a total credit score according to the first parameter and the weight, where the first parameter corresponds to at least one sub-factor parameter of the at least one factor parameter associated with the assessed object and is determined by The weight is received by the communication module and corresponds to at least one factor parameter. The verification module is electrically connected to the microprocessor to obtain at least one updated first parameter based on a plurality of overrun data, and obtain at least one update weight with at least one updated first parameter, and then obtain a high risk with at least one update weight The interval, wherein each of the overrun data individually corresponds to one of the multiple evaluated objects and is received by the communication module, and at least one updated first parameter corresponds to at least one of the multiple overrun data The factor parameter, at least one update weight corresponding to the at least one factor parameter associated with the plurality of overrelease data, wherein when the total credit score is within the high-risk interval, the assessed object is a high-risk object.

在一實施例中,驗證模組根據多個更新第一參數得到多個更新權數,並以該等多個更新權數以及該等多個更新第一參數個別地得到多個主要參數值,其中該等多個更新第一參數以及該等多個主要參數值個別地對應該等多個受評對象的其中一者。 In an embodiment, the verification module obtains a plurality of update weights according to a plurality of updated first parameters, and obtains a plurality of main parameter values individually by the plurality of update weights and the plurality of updated first parameters, wherein the The multiple updated first parameters and the multiple main parameter values individually correspond to one of the multiple evaluated objects.

在一實施例中,逾放資料為受評對象對應一借貸款項的每月未還款資訊。 In one embodiment, the over-disbursement data is the monthly outstanding information corresponding to a loan item.

在一實施例中,第一參數代表子因子參數對應逾放情形發生的機率。 In one embodiment, the first parameter represents the probability that the sub-factor parameter corresponds to the occurrence of the overshoot situation.

在一實施例中,高風險區間為一最大主要參數值的0.4至1.6倍之間,其中最大主要參數值為主要參數值中的最大值。 In one embodiment, the high-risk interval is between 0.4 and 1.6 times a maximum main parameter value, where the maximum main parameter value is the maximum value of the main parameter values.

在一實施例中,行為模式信評系統更包括一權數設定模組,其與微處理器電連接,用以根據該更新權數調整該權數,並用以根據該更新第一參數調整該第一參數,其中該更新權數與該權數對應於同一因子參數,且該更新第一參數與該第一參數對應於同一子因子參數。 In one embodiment, the behavior model credit rating system further includes a weight setting module, which is electrically connected to the microprocessor, for adjusting the weight according to the update weight, and for adjusting the first parameter according to the update first parameter , Wherein the update weight and the weight correspond to the same factor parameter, and the update first parameter and the first parameter correspond to the same sub-factor parameter.

在一實施例中,權數設定模組用以設定初始的權數、第一參數以及最大主要參數值。 In one embodiment, the weight setting module is used to set the initial weight, the first parameter, and the maximum main parameter value.

在一實施例中,行為模式信評系統更包括:一因子參數決定模組,與微處理器電連接,因子參數決定模組用以設定計算該總信用評分所使用的至少一因子參數。 In one embodiment, the behavior model credit rating system further includes: a factor parameter determination module electrically connected to the microprocessor, and the factor parameter determination module is used to set at least one factor parameter used for calculating the total credit score.

在一實施例中,至少一子因子參數為受評對象所選擇的至少一因子參數。 In an embodiment, the at least one sub-factor parameter is at least one factor parameter selected by the subject.

在一實施例中,因子參數為顏色、隨機問題、操作習性、消費性電子產品接收度、社群活躍度、金融關係或數位足跡的至少其中之一。 In an embodiment, the factor parameter is at least one of color, random question, operating habits, consumer electronic product acceptance, community activity, financial relationship, or digital footprint.

藉此,藉由本發明提出的行為模式信評系統,可快速根據與受評對象相關聯或對應的因子參數以及其子因子參數得到對應受評對象的總信用評分,即可快速判定受評對象是否為高風險對象(逾放機率相對較高),以據以判定是否同意受評對象的核貸申請或調整其核貸金額。此外,更可藉由核貸後所產生的逾放資料優化信用評分的準確度,進而有效減少逾放情形的發生。 As a result, with the behavioral pattern credit rating system proposed by the present invention, the total credit score of the rated object can be quickly obtained according to the factor parameters associated with or corresponding to the rated object and its sub-factor parameters, so that the rated object can be quickly determined Whether it is a high-risk object (the probability of over-release is relatively high), it can be used to determine whether to approve the subject’s loan application or adjust its loan amount. In addition, the accuracy of credit scoring can be optimized by the overpayment data generated after the loan is approved, thereby effectively reducing the occurrence of overpayment.

