WO2023100846A1 - Account monitoring device, account monitoring method, and non-transitory computer-readable recording medium - Google Patents
Account monitoring device, account monitoring method, and non-transitory computer-readable recording medium Download PDFInfo
- Publication number
- WO2023100846A1 WO2023100846A1 PCT/JP2022/043888 JP2022043888W WO2023100846A1 WO 2023100846 A1 WO2023100846 A1 WO 2023100846A1 JP 2022043888 W JP2022043888 W JP 2022043888W WO 2023100846 A1 WO2023100846 A1 WO 2023100846A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- items
- withdrawal
- account monitoring
- deposit
- account
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/08—Payment architectures
- G06Q20/10—Payment architectures specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/02—Banking, e.g. interest calculation or account maintenance
Definitions
- the present invention relates to an account monitoring device, an account monitoring method, and a non-temporary computer-readable recording medium.
- Patent Literature 1 describes a system for preventing unauthorized withdrawal of cash.
- This system has a financial system server and a withdrawal reservation server.
- the financial system server comprises invalidation means for invalidating the withdrawal operation, and invalidation canceling means for canceling the invalidation of the withdrawal operation when the withdrawal is permitted in the withdrawal approval/disapproval notification from the withdrawal reservation server.
- the withdrawal reservation server stores the contact information of the approver.
- the withdrawal reservation server also automatically sends a notification as to whether or not the withdrawal is approved to the approver, and receives a response of approval or disapproval from the approver. Then, the withdrawal reservation server confirms the contents of the reply, determines whether the withdrawal is permitted or not, and transmits a withdrawal permission notification describing whether the withdrawal is permitted or not to the financial institution system server.
- Another method of embezzlement is to make unauthorized transfers from accounts.
- One of the objects of the present invention is to accurately detect this fraudulent transfer.
- data acquisition means for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account; determination means for determining whether the deposit/withdrawal data satisfies rules set for each of the plurality of items; output means for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
- a computer is configured to: a data acquisition process for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account; a judgment process for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items; an output process of performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number; There is provided an account monitoring method for performing
- the computer is configured to: a data acquisition function for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account; a judgment function for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items; an output function for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
- a non-transitory computer readable recording medium is provided for recording a program for providing a.
- fraudulent transfers from accounts can be accurately detected.
- FIG. 1 is a diagram showing an example of the functional configuration of the account monitoring device 10 according to the embodiment.
- the account monitoring device 10 detects fraudulent depositing or withdrawal processing for accounts of financial institutions. Examples of financial institutions are, but are not limited to, banks and securities firms. In addition, the holder of the account is a corporation, corporation, limited company, etc., but is not limited to these.
- the account monitoring device 10 has an acquisition unit 110, a determination unit 120, and an output unit 130, and can use the information stored in the storage unit 140.
- the storage unit 140 is part of the account monitoring device 10 in the example shown in this figure, it may be located outside the account monitoring device 10 .
- the acquisition unit 110 acquires deposit/withdrawal data.
- the deposit/withdrawal data is data relating to deposits or withdrawals of the account being monitored. Specifically, the deposit/withdrawal data is generated each time a deposit is made to the account and each time a withdrawal is made from the account.
- the deposit/withdrawal data includes, for example, at least one of deposit/withdrawal category, date (for example, month and day), amount, channel, and withdrawal destination identification information.
- the channel is the designation method of the payee. Concrete examples of the channel are "payment on demand in ATM or Internet transactions", "payment destinations are specified using a pre-registered list in ATM or Internet transactions", and “payment by window”. ”, etc.
- the withdrawal destination identification information includes information for identifying the account of the transaction partner (for example, transfer destination or transfer source), such as bank name, branch name, and account number.
- the withdrawal destination identification information may further include the name of the account.
- the acquisition unit 110 may acquire the deposit/withdrawal data from, for example, a server managed by a financial institution, or may acquire the deposit/withdrawal data from a removable medium.
- the determination unit 120 determines whether or not the deposit/withdrawal data satisfies rules set for each of a plurality of items. This rule is stored in the storage unit 140 . Details of the rules stored in the storage unit 140 will be described later with reference to other drawings.
- the output unit 130 performs a predetermined output when the rule is satisfied for items equal to or greater than the first reference number. In other words, whether or not a predetermined output is performed is determined by a majority decision.
- the first reference number is, for example, half or half+1, but may be less than half or half+2 or more.
- the predetermined output indicates that the deposit/withdrawal data being processed is highly likely to be a fraudulent transaction. Predetermined output may be performed, for example, to a terminal managed by the financial institution (or its branch) of the account, or to a terminal of the manager of the account linked to the deposit/withdrawal data may be done.
- the predetermined output preferably includes at least a portion (preferably all) of the deposit/withdrawal data.
- the acquisition unit 110 may acquire the deposit/withdrawal data in a batch format, or may acquire the deposit/withdrawal data in real time. In the former case, the acquisition unit 110 may collectively acquire a plurality of deposit/withdrawal data. In this case, the determination unit 120 and the output unit 130 perform the above-described processing for each of the plurality of deposit/withdrawal data.
- FIG. 2 is a diagram showing an example of rules stored in the storage unit 140.
- subrules are set for each of a plurality of items included in the deposit/withdrawal data.
- the number of subrules is, for example, 5 or more per item, but may be 10 or more.
- the rule for each item described above is that the number of sub-rules equal to or greater than the second reference number is satisfied in the item.
- the second reference number is, for example, half (half + 0.5 if the parameter is an odd number) or half + 1, but may be less than half or half + 2 or more. In other words, whether or not a rule is met is also determined by majority decision.
- the amount subrule indicates the range of amounts in a normal transaction when the transfer source of the deposit has transactions in the past and the date and channel satisfy predetermined conditions.
- the date subrule indicates the range of dates in normal transactions when the deposit is a transaction, the transfer source has a transaction in the past, and the amount and channel satisfy predetermined conditions.
- Subrules may be set manually or may be generated using machine learning. In the latter case, for example, logical thinking AI (Artificial Intelligence) is used as machine learning, but it is not limited to this.
- FIG. 3 is a diagram showing a hardware configuration example of the account monitoring device 10. As shown in FIG. Account monitoring device 10 has bus 1010 , processor 1020 , memory 1030 , storage device 1040 , input/output interface 1050 and network interface 1060 .
- the bus 1010 is a data transmission path for the processor 1020, the memory 1030, the storage device 1040, the input/output interface 1050, and the network interface 1060 to exchange data with each other.
