CN101299285A - Bank abnormity draw money detector and method thereof - Google Patents
Bank abnormity draw money detector and method thereof Download PDFInfo
- Publication number
- CN101299285A CN101299285A CNA2007101792099A CN200710179209A CN101299285A CN 101299285 A CN101299285 A CN 101299285A CN A2007101792099 A CNA2007101792099 A CN A2007101792099A CN 200710179209 A CN200710179209 A CN 200710179209A CN 101299285 A CN101299285 A CN 101299285A
- Authority
- CN
- China
- Prior art keywords
- money
- network adapter
- cpu
- ram
- bank
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
A bank abnormal withdrawal detector and method thereof pertains to the financial services technology field. The detector includes: a central processing unit CPU (1), an abnormal testing algorithm (2), a random access memory RAM (3), a network adapter (4), a motherboard (5), a power supply (6), and a sealed box (7), wherein, the power supply (6) provides direct-current power supply for the motherboard (5), the network adapter (4), the CPU (1), the abnormal testing algorithm (2), and the RAM (3) are serially-arranged in sequence and directly inserted on the motherboard (5) by the slots provided on the motherboard (5); data are read by the network adapter (4) onto the RAM (3); the CPU (1) accesses data in the RAM (3) through the motherboard (5), meanwhile the CPU (1) implement the abnormal testing algorithm (2) and output the implementation results through the network adapter (4). The method is simple, which judges the withdrawal abnormal by automatic analysis of historical data and comparison of the difference between the current data and the historical data, and is easy to implement.
Description
Technical field
The invention belongs to financial services technology field, a kind of bank abnormity draw money detector and method thereof particularly are provided.This detecting device is by analyzing the bank client withdrawl deposit record, obtains the bank client pattern of withdrawing the money.When bank client when the bank debits, this detecting device can be according to client withdraw the money frequency, the withdraw the money time interval and three factors of the amount of money of withdrawing the money, the contrast client pattern of withdrawing the money, whether this withdraws the money to belong to and differs from the behavior pattern of withdrawing the money to analyze the client.Differ from the behavior pattern of withdrawing the money if belong to, then send the abnormity draw money alarm, take to carry out measure, the alarm of abnormity draw money is made corresponding response by bank clerk.
Background technology
Being extensive use of of current bank card, particularly the Internet bank is open-minded, has brought the stolen risk of cash in banks to bank client.For example, the client causes account No. and password leakage, and then causes the loss of property owing to there is not safety properly to protect oneself account No. and password.Statistics shows, in recent years, along with people use the use of opening of the increasing of automated teller unit frequency and the Internet bank, the bank card crime activity had the trend that increases.The property loss risk of how to take precautions against criminal activity, reduction bank client effectively is the significant problem that each bank and bank client are concerned about.The bank aspect is merely able to get 20,000 yuan by formulating some measures at most as regulation every bank card every day.These measures have reduced the risk that the client may suffer a loss to a certain extent, but nonetheless, for the customer, usurp if bank card takes place, and the property loss that causes is still not little.
And the feature by usurping account No. or bank card crime is exactly in case after obtaining account No. and password or producing magnetic card, will take cash as much as possible away in the shortest time.For this reason, invent the unusual intelligent detector of a kind of bank debits.This detecting device is at each bank client, by analyzing the bank client pattern of withdrawing the money, and whether belongs to abnormal behaviour according to the pattern discrimination client's that withdraws the money the behavior of withdrawing the money.Bank then can utilize testing result, handles accordingly.For example, belong to abnormal behaviour, then temporarily refuse withdrawing the money of client if withdraw the money, simultaneously, the presenting bank staff.Bank clerk then can be taked corresponding measure, confirms whether remittee's identity is legal, whether can withdraw the money with decision.Like this, judge, discern unusual before taking out by client's debt automatically, reach protection client interests, reduce the risk of the economic loss that the criminal activity of being correlated with brings to bank client.
Only by the total charge number of withdrawing the money a fixing day is set, limited subscriber is withdrawn the money by bank card, though this mode is simple, can not effectively stop abnormal behaviours such as stolen in bank debits at present.
Summary of the invention
The object of the present invention is to provide a kind of bank abnormity draw money detector and method thereof, effectively stoped abnormal behaviours such as stolen.