10:行為模式信評系統伺服器 10: Behavioral Model Credit Rating System Server

20:網路 20: Internet

30、40:外部伺服器 30, 40: External server

110:微處理器 110: Microprocessor

120:通訊模組 120: Communication module

130:因子參數決定模組 130: Factor parameter determination module

140:評分產生模組 140: Score generation module

150:驗證模組 150: verification module

160:權數設定模組 160: Weight setting module

170:資料庫 170: database

圖1為根據本發明實施例之行為模式信評系統的使用環境示意圖;圖2為根據本發明實施例之行為模式信評系統伺服器的示意圖;以及 圖3為根據本發明實施例之逾放資料之示意圖。 FIG. 1 is a schematic diagram of a use environment of a behavioral model credit rating system according to an embodiment of the present invention; FIG. 2 is a schematic diagram of a behavioral model credit rating system server according to an embodiment of the present invention; and FIG. 3 is a schematic diagram of over-released data according to an embodiment of the invention.

為充分瞭解本發明之目的、特徵及功效,茲藉由下述具體之實施例,並配合所附之圖式,對本發明做一詳細說明,說明如後:請參考圖1,圖1為本發明之行為模式信評系統的使用環境實施例示意圖,其中,行為模式信評系統可以行為模式信評系統伺服器來實現,且本發明不以此為限制。圖1包括行為模式信評系統伺服器10、網路20、以及外部伺服器30以及40。外部伺服器30用以提供至少包括一子因子參數的因子參數的資訊,且所述因子參數與一受評對象相關聯,其中外部伺服器30可以由網路銀行系統伺服器、金融巨量分析暨應用平台伺服器、資料倉儲伺服器的至少其中之一來實現,且本發明不以此為限制。在一實施例中,所述受評對象例如為向金融機構提出貸款需求的客戶,所述外部伺服器30可為所述金融機構所屬之伺服器,且本發明不以此為限制。 In order to fully understand the purpose, features and effects of the present invention, the following specific embodiments are used in conjunction with the accompanying drawings to give a detailed description of the present invention. The description is as follows: please refer to Figure 1, which is A schematic diagram of an embodiment of the use environment of the behavior mode credit rating system of the invention, wherein the behavior mode credit rating system can be implemented by the behavior mode credit rating system server, and the present invention is not limited thereto. FIG. 1 includes a behavior model credit rating system server 10, a network 20, and external servers 30 and 40. The external server 30 is used to provide information on factor parameters including at least one sub-factor parameter, and the factor parameter is associated with a subject to be evaluated. The external server 30 can be analyzed by an online banking system server or a financial giant At least one of the application platform server and the data storage server is implemented, and the present invention is not limited to this. In one embodiment, the subject of evaluation is, for example, a customer who requests a loan from a financial institution, and the external server 30 may be a server to which the financial institution belongs, and the present invention is not limited thereto.