- the method of connecting processors 1020 and the like to each other is not limited to bus connection.
- the processor 1020 is a processor realized by a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or the like.
- the memory 1030 is a main memory implemented by RAM (Random Access Memory) or the like.
- the storage device 1040 is a removable medium such as a HDD (Hard Disk Drive), an SSD (Solid State Drive), a memory card, or an auxiliary storage device realized by a ROM (Read Only Memory).
- the storage device 1040 stores program modules that implement each function of the account monitoring device 10 (for example, the acquisition unit 110, the determination unit 120, and the output unit 130). Each function corresponding to the program module is realized by the processor 1020 reading each program module into the memory 1030 and executing it.
- the storage device 1040 also functions as the storage section 140 .
- the input/output interface 1050 is an interface for connecting the account monitoring device 10 and various input/output devices.
- the network interface 1060 is an interface for connecting the account monitoring device 10 to the network.
- This network is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network).
- a method for connecting the network interface 1060 to the network may be a wireless connection or a wired connection.
- Acquisition unit 110 of account monitoring device 10 acquires deposit/withdrawal data via network interface 1060, for example.
- FIG. 4 is a flowchart showing an example of processing performed by the account monitoring device 10.
- the acquisition unit 110 of the account monitoring device 10 acquires deposit/withdrawal data (step S10).
- the determination unit 120 of the account monitoring device 10 specifies the number of matching sub-rules for each item included in the deposit/withdrawal data (step S20).
- the determination unit 120 identifies the number of items in which the number of matched subrules exceeds the second reference value (step S30).
- the output unit 130 performs a predetermined output (step S50). In other words, if the deposit/withdrawal data is recognized as an exceptional transaction in a plurality of items, the output unit 130 determines that the transfer indicated by the deposit/withdrawal data is highly likely to be fraudulent.
- the predetermined output indicates that the deposit/withdrawal data being processed (including both withdrawals and deposits) is highly likely to be an unauthorized transaction.
- the output destination of the predetermined output is, for example, the terminal of the manager of the account. Therefore, by recognizing the output from the output unit 130, the administrator can recognize that there is a possibility that fraudulent transactions, such as embezzlement, have been made.
- rules for detecting exceptional transactions are set for each item included in the deposit/withdrawal data. Then, the account monitoring device 10 uses the number of items that match this rule to detect deposit/withdrawal data that are highly likely to be fraudulent transactions. Therefore, by using the account monitoring device 10, fraudulent transfers can be detected with high accuracy.
- data acquisition means for acquiring deposit/withdrawal data relating to deposits or withdrawals from an account and having a plurality of items; determination means for determining whether the deposit/withdrawal data satisfies rules set for each of the plurality of items; output means for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number; account monitoring device.
- a plurality of subrules are set for each of the plurality of items, The account monitoring device, wherein the rule is that a second criterion number or more of the sub-rules are satisfied.
- the account monitoring device wherein the plurality of sub-rules are generated using machine learning. 4. In the account monitoring device according to 2 or 3 above, The account monitoring device, wherein the sub-rules indicate exceptional deposits or withdrawals. 5. In the account monitoring device according to any one of 1 to 4 above, The account monitoring device, wherein the items include at least one of classification of deposit and withdrawal, amount, date, designation method of transfer destination, channel, and withdrawal destination identification information. 6.
- the computer a data acquisition process for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account; a judgment process for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items; an output process of performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number; account monitoring method. 7.
- account monitoring method described in 6 above, A plurality of subrules are set for each of the plurality of items, The method of account monitoring, wherein the rule is that a second criterion number or more of the sub-rules are satisfied.
- the account monitoring method wherein the plurality of sub-rules are generated using machine learning. 9. In the account monitoring method according to 7 or 8 above, The account monitoring method, wherein the sub-rules indicate exceptional deposits or withdrawals. 10. In the account monitoring method according to any one of 6 to 9 above, The account monitoring method, wherein the items include at least one of deposit/withdrawal category, amount, date, transfer destination designation method, channel, and withdrawal destination identification information. 11.
- a data acquisition function for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account; a judgment function for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items; an output function for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
- a program that has 12. 11.
- a plurality of subrules are set for each of the plurality of items, The program, wherein the rule is that a second criterion number or more of the subrules are satisfied.
- the program, wherein the plurality of sub-rules are generated using machine learning. 14.
- the subrule indicates an exceptional deposit or withdrawal.
- the items include at least one of classification of deposit and withdrawal, amount, date, transfer destination designation method, channel, and withdrawal destination identification information.
Landscapes
- Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- Technology Law (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
An account monitoring device (10) comprises an acquisition unit (110), a determination unit (120), and an output unit (130). The acquisition unit (110) acquires deposit/withdrawal data including a plurality of items, related to deposit or withdrawal in an account. The items include, for example, at least one of: a classification of deposit and withdrawal; an amount; a date; a method of specifying a remittance destination; a channel; and withdrawal destination identification information. The determination unit (120) determines whether or not the deposit/withdrawal data satisfies a rule defined for each of the plurality of items. The output unit (130) carries out predetermined output when the rule is satisfied for at least a first reference number of items.
Description
本発明は、口座監視装置、口座監視方法、及び非一時的なコンピュータ可読記録媒体に関する。
The present invention relates to an account monitoring device, an account monitoring method, and a non-temporary computer-readable recording medium.
企業に勤務している人による不正の一つに、横領がある。横領の手口の一つに、現金の不正な引出しがある。これに対して特許文献１には、現金の不正な引出しを防止するためのシステムが記載されている。このシステムは、金融システムサーバと出金予約サーバを有している。金融システムサーバは、出金操作を無効とする無効手段と、出金予約サーバからの出金可否通知における出金が可であるときには出金操作の無効を解除する無効解除手段と、を備えている。出金予約サーバは、承認者の連絡先を記憶する。また出金予約サーバは、出金を承認するか否かについての通知を自動的に承認者へ発送し、かつ、承認者からの承認または否認の返答を受信する。そして出金予約サーバは、返答内容を確認して出金の可否を判定し、出金の可否何れかを記述した出金可否通知を金融機関システムサーバに送信する。
One of the frauds committed by people working for a company is embezzlement. One of the methods of embezzlement is illegal withdrawal of cash. On the other hand, Patent Literature 1 describes a system for preventing unauthorized withdrawal of cash. This system has a financial system server and a withdrawal reservation server. The financial system server comprises invalidation means for invalidating the withdrawal operation, and invalidation canceling means for canceling the invalidation of the withdrawal operation when the withdrawal is permitted in the withdrawal approval/disapproval notification from the withdrawal reservation server. there is The withdrawal reservation server stores the contact information of the approver. The withdrawal reservation server also automatically sends a notification as to whether or not the withdrawal is approved to the approver, and receives a response of approval or disapproval from the approver. Then, the withdrawal reservation server confirms the contents of the reply, determines whether the withdrawal is permitted or not, and transmits a withdrawal permission notification describing whether the withdrawal is permitted or not to the financial institution system server.