Detecting device of the present invention comprises: central processor CPU 1, abnormality detection algorithm 2, random access storage device RAM3, network adapter 4, mainboard 5, power supply 6 and seal box 7.Wherein: power supply 6 provides direct supply for mainboard 5, and network adapter 4, CPU1, abnormality detection algorithm 2, RAM3 be series arrangement successively, and the slot that provides by mainboard 4 directly is inserted on the mainboard 4.Data read among the RAM3 by network adapter 4; By mainboard 4, CPU1 can visit the data among the RAM3, and simultaneously, CPU1 can execute exception detection algorithm 2, and with execution result by network adapter 4 outputs.CPU1, abnormality detection algorithm 2, random access storage device RAM3, network adapter 4, mainboard 5 and power supply 6 are sealed in the seal box 7, and in addition, the transmission line interface of network adapter 4 is exposed to seal box 7 right sides, use for connecting outside netting twine.The interface of power supply 6 and outside is exposed to the left side of seal box, uses for connecting the external cable lead.
Bank abnormity draw money of the present invention detects step: behind the amount of money that client's input will be withdrawn the money, CPU1 carries out data and obtains instruction, by network adapter 4 Bank Account Number and the amount of money of withdrawing the money are read among the RAM3, simultaneously, obtaining client's history data messages such as the amount of money, date of withdrawing the money by network adapter 4 is read among the RAM3.After finishing data read, CPU1 execute exception detection algorithm 2, and from RAM3, read required information.After CPU1 executes the abnormality detection algorithm, be abnormity draw money if definite this withdrawn the money, then CPU1 execution data output instruction is exported the result by network adapter 4.Bank clerk, is taked the corresponding precautionary measures, thereby can be stoped abnormity draw money efficiently according to the flow process that bank formulates according to the output result.
The present invention obtains the behavior pattern that the client normally withdraws the money by analyze the client amount of money of normally withdrawing the money and the frequency of withdrawing the money at every turn.When withdrawing the money during the amount of money of client input, the number of times that the client who obtains according to the withdraw the money amount of money and statistics withdrew the money the same day mates with client's model of normally withdrawing the money, and judges that this withdraws the money whether to belong to normally to withdraw the money.Do not withdraw the money if do not belong to normally, then suspend the client and withdraw the money, report to the police to bank clerk simultaneously.Like this, withdraw the money by the client that the pattern of behavior is concluded and the automatic detection of the behavior of withdrawing the money, add the manual intervention of bank clerk, reach reduction because of account No. or the stolen purpose of bringing economic loss to the client of bank card.
Principle of the present invention is: for an account No., with client's amount of money of withdrawing the money at every turn, add up to withdraw the money the number of times and the interval fate of withdrawing the money for twice day as analytical factor, when withdrawing the money incident, the number of respectively this being withdrawn the money, this withdraw the money number of times of withdrawing the money on the same day and this are withdrawn the money and the last time withdraws the money at interval that fate compares with corresponding historical data.For each factor, comparative result has situation in three, that is: 1) and suitable with historical data; 2) differ bigger with historical data, and lower than historical data; 3) differ less with historical data, and than historical data height.Situation is the abnormity draw money that is worth bank to pay close attention in the 3rd, therefore, if comparative result belongs to situation in the 3rd, then defines this and withdraws the money and belong to abnormity draw money.
Advantage of the present invention is: 1) the present invention relates to the multifactor of abnormity draw money judgement, compares with the single amount of money factor of withdrawing the money of present employing, and more reasonable, more practical; 2) dynamic of method and dirigibility.The present invention be directed to the pattern of self the withdrawing the money judgement that each account is carried out, need not the factor that other is difficult to measure; 3) method letter, by automatic analysis of history data, relatively the size of the difference between current data and historical data is judged withdraw the money unusual, is easy to realize.
Description of drawings.
Fig. 1 is that bank abnormity draw money detector of the present invention is formed synoptic diagram.Wherein, central processor CPU 1, abnormality detection algorithm 2, random access storage device RAM3, network adapter 4, mainboard 5, power supply 6 and seal box 7.
Fig. 2 is a process flow diagram of the present invention.Comprise unusual judgement to withdraw the money the amount of withdrawing the money, day number of times, the time interval of withdrawing the money.Wherein bank debits abnormality detection factor comprises three, the amount of money of promptly withdrawing the money, day accumulative total withdraw the money number of times, withdraw the money the time interval for twice; Parameter comprises in the abnormality detection algorithm, 1, withdraw the money the amount of money when whether unusual in judgement, and parameter is made as the withdraw the money standard deviation of amount record of 3 times history; 2, judging that whether unusual day accumulative total withdraw the money number of times when, parameter is set to the withdraw the money standard deviation of number of times record of 2 times historical day accumulative total; 3, when judging that the time interval of withdrawing the money for twice is whether unusual, parameter is set to the standard deviation of 1.5 times adjacent twice time interval record of withdrawing the money of corresponding history.