所述因子參數例如為顏色,其子因子參數可以為紅色、橙色、黃色、綠色、藍色、黑色等不同顏色,其中藉由受評對象選擇不同的子因子參數,可判定受評對象之個性。舉例來說,選擇紅色的受評對象相對於選擇藍色的受評對象可被判斷其個性較為活潑熱情。所述因子參數例如為隨機問題,其子因子參數可以用以表達受評對象的謊言程度,並以高、中以及低來表示。舉例來說,為隨機問題的因子參數可以為具有客觀事實的問題,例如受評對象的年齡,因此藉由受評對象的答案可判斷受評對象的謊言程度。所述因子參數例如為操作習性,其子因子參數可用以表達受評對象操作(例如操作滑鼠點選對應的網頁)時的狀態,且以慢、穩以及急來表示。藉由受評對象選擇不同的子因子參數, 可判定受評對象之性格,舉例來說,當受評對象的操作狀態被判定為「慢」的子因子參數時,可代表此受評對象的性格相對是比較溫吞或者反應較慢的。所述因子參數例如為消費性電子產品接收度,其子因子參數可以用數值(例如0~10)來表示。所述因子參數例如為社群活躍度,可以受評對象於社群軟體的發文字數或使用次數來得到,其子因子參數可以用數值(例如0~10)來表示。所述因子參數例如金融關係(例如為受評對象的交易次數或資產),其子因子參數可以用數值(例如0~10)來表示,數值越高表示其交易次數或資產越高,與金融機構的金融關係更密切。所述因子參數例如為數位足跡(使用電子裝置進行交易的次數或操作網路銀行的次數),其子因子參數可以用數值(例如0~10)來表示,數值越高表示其以電子裝置進行交易或操作網路銀行的次數越高。換言之,因子參數可為顏色、隨機問題、操作習性、消費性電子產品接收度、社群活躍度、金融關係或數位足跡的至少其中之一。 The factor parameter is, for example, color, and its sub-factor parameters can be different colors such as red, orange, yellow, green, blue, black, etc. The personality of the assessed object can be determined by selecting different sub-factor parameters . For example, a subject who chooses red can be judged to have a more lively and enthusiastic personality than a subject who chooses blue. The factor parameter is, for example, a random question, and its sub-factor parameter can be used to express the degree of lies of the assessed object, and is represented by high, medium, and low. For example, the factor parameter that is a random question can be a question with objective facts, such as the age of the subject. Therefore, the degree of lies of the subject can be judged by the answers of the subject. The factor parameters are, for example, operating habits, and its sub-factor parameters can be used to express the state of the assessed object during operation (for example, operating a mouse to click on the corresponding webpage), and are expressed in terms of slow, steady and urgent. By selecting different sub-factor parameters, The personality of the assessed object can be determined. For example, when the operating state of the assessed object is judged as a "slow" sub-factor parameter, it can mean that the personality of the assessed object is relatively mild or slow in response. The factor parameter is, for example, the acceptance of consumer electronic products, and its sub-factor parameter can be represented by a numerical value (for example, 0-10). The factor parameter is, for example, the activity of the community, which can be obtained by the number of texts posted or the number of uses of the social software by the subject, and the sub-factor parameter can be represented by a numerical value (for example, 0-10). The factor parameter is, for example, financial relationship (for example, the number of transactions or assets of the assessed object), and its sub-factor parameter can be represented by a value (for example, 0~10). The higher the value, the higher the number of transactions or the higher the assets. The financial relationship between institutions is closer. The factor parameter is, for example, a digital footprint (the number of times an electronic device is used to conduct transactions or the number of online banking operations), and its sub-factor parameter can be represented by a numerical value (for example, 0~10). The higher the numerical value, the electronic device The higher the number of transactions or operations of online banking. In other words, the factor parameter can be at least one of color, random question, operating habits, consumer electronic product acceptance, community activity, financial relationship, or digital footprint.

舉例來說,外部伺服器30以網路銀行系統伺服器實現時,外部伺服器30可藉由使受評對象操作一子因子資訊收集介面(例如網頁),而收集到對應不同因子參數的子因子參數。進一步的來說,受評對象可操作子因子資訊收集介面來回應一子因子收集問卷(例如為以不同子因子參數設計之問卷),使網路銀行系統伺服器可藉由受評對象針對子因子收集問卷所提供的問卷答案收集到不同的子因子參數。例如收集到紅色的子因子參數、收集到對應謊言程度且為「高」的子因子參數,且收集的子因子參數不以此為限制。此外,更可藉由受評對象操作子因子資訊收集介面的狀態(例如操作速度)收集到對應操作習性因子參數的子因子參數的資訊。同時並可藉由收集受評對象操作網路銀行的次數來收集到對應數位足跡的子因子參數,且本發明不以此為限制。 For example, when the external server 30 is implemented as an online banking system server, the external server 30 can collect sub-factors corresponding to different factors by operating a sub-factor information collection interface (such as a web page) Factor parameter. Furthermore, the assessed object can operate the sub-factor information collection interface to respond to a sub-factor collection questionnaire (for example, a questionnaire designed with different sub-factor parameters), so that the online banking system server can target the sub-factors by the assessed object The questionnaire answers provided by the factor collection questionnaire collect different sub-factor parameters. For example, the red sub-factor parameters are collected, the sub-factor parameters corresponding to the degree of lies and are "high" are collected, and the collected sub-factor parameters are not limited by this. In addition, the information of the sub-factor parameters corresponding to the operating habit factor parameters can be collected through the state of the operating sub-factor information collection interface of the assessed object (such as operating speed). At the same time, the sub-factor parameters corresponding to the digital footprint can be collected by collecting the number of times the subject has operated the online banking, and the present invention is not limited by this.

舉例來說,外部伺服器30為金融巨量分析暨應用平台伺服器的實施例時,外部伺服器30可產生並提供因子參數為消費性電子產品接收度的子因子參數,以及因子參數為社群活耀度的子因子參數,且本發明不以此為限制。 For example, when the external server 30 is an embodiment of the financial massive analysis and application platform server, the external server 30 may generate and provide the factor parameter as the sub-factor parameter of the acceptance of consumer electronic products, and the factor parameter is the social The sub-factor parameter of the group activity brightness, and the present invention is not limited thereto.

舉例來說,外部伺服器30為資料倉儲伺服器的實施例時,外部伺服器30可產生並提供因子參數為金融關係的子因子參數,且本發明不以此為限制。 For example, when the external server 30 is an embodiment of a data storage server, the external server 30 may generate and provide the factor parameter as the sub-factor parameter of the financial relationship, and the present invention is not limited thereto.