横領の他の手口として、口座から不正な振り込みを行う方法がある。本発明の目的の一例は、この不正な振り込みを精度よく検出することにある。
Another method of embezzlement is to make unauthorized transfers from accounts. One of the objects of the present invention is to accurately detect this fraudulent transfer.
本発明の一態様によれば、口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得手段と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断手段と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力手段と、
を備える口座監視装置が提供される。 According to one aspect of the present invention, data acquisition means for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account;
determination means for determining whether the deposit/withdrawal data satisfies rules set for each of the plurality of items;
output means for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
There is provided an account monitoring device comprising:
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断手段と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力手段と、
を備える口座監視装置が提供される。 According to one aspect of the present invention, data acquisition means for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account;
determination means for determining whether the deposit/withdrawal data satisfies rules set for each of the plurality of items;
output means for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
There is provided an account monitoring device comprising:
本発明の一態様によれば、コンピュータが、
口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得処理と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断処理と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力処理と、
を行う口座監視方法が提供される。 According to one aspect of the invention, a computer is configured to:
a data acquisition process for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account;
a judgment process for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items;
an output process of performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
There is provided an account monitoring method for performing
口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得処理と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断処理と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力処理と、
を行う口座監視方法が提供される。 According to one aspect of the invention, a computer is configured to:
a data acquisition process for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account;
a judgment process for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items;
an output process of performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
There is provided an account monitoring method for performing
本発明の一態様によれば、コンピュータに、
口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得機能と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断機能と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力機能と、
を持たせるプログラムを記録する、非一時的なコンピュータ可読記録媒体が提供される。 According to one aspect of the invention, the computer is configured to:
a data acquisition function for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account;
a judgment function for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items;
an output function for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
A non-transitory computer readable recording medium is provided for recording a program for providing a.
口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得機能と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断機能と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力機能と、
を持たせるプログラムを記録する、非一時的なコンピュータ可読記録媒体が提供される。 According to one aspect of the invention, the computer is configured to:
a data acquisition function for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account;
a judgment function for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items;
an output function for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
A non-transitory computer readable recording medium is provided for recording a program for providing a.
本発明の一態様によれば、口座からの不正な振り込みを精度よく検出できる。
According to one aspect of the present invention, fraudulent transfers from accounts can be accurately detected.
以下、本発明の実施の形態について、図面を用いて説明する。尚、すべての図面において、同様な構成要素には同様の符号を付し、適宜説明を省略する。
Embodiments of the present invention will be described below with reference to the drawings. In addition, in all the drawings, the same constituent elements are denoted by the same reference numerals, and the description thereof will be omitted as appropriate.
図１は、実施形態に係る口座監視装置１０の機能構成の一例を示す図である。口座監視装置１０は、金融機関の口座に対する、不正と思われる入金処理又は出金処理を検出する。金融機関の一例は銀行及び証券会社であるが、これらに限定されない。また、口座の名義人は法人、企業、又は有限会社などであるが、これらに限定されない。
FIG. 1 is a diagram showing an example of the functional configuration of the account monitoring device 10 according to the embodiment. The account monitoring device 10 detects fraudulent depositing or withdrawal processing for accounts of financial institutions. Examples of financial institutions are, but are not limited to, banks and securities firms. In addition, the holder of the account is a corporation, corporation, limited company, etc., but is not limited to these.
口座監視装置１０は、取得部１１０、判断部１２０、及び出力部１３０を有しており、記憶部１４０が記憶している情報を利用可能である。本図に示す例において、記憶部１４０は口座監視装置１０の一部となっているが、口座監視装置１０の外部に位置していてもよい。
The account monitoring device 10 has an acquisition unit 110, a determination unit 120, and an output unit 130, and can use the information stored in the storage unit 140. Although the storage unit 140 is part of the account monitoring device 10 in the example shown in this figure, it may be located outside the account monitoring device 10 .
取得部１１０は、入出金データを取得する。入出金データは、監視対象となっている口座の入金又は出金に関するデータである。詳細には、入出金データは、口座への入金が行われるたびに生成されるとともに、口座からの出金が行われるたびに生成される。入出金データは、例えば、入金及び出金の区分、日付（例えば月日）、金額、チャネル、及び出金先特定情報の少なくとも一つを含んでいる。ここでチャネルは、振込先の指定方法である。チャネルの具体例は、「ＡＴＭやインターネット取引において都度振込である」、「ＡＴＭやインターネット取引において予め登録されているリストを用いて振込先が指定されている」、及び、「窓口による振り込みである」、などである。また出金先特定情報は、取引先（例えば振込先又は振込元）の口座を特定する情報、例えば銀行名、支店名、及び口座番号を含んでいる。出金先特定情報は、さらに、その口座の名義を含んでいてもよい。取得部１１０は、例えば金融機関が管理しているサーバから入出金データを取得してもよいし、リムーバブルメディアから入出金データを取得してもよい。
The acquisition unit 110 acquires deposit/withdrawal data. The deposit/withdrawal data is data relating to deposits or withdrawals of the account being monitored. Specifically, the deposit/withdrawal data is generated each time a deposit is made to the account and each time a withdrawal is made from the account. The deposit/withdrawal data includes, for example, at least one of deposit/withdrawal category, date (for example, month and day), amount, channel, and withdrawal destination identification information. Here, the channel is the designation method of the payee. Concrete examples of the channel are "payment on demand in ATM or Internet transactions", "payment destinations are specified using a pre-registered list in ATM or Internet transactions", and "payment by window". ”, etc. Also, the withdrawal destination identification information includes information for identifying the account of the transaction partner (for example, transfer destination or transfer source), such as bank name, branch name, and account number. The withdrawal destination identification information may further include the name of the account. The acquisition unit 110 may acquire the deposit/withdrawal data from, for example, a server managed by a financial institution, or may acquire the deposit/withdrawal data from a removable medium.