Embodiment
Fig. 1 and Fig. 2 are one embodiment of the present invention a kind of embodiments of the present invention.
Detecting device comprises central processor CPU 1, abnormality detection algorithm 2, random access storage device RAM3, network adapter 4, mainboard 5, power supply 6 and seal box 7.Central processor CPU 1, abnormality detection algorithm 2, random access storage device RAM3, network adapter 4, mainboard 5, power supply 6 and seal box 7.: power supply 6 provides direct supply for mainboard 5, and network adapter 4, CPU1, abnormality detection algorithm 2, RAM3 be series arrangement successively, and the slot that provides by mainboard 4 directly is inserted on the mainboard 4.Data read among the RAM3 by network adapter 4; By mainboard 4, CPU1 can visit the data among the RAM3, and simultaneously, CPU1 can execute exception detection algorithm 2, and with execution result by network adapter 4 outputs.CPU1, abnormality detection algorithm 2, random access storage device RAM3, network adapter 4, mainboard 5 and power supply 6 are sealed in the seal box 7, and in addition, the transmission line interface of network adapter 4 is exposed to seal box 7 right sides, use for connecting outside netting twine.The interface of power supply 6 and outside is exposed to the left side of seal box, uses for connecting the external cable lead.
Behind the amount of money that client's input will be withdrawn the money, CPU1 carries out data and obtains instruction, by network adapter 4 Bank Account Number and the amount of money of withdrawing the money are read among the RAM3, simultaneously, obtained client's history data messages such as the amount of money, date of withdrawing the money by network adapter 4 and be read among the RAM3.After finishing data read, CPU1 execute exception detection algorithm 2, and from RAM3, read required information.After CPU1 executes the abnormality detection algorithm, be abnormity draw money if definite this withdrawn the money, then CPU1 execution data output instruction is exported the result by network adapter 4.Bank clerk, is taked the corresponding precautionary measures, thereby can be stoped abnormity draw money efficiently according to the flow process that bank formulates according to the output result.
Fig. 2 is a kind of embodiment and the flow process of abnormality detection algorithm of the present invention.
1, at first, want the number of withdrawing the money that takes out, represent with a by the client, and with unit as unit, for example the client wants to get 1000 yuan, so a=1000;
2, then calculate at every turn withdrew the money the in the past average of number of account, represent with Ma, and with unit as unit.The amount of money of withdrawing the money in the past by the account that adds up obtains divided by the number of times of withdrawing the money.For example, reached money 10 times if account is crossed, the amount of money that adds up to withdraw the money adds up to 100000 yuan, and the average of the number of then passing by at every turn to withdraw the money is Ma=10000.
3, calculate the standard variance of the amount of money of withdrawing the money in the past, represent with Sa, and with unit as unit.Its computing method are to establish the volume of at every turn withdrawing the money, with A
iExpression, the past average Ma that at every turn withdraws the money, then
4, judge that whether this amount of money a that desires to withdraw the money adds 3 times withdraw the money amount of money standard variance, i.e. Ma+3Sa greater than the past average of withdrawing the money at every turn.If a＞=Ma+3Sa, then this is withdrawn the money and belongs to abnormity draw money, enters step 13; Otherwise, enter step 5;
5, calculate this and withdraw the money, represent with b apart from the time interval of withdrawing the money last time, and with the sky as unit, for example, if this withdraw the money apart from withdrew the money last time in time interval be 20 days, b=20. then
6, calculate in the past this account number time-interval averaging value of at every turn withdrawing the money, represent with Mb, with the sky as unit;
7, calculate the standard variance in the time interval of withdrawing the money in the past, represent with Sb, and with the sky as unit.Its computing method are to establish at every turn and withdraw the money interval time, with B
iExpression, the average Mb at interval that withdraws the money in the past, then
8, whether judge that this is withdrawn the money deducts the standard variance in 1.5 times of time intervals of withdrawing the money in the past, i.e. Mb-1.5Sb less than the past time interval average of withdrawing the money at every turn apart from the time interval b that withdrew the money last time.If b＜=Mb-1.5Sb, then this is withdrawn the money and belongs to abnormity draw money, enters step 13; Otherwise, enter step 9;
9, calculating this which time of withdrawing the money the same day for this account number of withdrawing the money and withdraw the money, represent with c, for example, is to withdraw the money for the 3rd time on account same day if this is withdrawn the money, then c=3.