在圖1的實施例中僅以一個外部伺服器30為例,但本發明不以此為限制。在其他實施例中,外部伺服器30可根據子因子參數的需求而有多個。 In the embodiment of FIG. 1, only one external server 30 is taken as an example, but the present invention is not limited thereto. In other embodiments, there may be multiple external servers 30 according to the requirements of the sub-factor parameters.

在一實施例中,外部伺服器40可由逾放作業管理系統來實現,且本發明不以此為限制。在此實施例中,外部伺服器40可用以提供對應受評對象的至少一筆逾放資料,其中所述逾放資料為受評對象對應一借貸款項的每月未還款資訊。舉例來說,逾放資料的子因子參數可包括第一個月逾放資訊、第二個月逾放資訊等資訊,其中所述第一個月逾放資訊、第二個月逾放資訊為受評對象於核貸後的第幾個月逾放的資訊。在其他實施例中,逾放資料亦可作為因子參數,且本發明不以此為限制。 In one embodiment, the external server 40 can be implemented by an overrun operation management system, and the invention is not limited thereto. In this embodiment, the external server 40 can be used to provide at least one piece of overpayment data corresponding to the assessed object, wherein the overrun data is the monthly outstanding information of the assessed object corresponding to a loan item. For example, the sub-factor parameters of the over-release data can include the first-month over-release information, the second-month over-release information and other information, where the first-month over-release information and the second-month over-release information are Information about the overdue release of the subject in the first few months after the loan was approved. In other embodiments, the overrun data can also be used as factor parameters, and the present invention is not limited thereto.

因此,行為模式信評系統伺服器10可用以透過網路20(內部網路或網際網路)與外部伺服器30以及40通訊連接,以藉由因子參數的子因子參數資訊來對受評對象進行評分並產生對應的總信用評分,且當總信用評分位於一高風險區間內時,受評對象可被判斷為一高風險對象,同時行為模式信評系統伺服器10更可藉由逾放資料優化總信用評分的準確度。 Therefore, the behavioral model credit rating system server 10 can be used to communicate with the external servers 30 and 40 through the network 20 (intranet or Internet), so as to communicate with the assessed object through the sub-factor parameter information of the factor parameter. Perform scoring and generate a corresponding total credit score, and when the total credit score is within a high-risk range, the subject can be judged as a high-risk subject. At the same time, the behavioral model credit rating system server 10 can also pass The data optimizes the accuracy of the total credit score.

請參考圖2,圖2為行為模式信評系統伺服器10的實施例示意圖。行為模式信評系統伺服器10包括通訊模組120、微處理器110、因子參數決定模 組130、評分產生模組140、驗證模組150、權數設定模組160以及資料庫170,其中微處理器110與通訊模組120、因子參數決定模組130、評分產生模組140、驗證模組150、權數設定模組160以及資料庫170電連接,以用以進行資料的交換以及處理的相關操作。 Please refer to FIG. 2, which is a schematic diagram of an embodiment of the behavioral pattern credit rating system server 10. The behavior model credit rating system server 10 includes a communication module 120, a microprocessor 110, and a factor parameter determination model. Group 130, score generation module 140, verification module 150, weight setting module 160, and database 170, wherein the microprocessor 110 and the communication module 120, the factor parameter determination module 130, the score generation module 140, the verification module The group 150, the weight setting module 160, and the database 170 are electrically connected for data exchange and processing related operations.

通訊模組120可以有線或無線的方式與網路20通訊連接,以接收前述的個別對應一因子參數的至少一子因子參數以及前述的逾放資料,其中通訊模組120可以為乙太網路、光纖網路或無線區域網路之通訊電路來實現,且本發明不以此為限制。 The communication module 120 can be connected to the network 20 in a wired or wireless manner to receive the aforementioned at least one sub-factor parameter corresponding to a factor parameter and the aforementioned overrun data. The communication module 120 can be an Ethernet network. , Optical fiber network or wireless local area network communication circuit, and the present invention is not limited by this.

因子參數決定模組130用以產生一因子參數決定介面,因此一操作人員(例如核貸專職人員)可根據外部伺服器30以及多個外部伺服器30所個別提供的因子參數來決定並設定評分產生模組140產生總信用評分所參考或使用之至少一因子參數。換言之,因子參數可根據需求而設定為1個或多個(例如為2個或5個),且本發明不以此為限制。 The factor parameter determination module 130 is used to generate a factor parameter determination interface, so an operator (for example, a loan professional) can determine and set the score according to the factor parameters provided by the external server 30 and multiple external servers 30. The generating module 140 generates at least one factor parameter referred to or used by the total credit score. In other words, the factor parameter can be set to one or more (for example, two or five) according to requirements, and the present invention is not limited thereto.