判断部１２０は、入出金データが、複数の項目別に設定されたルールを満たすか否かを判断する。このルールは、記憶部１４０に記憶されている。記憶部１４０が記憶しているルールの詳細については、他の図を用いて後述する。
The determination unit 120 determines whether or not the deposit/withdrawal data satisfies rules set for each of a plurality of items. This rule is stored in the storage unit 140 . Details of the rules stored in the storage unit 140 will be described later with reference to other drawings.
出力部１３０は、第１基準数以上の項目においてルールが満たされている場合に、所定の出力を行う。すなわち所定の出力が行われるか否かは、多数決的な考え方により判断されている。第１基準数は、例えば半数又は半数＋１であるが、半数より少なくてもよいし、半数＋２以上であってもよい。所定の出力は、処理対象となっている入出金データが不正な取引である可能性が高いことを示している。所定の出力は、例えばその口座の金融機関（さらにはその支店）が管理している端末に対して行われてもよいし、その入出金データに紐づいた口座の管理者の端末に対して行われてもよい。所定の出力は、入出金データの少なくとも一部（好ましくは全部）を含んでいるのが好ましい。
The output unit 130 performs a predetermined output when the rule is satisfied for items equal to or greater than the first reference number. In other words, whether or not a predetermined output is performed is determined by a majority decision. The first reference number is, for example, half or half+1, but may be less than half or half+2 or more. The predetermined output indicates that the deposit/withdrawal data being processed is highly likely to be a fraudulent transaction. Predetermined output may be performed, for example, to a terminal managed by the financial institution (or its branch) of the account, or to a terminal of the manager of the account linked to the deposit/withdrawal data may be done. The predetermined output preferably includes at least a portion (preferably all) of the deposit/withdrawal data.
取得部１１０は、バッチ形式で入出金データを取得してもよいし、リアルタイムで入出金データを取得してもよい。前者の場合、取得部１１０は、複数の入出金データを纏めて取得してもよい。この場合、判断部１２０及び出力部１３０は、複数の入出金データ別に、上記した処理を行う。
The acquisition unit 110 may acquire the deposit/withdrawal data in a batch format, or may acquire the deposit/withdrawal data in real time. In the former case, the acquisition unit 110 may collectively acquire a plurality of deposit/withdrawal data. In this case, the determination unit 120 and the output unit 130 perform the above-described processing for each of the plurality of deposit/withdrawal data.
図２は、記憶部１４０が記憶しているルールの一例を示す図である。本図に示す例において、入出金データに含まれる複数の項目別にサブルールが設定されている。サブルールの数は、１項目について例えば５以上であるが、１０以上であってもよい。そして上記した項目別のルールは、当該項目において、第２基準数以上のサブルールが満たされていることである。第２基準数は、例えば半数（母数が奇数の場合は半数＋０．５）又は半数＋１であるが、半数より少なくてもよいし、半数＋２以上であってもよい。すなわちルールに合致するか否かも、多数決的な考え方により判断されている。
FIG. 2 is a diagram showing an example of rules stored in the storage unit 140. FIG. In the example shown in this figure, subrules are set for each of a plurality of items included in the deposit/withdrawal data. The number of subrules is, for example, 5 or more per item, but may be 10 or more. The rule for each item described above is that the number of sub-rules equal to or greater than the second reference number is satisfied in the item. The second reference number is, for example, half (half + 0.5 if the parameter is an odd number) or half + 1, but may be less than half or half + 2 or more. In other words, whether or not a rule is met is also determined by majority decision.
これらのサブルールは、いずれも、当該入出金データが示す取引が、例外的な取引であることを示している。一例として、金額に関するサブルールは、入金の振り込み元が過去に取引があり、日付及びチャネルが所定の条件を満たす場合の、通常の取引における金額の範囲を示している。また、日付に関するサブルールは、入金であって、振り込み元が過去に取引があり、金額及びチャネルが所定の条件を満たす場合の、通常の取引における日付の範囲を示している。サブルールは、人手で設定されてもよいし、機械学習を用いて生成されてもよい。後者の場合、機械学習としては、例えば論理思考型のＡＩ（Artificial Intelligence）が用いられるが、これに限定されない。
All of these subrules indicate that the transaction indicated by the relevant deposit/withdrawal data is an exceptional transaction. As an example, the amount subrule indicates the range of amounts in a normal transaction when the transfer source of the deposit has transactions in the past and the date and channel satisfy predetermined conditions. Further, the date subrule indicates the range of dates in normal transactions when the deposit is a transaction, the transfer source has a transaction in the past, and the amount and channel satisfy predetermined conditions. Subrules may be set manually or may be generated using machine learning. In the latter case, for example, logical thinking AI (Artificial Intelligence) is used as machine learning, but it is not limited to this.
図３は、口座監視装置１０のハードウェア構成例を示す図である。口座監視装置１０は、バス１０１０、プロセッサ１０２０、メモリ１０３０、ストレージデバイス１０４０、入出力インタフェース１０５０、及びネットワークインタフェース１０６０を有する。
FIG. 3 is a diagram showing a hardware configuration example of the account monitoring device 10. As shown in FIG. Account monitoring device 10 has bus 1010 , processor 1020 , memory 1030 , storage device 1040 , input/output interface 1050 and network interface 1060 .
バス１０１０は、プロセッサ１０２０、メモリ１０３０、ストレージデバイス１０４０、入出力インタフェース１０５０、及びネットワークインタフェース１０６０が、相互にデータを送受信するためのデータ伝送路である。ただし、プロセッサ１０２０などを互いに接続する方法は、バス接続に限定されない。
The bus 1010 is a data transmission path for the processor 1020, the memory 1030, the storage device 1040, the input/output interface 1050, and the network interface 1060 to exchange data with each other. However, the method of connecting processors 1020 and the like to each other is not limited to bus connection.
プロセッサ１０２０は、ＣＰＵ（Central Processing Unit）やＧＰＵ（Graphics Processing Unit）などで実現されるプロセッサである。
The processor 1020 is a processor realized by a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or the like.
メモリ１０３０は、ＲＡＭ（Random Access Memory）などで実現される主記憶装置である。
The memory 1030 is a main memory implemented by RAM (Random Access Memory) or the like.