10, calculate the per day time numerical value of withdrawing the money of this account number in the past, represent with Mc; This computing method basis is withdrawn the money total degree divided by the fate that has the incident of withdrawing the money to take place.For example, a number of the account was in past 1 year, and the client was only getting 3 times money, then Mc=3/1=3 in some day;
11, calculate the standard variance that this number of the account is in the past on average withdrawn the money time every day, represent with Sc.Its computing method are to establish the number of times of withdrawing the money day, with C
iExpression, the number of times average Mc that withdraws the money day, then
12, judge that whether this number of times c that withdraws the money is greater than crossing the standard variance that the number of times average of withdrawing the money in past days adds 2 times the per day number of times of withdrawing the money, i.e. Mc+2Sc.If c＞=Mc+2Sc, then this is withdrawn the money and belongs to abnormity draw money; Otherwise, enter step 14;
13, the output abnormality information of withdrawing the money, the prompting abnormity draw money need arouse attention and manual intervention;
14, normally withdraw the money, do not export any information.
Claims (4)
1, a kind of bank abnormity draw money detector is characterized in that, detecting device comprises: central processor CPU (1), abnormality detection algorithm (2), random access storage device RAM (3), network adapter (4), mainboard (5), power supply (6), seal box (7); Power supply (6) provides direct supply for mainboard (5), and network adapter (4), CPU (1), abnormality detection algorithm (2), RAM (3) be series arrangement successively, and the slot that provides by mainboard (4) directly is inserted on the mainboard (4); Data read among the RAM (3) by network adapter (4); By mainboard (4), the data among CPU (1) the visit RAM (3), simultaneously, CPU (1) execute exception detection algorithm (2), and execution result is passed through network adapter (4) export.
According to the described bank abnormity draw money detector of claim 1, it is characterized in that 2, CPU (1), abnormality detection algorithm (2), random access storage device RAM (3), network adapter (4), mainboard (5) and power supply (6) are sealed in the seal box (7).
According to the described bank abnormity draw money detector of claim 2, it is characterized in that 3, the transmission line interface of network adapter (4) is exposed to seal box (7) right side, use for connecting outside netting twine; The interface of power supply (6) and outside is exposed to the left side of seal box, uses for connecting the external cable lead.
4, a kind of method that adopts the described detecting device of claim 1 to detect bank abnormity draw money, it is characterized in that, the detection step is: behind the amount of money that client's input will be withdrawn the money, CPU (1) carries out data and obtains instruction, by network adapter (4) Bank Account Number and the amount of money of withdrawing the money are read among the RAM (3), simultaneously, obtaining client's history data messages such as the amount of money, date of withdrawing the money by network adapter (4) is read among the RAM (3); After finishing data read, CPU (1) execute exception detection algorithm (2), and from RAM (3), read required information; After CPU (1) executes the abnormality detection algorithm, determine that this is withdrawn the money and be abnormity draw money, then CPU (1) carry out data output instruction with the result by network adapter (4) output.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNA2007101792099A CN101299285A (en) | 2007-12-11 | 2007-12-11 | Bank abnormity draw money detector and method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNA2007101792099A CN101299285A (en) | 2007-12-11 | 2007-12-11 | Bank abnormity draw money detector and method thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN101299285A true CN101299285A (en) | 2008-11-05 |
Family
ID=40079103
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CNA2007101792099A Pending CN101299285A (en) | 2007-12-11 | 2007-12-11 | Bank abnormity draw money detector and method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101299285A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103956007A (en) * | 2014-04-27 | 2014-07-30 | 王美金 | Bank abnormal condition detection system based on mobile phone acceleration sensor and gyroscope |
| CN106325744A (en) * | 2016-08-23 | 2017-01-11 | 深圳怡化电脑股份有限公司 | Interaction method and device of financial self-service equipment |
| CN106340138A (en) * | 2016-08-23 | 2017-01-18 | 深圳怡化电脑股份有限公司 | Transaction behavior detection method and device |