評分產生模組140用以根據通訊模組120接收的且對應受評對象的至少一因子參數的至少一子因子參數所對應的一第一參數以及至少一因子參數對應的一權數產生一總信用評分。 The score generating module 140 is used for generating a total credit according to a first parameter corresponding to at least one sub-factor parameter of at least one factor parameter corresponding to the at least one factor parameter of the subject and a weight corresponding to the at least one factor parameter received by the communication module 120 score.

舉例來說,以因子參數為顏色,其包括紅色、橙色、黃色、綠色以及藍色等子因子參數為例,當對應受評對象的子因子參數為紅色,紅色對應之第一參數為120,且因子參數為顏色所對應的權數為0.51,因此評分產生模組140可得到61.2的總信用評分(120*0.51=61.2)。在其他實施例中,當評分產生模組140所採用的因子參數不只一種時,評分產生模組140個別得到對應每一因子參數的信用評分後,將多個信用評分加總而得到對應該受評對象的總信用評分。 For example, taking the factor parameter as color, which includes sub-factor parameters such as red, orange, yellow, green, and blue, as an example, when the sub-factor parameter corresponding to the assessed object is red, the first parameter corresponding to red is 120. And the factor parameter is that the weight corresponding to the color is 0.51, so the score generating module 140 can obtain a total credit score of 61.2 (120*0.51=61.2). In other embodiments, when the score generating module 140 uses more than one factor parameter, the score generating module 140 obtains the credit score corresponding to each factor parameter individually, and then adds the multiple credit scores to obtain the corresponding credit score. The total credit score of the subject.

驗證模組150用以根據個別地對應多個受評對象的多筆逾放資料得到對應逾放資料的至少一子因子參數的更新第一參數。驗證模組150並以多個逾放資料所對應的的至少一子因子參數的更新第一參數得到對應多個逾放資料的至少一因子參數的一更新權數以及高風險區間。所述更新第一參數可代表對應的子因子參數對應於逾放情形發生的相對機率的高低。 The verification module 150 is used for obtaining an updated first parameter corresponding to at least one sub-factor parameter of the overriding data according to a plurality of overriding data individually corresponding to a plurality of evaluated objects. The verification module 150 updates the first parameter of at least one sub-factor parameter corresponding to the multiple overrun data to obtain an update weight and high-risk interval corresponding to at least one factor parameter of the multiple overrun data. The updated first parameter may represent the relative probability of the corresponding sub-factor parameter corresponding to the occurrence of the overshoot situation.

以下以因子參數為顏色,其包括紅色、橙色、黃色、綠色以及藍色等子因子參數以及十筆的逾放資料為例來說明第一參數的實施例,其中逾放資料為第一個月逾放資訊為例,且本發明不以此為限制。驗證模組150判斷在十筆的逾放資料中,六筆逾放資料對應紅色,兩筆逾放資料對應於綠色,兩筆逾放資料對應於橙色,紅色對應逾放資料的機率為60,綠色對應逾放資料的機率為20%,橙色對應逾放資料的機率為20%,黃色以及藍色對應逾放資料的機率為0%。因此在因子參數為顏色所對應的總分為200的例子下,驗證模組150產生對應於紅色的子因子參數的更新第一參數(200*0.6=120,亦代表其對應逾放情形發生的機率相對較高),對應綠色以及橙色的子因子參數的更新第一參數(200*0.2=40,亦代表其對應逾放情形發生的機率相對為中間),對應黃色以及藍色的子因子參數的更新第一參數(200*0=0,亦代表其對應逾放情形發生的機率相對較低)。 The following takes the factor parameter as the color, which includes sub-factor parameters such as red, orange, yellow, green, and blue, and ten overrun data as examples to illustrate the embodiment of the first parameter, where the overrun data is the first month The overrun information is taken as an example, and the present invention is not limited thereto. The verification module 150 judges that among the ten overrun data, six overrun data correspond to red, two overrun data correspond to green, two overrun data correspond to orange, and the probability that red corresponds to overrun data is 60. The probability that green corresponds to overrun data is 20%, the probability that orange corresponds to overrun data is 20%, and the probability that yellow and blue correspond to overrun data is 0%. Therefore, when the factor parameter is the color corresponding to the total score of 200, the verification module 150 generates the updated first parameter (200*0.6=120) corresponding to the red sub-factor parameter, which also represents the occurrence of the corresponding overshoot situation. Relatively high probability), corresponding to the updated first parameter of the green and orange sub-factor parameters (200*0.2=40, which also means that the probability of the corresponding overshoot is relatively middle), corresponding to the yellow and blue sub-factor parameters Update the first parameter of (200*0=0, which also means that the probability of corresponding overshoot is relatively low).