ストレージデバイス１０４０は、ＨＤＤ（Hard Disk Drive）、ＳＳＤ（Solid State Drive）、メモリカードなどのリムーバブルメディア、又はＲＯＭ（Read Only Memory）などで実現される補助記憶装置である。ストレージデバイス１０４０は口座監視装置１０の各機能（例えば取得部１１０、判断部１２０、及び出力部１３０）を実現するプログラムモジュールを記憶している。プロセッサ１０２０がこれら各プログラムモジュールをメモリ１０３０上に読み込んで実行することで、そのプログラムモジュールに対応する各機能が実現される。また、ストレージデバイス１０４０は記憶部１４０としても機能する。
The storage device 1040 is a removable medium such as a HDD (Hard Disk Drive), an SSD (Solid State Drive), a memory card, or an auxiliary storage device realized by a ROM (Read Only Memory). The storage device 1040 stores program modules that implement each function of the account monitoring device 10 (for example, the acquisition unit 110, the determination unit 120, and the output unit 130). Each function corresponding to the program module is realized by the processor 1020 reading each program module into the memory 1030 and executing it. The storage device 1040 also functions as the storage section 140 .
入出力インタフェース１０５０は、口座監視装置１０と各種入出力機器とを接続するためのインタフェースである。
The input/output interface 1050 is an interface for connecting the account monitoring device 10 and various input/output devices.
ネットワークインタフェース１０６０は、口座監視装置１０をネットワークに接続するためのインタフェースである。このネットワークは、例えばＬＡＮ（Local Area Network）やＷＡＮ（Wide Area Network）である。ネットワークインタフェース１０６０がネットワークに接続する方法は、無線接続であってもよいし、有線接続であってもよい。口座監視装置１０の取得部１１０は、例えばネットワークインタフェース１０６０を介して入出金データを取得する。
The network interface 1060 is an interface for connecting the account monitoring device 10 to the network. This network is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network). A method for connecting the network interface 1060 to the network may be a wireless connection or a wired connection. Acquisition unit 110 of account monitoring device 10 acquires deposit/withdrawal data via network interface 1060, for example.
図４は、口座監視装置１０が行う処理の一例を示すフローチャートである。まず口座監視装置１０の取得部１１０は、入出金データを取得する（ステップＳ１０）。すると口座監視装置１０の判断部１２０は、入出金データに含まれる項目別に、合致するサブルールの数を特定する（ステップＳ２０）。そして判断部１２０は、合致したサブルールの数が第２基準値を超えた項目の数を特定する（ステップＳ３０）。そして出力部１３０は、特定した項目の数が第１基準値を超えた場合（ステップＳ４０：Ｙｅｓ）、所定の出力を行う（ステップＳ５０）。言い換えると、出力部１３０は、複数の項目においてその入出金データが例外的な取引であると認定された場合、その入出金データが示す振り込みは不正である可能性が高い、と判断する。
FIG. 4 is a flowchart showing an example of processing performed by the account monitoring device 10. First, the acquisition unit 110 of the account monitoring device 10 acquires deposit/withdrawal data (step S10). Then, the determination unit 120 of the account monitoring device 10 specifies the number of matching sub-rules for each item included in the deposit/withdrawal data (step S20). Then, the determination unit 120 identifies the number of items in which the number of matched subrules exceeds the second reference value (step S30). When the number of specified items exceeds the first reference value (step S40: Yes), the output unit 130 performs a predetermined output (step S50). In other words, if the deposit/withdrawal data is recognized as an exceptional transaction in a plurality of items, the output unit 130 determines that the transfer indicated by the deposit/withdrawal data is highly likely to be fraudulent.
上記したように、所定の出力は、処理対象となっている入出金データ（出金及び入金のいずれの場合も含む）が不正な取引である可能性が高いことを示している。そして、所定の出力の出力先は、例えばその口座の管理者の端末である。このため、この管理者は、出力部１３０からの出力を認識することにより、不正な取引、例えば横領のための出金や入金が行われた可能性があることを、認識できる。
As described above, the predetermined output indicates that the deposit/withdrawal data being processed (including both withdrawals and deposits) is highly likely to be an unauthorized transaction. The output destination of the predetermined output is, for example, the terminal of the manager of the account. Therefore, by recognizing the output from the output unit 130, the administrator can recognize that there is a possibility that fraudulent transactions, such as embezzlement, have been made.
以上、本実施形態によれば、入出金データに含まれる項目別に、例外的な取引であることを検知するためのルールが設定されている。そして口座監視装置１０は、このルールに合致した項目の数を用いて、不正な取引である可能性が高い入出金データを検知する。したがって、口座監視装置１０を用いると、不正な振り込みを精度よく検出できる。
As described above, according to the present embodiment, rules for detecting exceptional transactions are set for each item included in the deposit/withdrawal data. Then, the account monitoring device 10 uses the number of items that match this rule to detect deposit/withdrawal data that are highly likely to be fraudulent transactions. Therefore, by using the account monitoring device 10, fraudulent transfers can be detected with high accuracy.
以上、図面を参照して本発明の実施形態について述べたが、これらは本発明の例示であり、上記以外の様々な構成を採用することもできる。
Although the embodiments of the present invention have been described above with reference to the drawings, these are examples of the present invention, and various configurations other than those described above can be adopted.
また、上述の説明で用いた複数のフローチャートでは、複数の工程（処理）が順番に記載されているが、各実施形態で実行される工程の実行順序は、その記載の順番に制限されない。各実施形態では、図示される工程の順番を内容的に支障のない範囲で変更することができる。また、上述の各実施形態は、内容が相反しない範囲で組み合わせることができる。
Also, in the plurality of flowcharts used in the above description, a plurality of steps (processing) are described in order, but the execution order of the steps executed in each embodiment is not limited to the order of description. In each embodiment, the order of the illustrated steps can be changed within a range that does not interfere with the content. Moreover, each of the above-described embodiments can be combined as long as the contents do not contradict each other.