| WO2017193290A1 (en) * | 2016-05-10 | 2017-11-16 | 深圳怡化电脑股份有限公司 | Service processing method and system for use in self-service terminal |
| CN109033468A (en) * | 2018-08-31 | 2018-12-18 | 阿里巴巴集团控股有限公司 | The processing method and processing device of resource change |
| CN109660529A (en) * | 2018-12-06 | 2019-04-19 | 深圳蓝贝科技有限公司 | Safety wind control method, apparatus, vending machine and system for vending machine |
-
2007
- 2007-12-11 CN CNA2007101792099A patent/CN101299285A/en active Pending
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103956007A (en) * | 2014-04-27 | 2014-07-30 | 王美金 | Bank abnormal condition detection system based on mobile phone acceleration sensor and gyroscope |
| CN103956007B (en) * | 2014-04-27 | 2016-06-15 | 王美金 | Bank abnormity situation detection system based on mobile phone acceleration sensor and gyroscope |
| WO2017193290A1 (en) * | 2016-05-10 | 2017-11-16 | 深圳怡化电脑股份有限公司 | Service processing method and system for use in self-service terminal |
| CN105993036B (en) * | 2016-05-10 | 2018-12-11 | 深圳怡化电脑股份有限公司 | A kind of method for processing business and system of self-aided terminal |
| CN106325744A (en) * | 2016-08-23 | 2017-01-11 | 深圳怡化电脑股份有限公司 | Interaction method and device of financial self-service equipment |
| CN106340138A (en) * | 2016-08-23 | 2017-01-18 | 深圳怡化电脑股份有限公司 | Transaction behavior detection method and device |
| CN106340138B (en) * | 2016-08-23 | 2019-08-27 | 深圳怡化电脑股份有限公司 | A kind of trading activity detection method and device |
| CN106325744B (en) * | 2016-08-23 | 2019-10-11 | 深圳怡化电脑股份有限公司 | A kind of financial self-service equipment exchange method and device |
| CN109033468A (en) * | 2018-08-31 | 2018-12-18 | 阿里巴巴集团控股有限公司 | The processing method and processing device of resource change |
| CN109033468B (en) * | 2018-08-31 | 2022-09-16 | 创新先进技术有限公司 | Resource change processing method and device |
| CN109660529A (en) * | 2018-12-06 | 2019-04-19 | 深圳蓝贝科技有限公司 | Safety wind control method, apparatus, vending machine and system for vending machine |
| CN109660529B (en) * | 2018-12-06 | 2021-10-26 | 深圳蓝贝科技有限公司 | Safety air control method and device for vending machine, vending machine and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101299285A (en) | Bank abnormity draw money detector and method thereof | |
| CN103745538B (en) | The cipher code protection method of finance account and system | |
| TW201723967A (en) | Financial terminal security system and financial terminal security method | |
| CN105993036B (en) | A kind of method for processing business and system of self-aided terminal | |
| CN105809448A (en) | Account transaction clustering method and system thereof | |
| CN109447496A (en) | Electricity stealing determination method and terminal device | |
| Yang et al. | DBSCAN clustering algorithm applied to identify suspicious financial transactions | |
| CN111243156A (en) | Transformer substation safety access and operation and maintenance system | |
| CN106408751B (en) | A kind of clear of atm device is made an inventory of goods in a warehouse method and system | |
| CN203165071U (en) | Cash payment and management device | |
| CN205751065U (en) | A kind of ATM Self-Service point supervising device | |
| CN107358759A (en) | The clear method and system and terminal device of financial self-service equipment, storage medium | |
| US11880471B2 (en) | Password hardcoding checking method and apparatus based on PCA, and medium | |
| CN113313874B (en) | Cash counting method and device | |
| CN115310982A (en) | Electricity larceny prevention early warning data analysis method | |
| CN114596089A (en) | ATM transaction method, system, terminal and medium supporting digital currency | |
| TWI680438B (en) | Method of monitoring atm and atm using the same | |
| CN114125004B (en) | Method, device and server for supervising cash security of banking outlets | |
| CN110942568A (en) | Intelligent detection method and device for illegal bank note adding between bank note adding | |
| Gupta | Using of Machine Learning Techniques to detect Credit Card Frauds | |
| TWM563049U (en) | Automatic teller machine with monitoring function | |
| CN117436820B (en) | Control method and system based on artificial intelligence | |
| CN116720863A (en) | Transaction risk identification method and device based on banknote crown word number | |
| CN116628613A (en) | Block chain abnormal transaction detection method, system, equipment and storage medium | |
| CN116739726A (en) | Account data analysis method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C02 | Deemed withdrawal of patent application after publication (patent law 2001) | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Open date: 20081105 |