驗證模組150更可根據個別地對應多個受評對象的更新第一參數得到對應每一因子參數的更新權數以及個別地對應多個受評對象的多個主要參數值。在一實施例中,驗證模組150可以主成分分析法得到對應每一因子參數的更新權數以及對應至少一參數組合的主要參數值。主要參數值可代表對應於參數組合(特定逾放情形)的相對機率的高低,換言之,具有最大值的最大主要參數 值可代表發生逾放情形的相對機率最高。因此若受評對象的信用評分越接近最大主要參數值,可判斷受評對象為高風險對象。在其他實施例中,若受評對象的信用評分落於高風險區間內中,判斷受評對象為高風險對象,其中高風險區間約為最大主要參數值的0.4至1.6倍之間,且本創作不以此為限制。 The verification module 150 can further obtain an update weight corresponding to each factor parameter and a plurality of main parameter values corresponding to the plurality of evaluated objects according to the updated first parameters individually corresponding to the plurality of evaluated objects. In one embodiment, the verification module 150 can obtain the update weight corresponding to each factor parameter and the main parameter value corresponding to at least one parameter combination by the principal component analysis method. The main parameter value can represent the relative probability corresponding to the parameter combination (specific overshoot situation), in other words, the largest main parameter with the maximum value The value can represent the highest relative probability of an overrelease. Therefore, if the credit score of the evaluated object is closer to the maximum main parameter value, the evaluated object can be judged as a high-risk object. In other embodiments, if the credit score of the assessed object falls within the high-risk range, it is determined that the assessed object is a high-risk object, where the high-risk range is approximately 0.4 to 1.6 times the maximum main parameter value, and the Creation is not limited by this.

以下以圖3為例進一步說明驗證模組150的運作方法,且本發明不以此為限制。請參考圖3,圖3為放貸後,受評對象A~E所產生的逾放資料(例如為第一個月逾放資訊)實施例。驗證模組150根據對應於受評對象的多個子因子參數以及每個因子參數所對應的總分,可個別的得到每個子因子參數的分數,此分數即對應於前述的更新第一參數。接著,驗證模組150產生對應受評對象的多個主要參數值UA、UB、UC、UD、以及UE,其中UA為120a+60b+80c、UB為40a+60b+80c、UC為40a+180b+120c、UD為120a+180b+120c、UE為120a+180b+120c,a、b、c個別為代表顏色、謊言程度以及消費性電子產品接收度的更新權數。換言之,個別對應受評對象的主要參數值UA、UB、UC、UD、以及UE為受評對象所對應的子因子參數對應的更新第一參數與對應的更新權數的乘積組合。驗證模組150可以主成分分析法對主要參數值UA、UB、UC、UD、以及UE進行運算以個別得到a、b、c的值,進而可個別得到主要參數值UA、UB、UC、UD、以及UE的值,並得到最大主要參數值以及對應的高風險區間。 The following takes FIG. 3 as an example to further illustrate the operation method of the verification module 150, and the present invention is not limited thereto. Please refer to FIG. 3, which is an example of over-disbursement data (for example, the first-month over-disbursement information) generated by the assessed objects A to E after lending. The verification module 150 can individually obtain the score of each sub-factor parameter according to the multiple sub-factor parameters corresponding to the assessed object and the total score corresponding to each factor parameter, and this score corresponds to the aforementioned updated first parameter. Then, the verification module 150 generates multiple main parameter values U A , U B , U C , U D , and U E corresponding to the assessed object, where U A is 120a+60b+80c, and U B is 40a+60b+ 80c, U C is 40a+180b+120c, U D is 120a+180b+120c, U E is 120a+180b+120c, a, b, and c respectively represent the update of color, degree of lies and acceptance of consumer electronic products Weights. In other words, the main parameter values U A , U B , U C , U D , and U E respectively corresponding to the evaluated object are the product combination of the updated first parameter and the corresponding update weight corresponding to the sub-factor parameter corresponding to the evaluated object . The verification module 150 can perform calculations on the main parameter values U A , U B , U C , U D , and U E by the principal component analysis method to obtain the values of a, b, and c individually, and then obtain the main parameter values U A individually , U B , U C , U D , and U E values, and get the maximum main parameter value and the corresponding high-risk interval.