上記の実施形態の一部または全部は、以下の付記のようにも記載されうるが、以下に限られない。
１．口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得手段と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断手段と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力手段と、
を備える口座監視装置。
２．上記１に記載の口座監視装置において、
前記複数の項目別に複数のサブルールが設定されており、
前記ルールは、第２基準数以上の前記サブルールが満たされていることである、口座監視装置。
３．上記２に記載の口座監視装置において、
前記複数のサブルールは機械学習を用いて生成されている口座監視装置。
４．上記２又は３に記載の口座監視装置において、
前記サブルールは、例外的な入金又は出金であることを示している、口座監視装置。
５．上記１～４のいずれか一項に記載の口座監視装置において、
前記項目は、入金及び出金の区分、金額、日付、振込先の指定方法、チャネル、及び出金先特定情報の少なくとも一つを含む、口座監視装置。
６．コンピュータが、
口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得処理と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断処理と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力処理と、
を行う口座監視方法。
７．上記６に記載の口座監視方法において、
前記複数の項目別に複数のサブルールが設定されており、
前記ルールは、第２基準数以上の前記サブルールが満たされていることである、口座監視方法。
８．上記７に記載の口座監視方法において、
前記複数のサブルールは機械学習を用いて生成されている口座監視方法。
９．上記７又は８に記載の口座監視方法において、
前記サブルールは、例外的な入金又は出金であることを示している、口座監視方法。
１０．上記６～９のいずれか一項に記載の口座監視方法において、
前記項目は、入金及び出金の区分、金額、日付、振込先の指定方法、チャネル、及び出金先特定情報の少なくとも一つを含む、口座監視方法。
１１．コンピュータに、
口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得機能と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断機能と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力機能と、
を持たせるプログラム。
１２．上記１１に記載のプログラムにおいて、
前記複数の項目別に複数のサブルールが設定されており、
前記ルールは、第２基準数以上の前記サブルールが満たされていることである、プログラム。
１３．上記１２に記載のプログラムにおいて、
前記複数のサブルールは機械学習を用いて生成されているプログラム。
１４．上記１２又は１３に記載のプログラムにおいて、
前記サブルールは、例外的な入金又は出金であることを示している、プログラム。
１５．上記１１～１４のいずれか一項に記載のプログラムにおいて、
前記項目は、入金及び出金の区分、金額、日付、振込先の指定方法、チャネル、及び出金先特定情報の少なくとも一つを含む、プログラム。 Some or all of the above embodiments can also be described as the following additional remarks, but are not limited to the following.
1. data acquisition means for acquiring deposit/withdrawal data relating to deposits or withdrawals from an account and having a plurality of items;
determination means for determining whether the deposit/withdrawal data satisfies rules set for each of the plurality of items;
output means for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
account monitoring device.
2. In the account monitoring device according to 1 above,
A plurality of subrules are set for each of the plurality of items,
The account monitoring device, wherein the rule is that a second criterion number or more of the sub-rules are satisfied.
3. In the account monitoring device according to 2 above,
The account monitoring device, wherein the plurality of sub-rules are generated using machine learning.
4. In the account monitoring device according to 2 or 3 above,
The account monitoring device, wherein the sub-rules indicate exceptional deposits or withdrawals.
5. In the account monitoring device according to any one of 1 to 4 above,
The account monitoring device, wherein the items include at least one of classification of deposit and withdrawal, amount, date, designation method of transfer destination, channel, and withdrawal destination identification information.
6. the computer
a data acquisition process for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account;
a judgment process for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items;
an output process of performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
account monitoring method.
7. In the account monitoring method described in 6 above,
A plurality of subrules are set for each of the plurality of items,
The method of account monitoring, wherein the rule is that a second criterion number or more of the sub-rules are satisfied.
8. In the account monitoring method described in 7 above,
The account monitoring method, wherein the plurality of sub-rules are generated using machine learning.
9. In the account monitoring method according to 7 or 8 above,
The account monitoring method, wherein the sub-rules indicate exceptional deposits or withdrawals.
10. In the account monitoring method according to any one of 6 to 9 above,
The account monitoring method, wherein the items include at least one of deposit/withdrawal category, amount, date, transfer destination designation method, channel, and withdrawal destination identification information.
11. to the computer,
a data acquisition function for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account;
a judgment function for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items;
an output function for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
A program that has
12. 11. In the program according to 11 above,
A plurality of subrules are set for each of the plurality of items,
The program, wherein the rule is that a second criterion number or more of the subrules are satisfied.
13. In the program according to 12 above,
The program, wherein the plurality of sub-rules are generated using machine learning.
14. In the program according to 12 or 13 above,
The program, wherein the subrule indicates an exceptional deposit or withdrawal.
15. In the program according to any one of 11 to 14 above,
The program, wherein the items include at least one of classification of deposit and withdrawal, amount, date, transfer destination designation method, channel, and withdrawal destination identification information.
１．口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得手段と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断手段と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力手段と、
を備える口座監視装置。
２．上記１に記載の口座監視装置において、
前記複数の項目別に複数のサブルールが設定されており、
前記ルールは、第２基準数以上の前記サブルールが満たされていることである、口座監視装置。
３．上記２に記載の口座監視装置において、
前記複数のサブルールは機械学習を用いて生成されている口座監視装置。
４．上記２又は３に記載の口座監視装置において、
前記サブルールは、例外的な入金又は出金であることを示している、口座監視装置。
５．上記１～４のいずれか一項に記載の口座監視装置において、
前記項目は、入金及び出金の区分、金額、日付、振込先の指定方法、チャネル、及び出金先特定情報の少なくとも一つを含む、口座監視装置。
６．コンピュータが、
口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得処理と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断処理と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力処理と、
を行う口座監視方法。
７．上記６に記載の口座監視方法において、
前記複数の項目別に複数のサブルールが設定されており、
前記ルールは、第２基準数以上の前記サブルールが満たされていることである、口座監視方法。
８．上記７に記載の口座監視方法において、
前記複数のサブルールは機械学習を用いて生成されている口座監視方法。
９．上記７又は８に記載の口座監視方法において、
前記サブルールは、例外的な入金又は出金であることを示している、口座監視方法。
１０．上記６～９のいずれか一項に記載の口座監視方法において、
前記項目は、入金及び出金の区分、金額、日付、振込先の指定方法、チャネル、及び出金先特定情報の少なくとも一つを含む、口座監視方法。
１１．コンピュータに、
口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得機能と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断機能と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力機能と、
を持たせるプログラム。
１２．上記１１に記載のプログラムにおいて、
前記複数の項目別に複数のサブルールが設定されており、
前記ルールは、第２基準数以上の前記サブルールが満たされていることである、プログラム。
１３．上記１２に記載のプログラムにおいて、
前記複数のサブルールは機械学習を用いて生成されているプログラム。
１４．上記１２又は１３に記載のプログラムにおいて、
前記サブルールは、例外的な入金又は出金であることを示している、プログラム。
１５．上記１１～１４のいずれか一項に記載のプログラムにおいて、
前記項目は、入金及び出金の区分、金額、日付、振込先の指定方法、チャネル、及び出金先特定情報の少なくとも一つを含む、プログラム。 Some or all of the above embodiments can also be described as the following additional remarks, but are not limited to the following.
1. data acquisition means for acquiring deposit/withdrawal data relating to deposits or withdrawals from an account and having a plurality of items;
determination means for determining whether the deposit/withdrawal data satisfies rules set for each of the plurality of items;
output means for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
account monitoring device.
2. In the account monitoring device according to 1 above,
A plurality of subrules are set for each of the plurality of items,
The account monitoring device, wherein the rule is that a second criterion number or more of the sub-rules are satisfied.
3. In the account monitoring device according to 2 above,
The account monitoring device, wherein the plurality of sub-rules are generated using machine learning.
4. In the account monitoring device according to 2 or 3 above,
The account monitoring device, wherein the sub-rules indicate exceptional deposits or withdrawals.
5. In the account monitoring device according to any one of 1 to 4 above,
The account monitoring device, wherein the items include at least one of classification of deposit and withdrawal, amount, date, designation method of transfer destination, channel, and withdrawal destination identification information.
6. the computer
a data acquisition process for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account;
a judgment process for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items;
an output process of performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
account monitoring method.
7. In the account monitoring method described in 6 above,
A plurality of subrules are set for each of the plurality of items,
The method of account monitoring, wherein the rule is that a second criterion number or more of the sub-rules are satisfied.
8. In the account monitoring method described in 7 above,
The account monitoring method, wherein the plurality of sub-rules are generated using machine learning.
9. In the account monitoring method according to 7 or 8 above,
The account monitoring method, wherein the sub-rules indicate exceptional deposits or withdrawals.
10. In the account monitoring method according to any one of 6 to 9 above,
The account monitoring method, wherein the items include at least one of deposit/withdrawal category, amount, date, transfer destination designation method, channel, and withdrawal destination identification information.
11. to the computer,
a data acquisition function for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account;
a judgment function for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items;
an output function for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
A program that has
12. 11. In the program according to 11 above,
A plurality of subrules are set for each of the plurality of items,
The program, wherein the rule is that a second criterion number or more of the subrules are satisfied.
13. In the program according to 12 above,
The program, wherein the plurality of sub-rules are generated using machine learning.
14. In the program according to 12 or 13 above,
The program, wherein the subrule indicates an exceptional deposit or withdrawal.
15. In the program according to any one of 11 to 14 above,
The program, wherein the items include at least one of classification of deposit and withdrawal, amount, date, transfer destination designation method, channel, and withdrawal destination identification information.
この出願は、２０２１年１２月１日に出願された日本出願特願２０２１－１９５６４０号を基礎とする優先権を主張し、その開示の全てをここに取り込む。
This application claims priority based on Japanese Patent Application No. 2021-195640 filed on December 1, 2021, and the entire disclosure thereof is incorporated herein.
１０ 口座監視装置
１１０ 取得部
１２０ 判断部
１３０ 出力部
１４０ 記憶部 10Account monitoring device 110 Acquisition unit 120 Judgment unit 130 Output unit 140 Storage unit
１１０ 取得部
１２０ 判断部
１３０ 出力部
１４０ 記憶部 10
Claims (15)
- 口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得手段と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断手段と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力手段と、
を備える口座監視装置。 data acquisition means for acquiring deposit/withdrawal data relating to deposits or withdrawals from an account and having a plurality of items;
determination means for determining whether the deposit/withdrawal data satisfies rules set for each of the plurality of items;
output means for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
account monitoring device. - 請求項１に記載の口座監視装置において、
前記複数の項目別に複数のサブルールが設定されており、
前記ルールは、第２基準数以上の前記サブルールが満たされていることである、口座監視装置。 In the account monitoring device according to claim 1,
A plurality of subrules are set for each of the plurality of items,
The account monitoring device, wherein the rule is that a second criterion number or more of the sub-rules are satisfied. - 請求項２に記載の口座監視装置において、
前記複数のサブルールは機械学習を用いて生成されている口座監視装置。 In the account monitoring device according to claim 2,
The account monitoring device, wherein the plurality of sub-rules are generated using machine learning. - 請求項２又は３に記載の口座監視装置において、
前記サブルールは、例外的な入金又は出金であることを示している、口座監視装置。 In the account monitoring device according to claim 2 or 3,
The account monitoring device, wherein the sub-rules indicate exceptional deposits or withdrawals. - 請求項１～４のいずれか一項に記載の口座監視装置において、
前記項目は、入金及び出金の区分、金額、日付、振込先の指定方法、チャネル、及び出金先特定情報の少なくとも一つを含む、口座監視装置。 In the account monitoring device according to any one of claims 1 to 4,
The account monitoring device, wherein the items include at least one of classification of deposit and withdrawal, amount, date, designation method of transfer destination, channel, and withdrawal destination identification information. - コンピュータが、
口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得処理と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断処理と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力処理と、
を行う口座監視方法。 the computer
a data acquisition process for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account;
a judgment process for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items;
an output process of performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
account monitoring method. - 請求項６に記載の口座監視方法において、
前記複数の項目別に複数のサブルールが設定されており、
前記ルールは、第２基準数以上の前記サブルールが満たされていることである、口座監視方法。 In the account monitoring method according to claim 6,
A plurality of subrules are set for each of the plurality of items,
The method of account monitoring, wherein the rule is that a second criterion number or more of the sub-rules are satisfied. - 請求項７に記載の口座監視方法において、
前記複数のサブルールは機械学習を用いて生成されている口座監視方法。 In the account monitoring method according to claim 7,
The account monitoring method, wherein the plurality of sub-rules are generated using machine learning. - 請求項７又は８に記載の口座監視方法において、
前記サブルールは、例外的な入金又は出金であることを示している、口座監視方法。 In the account monitoring method according to claim 7 or 8,
The account monitoring method, wherein the sub-rules indicate exceptional deposits or withdrawals. - 請求項６～９のいずれか一項に記載の口座監視方法において、