權數設定模組160,用以根據對應其中之一因子參數且為驗證模組150所產生的更新權數來更新(或調整)對應同一因子參數的權數,並以驗證模組150所產生的更新第一參數來更新(或調整)對應同一子因子參數的第一參數。在一實施例中,權數設定模組160更可用以設定初始的權數、第一參數以及最大主要參數值。 The weight setting module 160 is used to update (or adjust) the weight corresponding to the same factor parameter according to the update weight corresponding to one of the factor parameters and generated by the verification module 150, and use the update weight generated by the verification module 150 One parameter is used to update (or adjust) the first parameter corresponding to the same sub-factor parameter. In one embodiment, the weight setting module 160 can further be used to set the initial weight, the first parameter, and the maximum main parameter value.

資料庫170用以儲存行為模式信評系統所需之資訊或資料,例如為前述之對應受評對象的至少一子因子參數以及逾放資料,且本發明不以此為限制。 The database 170 is used to store information or data required by the behavioral model credit rating system, such as the aforementioned at least one sub-factor parameter and overrun data corresponding to the evaluated object, and the present invention is not limited thereto.

因此,當一受評對象欲進行貸款或借貸時,核貸機構(例如金融機構)可藉由上述之行為模式信評系統伺服器10收集到對應受評對象的至少一個子因子參數,並根據對應受評對象的至少一個子因子參數產生對應受評對象的總信用評分,且藉由判斷總信用評分是否落入高風險區間來判斷受評對象是否為高危險對象(逾放機率相對較高的對象)。 Therefore, when a subject wants to make a loan or a loan, the lending institution (such as a financial institution) can collect at least one sub-factor parameter corresponding to the subject through the above-mentioned behavior pattern credit rating system server 10, and then At least one sub-factor parameter corresponding to the assessed object generates a total credit score corresponding to the assessed object, and judges whether the assessed object is a high-risk object by judging whether the total credit score falls within the high-risk range (the probability of over-release is relatively high) Object).

綜以上所述,藉由本發明之行為模式信評系統,可快速根據與受評對象相關聯或對應的因子參數以及其子因子參數得到對應受評對象的總信用評分,即可快速判定受評對象是否為高風險對象(逾放機率相對較高),以據以判定是否同意受評對象的核貸申請或調整其核貸金額。此外,驗證模組150更可藉由核貸後所產生的逾放資料隨時更新以及調整因子參數所對應之權數以及每一子因子參數所對應的第一參數,以優化總信用評分的準確度,進而有效減少逾放情形的發生。 In summary, with the behavioral pattern credit rating system of the present invention, the total credit score of the rated object can be quickly obtained based on the factor parameters associated with or corresponding to the rated object and its sub-factor parameters, and the rating can be quickly determined Whether the object is a high-risk object (with a relatively high probability of over-release), it can be used to determine whether to approve the subject’s loan application or adjust its loan amount. In addition, the verification module 150 can update at any time and adjust the weight corresponding to the factor parameter and the first parameter corresponding to each sub-factor parameter by using the overpayment data generated after the loan is verified to optimize the accuracy of the total credit score. , Thereby effectively reducing the occurrence of over-release.

本發明在上文中已以較佳實施例揭露,然熟習本項技術者應理解的是,該實施例僅用於描繪本發明,而不應解讀為限制本發明之範圍。應注意的是,舉凡與該實施例等效之變化與置換,均應設為涵蓋於本發明之範疇內。因此,本發明之保護範圍當以申請專利範圍所界定者為準。 The present invention has been disclosed in a preferred embodiment above, but those skilled in the art should understand that the embodiment is only used to describe the present invention and should not be construed as limiting the scope of the present invention. It should be noted that all changes and substitutions equivalent to this embodiment should be included in the scope of the present invention. Therefore, the protection scope of the present invention should be defined by the scope of the patent application.

10:行為模式信評系統伺服器 10: Behavioral Model Credit Rating System Server

110:微處理器 110: Microprocessor

120:通訊模組 120: Communication module

130:因子參數決定模組 130: Factor parameter determination module

140:評分產生模組 140: Score generation module

150:驗證模組 150: verification module

160:權數設定模組 160: Weight setting module

170:資料庫 170: database

Claims (9)

一種行為模式信評系統,其包括:一通訊模組;一微處理器,與該通訊模組電連接;一評分產生模組,與該微處理器電連接,用以根據一第一參數以及一權數產生一總信用評分,其中該第一參數對應於與一受評對象相關聯的至少一因子參數中的至少一子因子參數且由該通訊模組所接收,且該權數對應於該至少一因子參數;以及一驗證模組,與該微處理器電連接,用以根據多個逾放資料得到至少一更新第一參數,並以該至少一更新第一參數得到至少一更新權數,再以該至少一更新權數得到一高風險區間,其中各該逾放資料個別地對應多個受評對象的其中一者且由該通訊模組所接收,該至少一更新第一參數對應於與該等多個逾放資料相關聯的至少一子因子參數,該至少一更新權數對應於與該等多個逾放資料相關聯的至少一因子參數;其中當該總信用評分位於該高風險區間內時,該受評對象為一高風險對象,其中該驗證模組根據多個更新第一參數得到多個更新權數,並以該等多個更新權數以及該等多個更新第一參數個別地得到多個主要參數值,其中該等多個更新第一參數以及該等多個主要參數值個別地對應該等多個受評對象的其中一者。 A behavior model credit rating system, which includes: a communication module; a microprocessor electrically connected to the communication module; a score generating module electrically connected to the microprocessor for according to a first parameter and A weight generates a total credit score, wherein the first parameter corresponds to at least one sub-factor parameter of at least one factor parameter associated with a subject and is received by the communication module, and the weight corresponds to the at least one factor parameter. A factor parameter; and a verification module electrically connected to the microprocessor for obtaining at least one updated first parameter based on a plurality of overrun data, and obtaining at least one update weight based on the at least one updated first parameter, and A high-risk interval is obtained by using the at least one update weight, wherein each of the overrun data individually corresponds to one of the multiple evaluated objects and is received by the communication module, and the at least one update first parameter corresponds to the Wait for at least one sub-factor parameter associated with a plurality of overdraft data, and the at least one update weight corresponds to at least one factor parameter associated with the plurality of overdraft data; wherein when the total credit score is within the high risk interval When the evaluation object is a high-risk object, the verification module obtains multiple update weights according to multiple update first parameters, and obtains multiple update weights and multiple update first parameters individually A plurality of main parameter values, wherein the plurality of updated first parameters and the plurality of main parameter values individually correspond to one of the plurality of evaluated objects. 如請求項1所述之行為模式信評系統,其中該高風險區間為一最大主要參數值的0.4至1.6倍之間,其中該最大主要參數值為該等多個主要參數值中的最大值。 The behavioral model credit rating system according to claim 1, wherein the high-risk interval is between 0.4 and 1.6 times a maximum main parameter value, and the maximum main parameter value is the maximum value of the plurality of main parameter values . 如請求項1所述之行為模式信評系統,其中各該逾放資料為各該受評對象對應一借貸款項的每月未還款資訊。 For example, in the behavioral model credit rating system described in claim 1, each of the overdue data is the monthly outstanding information of a loan item corresponding to each of the assessed objects. 如請求項1所述之行為模式信評系統,該第一參數代表該子因子參數對應逾放情形發生的機率。 For the behavioral model credit rating system described in claim 1, the first parameter represents the probability that the sub-factor parameter corresponds to the occurrence of the overrun situation. 如請求項1所述之行為模式信評系統,該行為模式信評系統更包括:一權數設定模組,與該微處理器電連接,用以根據該更新權數調整該權數,並用以根據該更新第一參數調整該第一參數,其中該更新權數與該權數對應於同一該因子參數,且該更新第一參數與該第一參數對應於同一該子因子參數。 For the behavioral model credit evaluation system of claim 1, the behavioral model credit evaluation system further includes: a weight setting module, electrically connected to the microprocessor, for adjusting the weight according to the update weight, and for adjusting the weight according to the update weight Update the first parameter to adjust the first parameter, wherein the update weight and the weight correspond to the same factor parameter, and the update first parameter and the first parameter correspond to the same sub-factor parameter. 如請求項5所述之行為模式信評系統,其中該權數設定模組用於設定初始的權數、第一參數以及最大主要參數值。 The behavioral model credit rating system according to claim 5, wherein the weight setting module is used to set the initial weight, the first parameter, and the maximum main parameter value. 如請求項1所述之行為模式信評系統,該行為模式信評系統更包括:一因子參數決定模組,與該微處理器電連接,該因子參數決定模組用以設定計算該總信用評分所使用的至少一因子參數。 For the behavioral model credit rating system of claim 1, the behavioral model credit rating system further includes: a factor parameter determination module electrically connected to the microprocessor, and the factor parameter determination module is configured to calculate the total credit At least one factor parameter used for scoring. 如請求項1所述之行為模式信評系統,其中該至少一子因子參數為該受評對象所選擇的至少一因子參數。 The behavioral pattern credit evaluation system according to claim 1, wherein the at least one sub-factor parameter is at least one factor parameter selected by the subject. 如請求項1所述之行為模式信評系統,其中該因子參數為一顏色、一隨機問題、一操作習性、一消費性電子產品接收度、一社群活躍度、一金融關係或一數位足跡的至少其中之一。 The behavioral model credit rating system according to claim 1, wherein the factor parameter is a color, a random question, an operating habit, a consumer electronic product acceptance, a community activity, a financial relationship, or a digital footprint At least one of them.
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