前記項目は、入金及び出金の区分、金額、日付、振込先の指定方法、チャネル、及び出金先特定情報の少なくとも一つを含む、口座監視方法。 In the account monitoring method according to any one of claims 6 to 9,
The account monitoring method, wherein the items include at least one of deposit/withdrawal category, amount, date, transfer destination designation method, channel, and withdrawal destination identification information. - コンピュータに、
口座の入金又は出金に関しており、複数の項目を有する入出金データを取得するデータ取得機能と、
前記入出金データが、前記複数の項目別に設定されたルールを満たすか否かを判断する判断機能と、
第１基準数以上の前記項目において前記ルールが満たされている場合に所定の出力を行う出力機能と、
を持たせるプログラムを記録する、非一時的なコンピュータ可読記録媒体。 to the computer,
a data acquisition function for acquiring deposit/withdrawal data having a plurality of items relating to deposits or withdrawals from an account;
a judgment function for judging whether or not the deposit/withdrawal data satisfies rules set for each of the plurality of items;
an output function for performing a predetermined output when the rule is satisfied for the items equal to or greater than a first reference number;
A non-transitory computer-readable recording medium that records a program that provides - 請求項１１に記載の非一時的なコンピュータ可読記録媒体において、
前記複数の項目別に複数のサブルールが設定されており、
前記ルールは、第２基準数以上の前記サブルールが満たされていることである、非一時的なコンピュータ可読記録媒体。 12. The non-transitory computer-readable medium of claim 11,
A plurality of subrules are set for each of the plurality of items,
The non-transitory computer-readable recording medium, wherein the rule is that a second criterion number or more of the sub-rules are satisfied. - 請求項１２に記載の非一時的なコンピュータ可読記録媒体において、
前記複数のサブルールは機械学習を用いて生成されている非一時的なコンピュータ可読記録媒体。 13. The non-transitory computer-readable medium of claim 12,
A non-transitory computer-readable recording medium, wherein the plurality of sub-rules are generated using machine learning. - 請求項１２又は１３に記載の非一時的なコンピュータ可読記録媒体において、
前記サブルールは、例外的な入金又は出金であることを示している、非一時的なコンピュータ可読記録媒体。 A non-transitory computer readable recording medium according to claim 12 or 13,
A non-transitory computer-readable recording medium, wherein the sub-rule indicates an exceptional deposit or withdrawal. - 請求項１１～１４のいずれか一項に記載の非一時的なコンピュータ可読記録媒体において、
前記項目は、入金及び出金の区分、金額、日付、振込先の指定方法、チャネル、及び出金先特定情報の少なくとも一つを含む、非一時的なコンピュータ可読記録媒体。 In the non-transitory computer-readable recording medium according to any one of claims 11 to 14,
The items are non-temporary computer-readable recording media including at least one of deposit/withdrawal category, amount, date, transfer destination designation method, channel, and withdrawal destination identification information.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2021-195640 | 2021-12-01 | ||
| JP2021195640 | 2021-12-01 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2023100846A1 true WO2023100846A1 (en) | 2023-06-08 |
Family
ID=86612283
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/JP2022/043888 WO2023100846A1 (en) | 2021-12-01 | 2022-11-29 | Account monitoring device, account monitoring method, and non-transitory computer-readable recording medium |
Country Status (1)
| Country | Link |
|---|---|
| WO (1) | WO2023100846A1 (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007226682A (en) * | 2006-02-24 | 2007-09-06 | Oki Consulting Solutions Co Ltd | Abnormal transaction prevention system and prevention method |
| JP2021072057A (en) * | 2019-11-01 | 2021-05-06 | 株式会社日立製作所 | Information processing device and information processing method |
| JP2021103357A (en) * | 2019-12-24 | 2021-07-15 | 株式会社三井住友銀行 | Bank system and method performed by bank system |
| JP2021144356A (en) * | 2020-03-10 | 2021-09-24 | Ａｓｓｅｓｔ株式会社 | Illegal financial transaction detection program |
-
2022
- 2022-11-29 WO PCT/JP2022/043888 patent/WO2023100846A1/en unknown
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007226682A (en) * | 2006-02-24 | 2007-09-06 | Oki Consulting Solutions Co Ltd | Abnormal transaction prevention system and prevention method |
| JP2021072057A (en) * | 2019-11-01 | 2021-05-06 | 株式会社日立製作所 | Information processing device and information processing method |
| JP2021103357A (en) * | 2019-12-24 | 2021-07-15 | 株式会社三井住友銀行 | Bank system and method performed by bank system |
| JP2021144356A (en) * | 2020-03-10 | 2021-09-24 | Ａｓｓｅｓｔ株式会社 | Illegal financial transaction detection program |
Non-Patent Citations (1)
| Title |
|---|
| "AML Practical Guide for Financial Institutions Risk Assessment and System Response", 17 July 2019, KINZAI INSTITUTE FOR FINANCIAL AFFAIRS, INC., JP, ISBN: 978-4-322-13468-1, article NAOKO FUJII, NOBUHIKO OSHIDA: "7-3 Types of scenarios and creation procedures How should I create a transaction monitoring scenario?", pages: 141 - 147, XP009546004 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11741480B2 (en) | Identifying fraudulent online applications | |
| US7427016B2 (en) | System and method for screening for fraud in commercial transactions | |
| US11989643B2 (en) | Interleaved sequence recurrent neural networks for fraud detection | |
| US11282086B1 (en) | Systems and methods for counterfeit check detection | |
| US10127554B2 (en) | Fraud early warning system and method | |
| CA2828751C (en) | System and method for suspect entity detection and mitigation | |
| US20180365696A1 (en) | Financial fraud detection using user group behavior analysis | |
| US20040064401A1 (en) | Systems and methods for detecting fraudulent information | |
| US20110202457A1 (en) | Systems and Methods for Managing Risk Associated with a Geo-Political Area | |
| US8548910B1 (en) | Address change notification | |
| US8117097B2 (en) | Method and system for identifying fraudulent account activity | |
| US8600789B1 (en) | System and method for processing offending items in a financial system | |
| US10223680B2 (en) | Transaction decisioning by an automated device | |
| US8429050B2 (en) | Method for detecting ineligibility of a beneficiary and system | |
| US20130282562A1 (en) | Systems and methods for preventing fraudulent purchases | |
| US20160358263A1 (en) | Auditing custodial accounts | |
| US8078533B1 (en) | Systems and methods for monitoring remittances for reporting requirements | |
| US10134019B2 (en) | Transaction decisioning by an automated device | |
| JP6931384B2 (en) | Banking system, and how it is performed by the banking system | |
| WO2023100846A1 (en) | Account monitoring device, account monitoring method, and non-transitory computer-readable recording medium | |
| US20170221167A1 (en) | System and Network for Detecting Unauthorized Activity | |
| US8078517B1 (en) | Systems and methods for monitoring remittances for reporting requirements | |
| WO2023175903A1 (en) | Monitoring system, model generation device, model generation method, and recording medium | |
| WO2023175898A1 (en) | Monitoring system, model generation device, model generation method, and recording medium | |
| US20240112192A1 (en) | Systems and methods for enhanced transaction authentication |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 22901278 Country of ref document: EP Kind code of ref document: A1 |