Cross-industry alliance anti-fraud cooperation system and methods

Abstract

A cross-industry alliance anti-fraud cooperation system includes a bank server and an instant messaging server electrically connected to it. The bank server identifies a target customer from multiple customer records based on an identity card number and bank account information of a fraudster. The bank server sends a suspicious identification query request containing the target customer's unique instant messaging identifier to the instant messaging server, causing it to read chat group data corresponding to a relevant chat group. This chat group data includes multiple unique instant messaging identifiers for multiple group members and a chat log, and generates multiple identity inference results corresponding to the unique instant messaging identifiers of each group member based on the chat log.

Description

Technical Field

[0001] This invention relates to an anti-fraud system, and more particularly to a system for cross-industry alliance cooperation. Prior Technology

[0002] With the widespread adoption of digitalization and social media, fraud methods are constantly evolving, among which "fake investment scams" have become one of the most common. Fraud groups typically utilize various channels, such as social media platforms and instant messaging software, to carry out their scams. For example, on the LINE messaging app, scammers may create fake groups to lure victims into making improper investments or transferring money.

[0003] Currently, combating fraud largely relies on reports or monitoring of suspicious activity by government agencies, financial institutions, and individuals. Despite numerous anti-fraud measures, they are still insufficient to completely curb fraud, particularly in terms of cross-industry cooperation and intelligence sharing, where effective collaborative mechanisms remain lacking. Summary of the Invention

[0004] Therefore, the purpose of this invention is to provide a cross-industry alliance anti-fraud cooperation system.

[0005] Another objective of this invention is to provide a method for cross-industry alliance anti-fraud cooperation.

[0006] Therefore, the cross-industry alliance anti-fraud cooperation system of the present invention is suitable for communicating with a police system and includes a bank server and an instant messaging server.

[0007] The bank server stores multiple customer records, each containing an identity card number, a bank account, and a unique instant messaging identifier. The instant messaging server is electrically connected to the bank server.

[0008] The bank server received fraudster identification information, including an ID number and a bank account, from the police system.

[0009] The bank server uses the identity card number and bank account information of the fraudster to identify a matching customer from the customer data and selects them as a target customer.

[0010] The bank server sends a suspicious identification information query request to the instant messaging server, which contains the target customer's information and the instant messaging unique identifier.

[0011] In response to the suspicious identification information query request, the instant messaging server reads a chat group data corresponding to a chat group. The chat group data includes multiple instant messaging unique identifiers of multiple group members and a chat record. One of the instant messaging unique identifiers of these group members matches the instant messaging unique identifier in the suspicious identification information query request.

[0012] The instant messaging server generates multiple identity prediction results based on the chat history, each corresponding to a unique instant messaging identifier of a member of the group, and each identity prediction result indicates a suspected fraudster or a suspected victim.

[0013] The instant messaging server transmits the unique instant messaging identification information of the group members and the corresponding identity estimation results to the bank server.

[0014] In some implementations, for each identity speculation result indicating a suspected fraudster, the bank server identifies the matching individual from the customer data to execute a transaction monitoring procedure.

[0015] In some implementations, for each identity speculation result indicating a suspected victim corresponding to the unique instant messaging identification information, the bank server identifies the match from the customer data to perform an anti-fraud awareness program.

[0016] In some implementations, the bank server receives fraudster online identity information from the police system, which includes a custom instant messaging identification.

[0017] The bank server sends a unique identifier query request to the instant messaging server containing the fraudster's online identity information and custom identifier.

[0018] In response to the unique identifier query request, the instant messaging server finds a corresponding unique identifier for the instant messaging custom identifier in the query request and sends a unique identifier query result containing the found unique identifier to the bank server.

[0019] In some implementations, when the instant messaging server responds to the unique identification data query request, it also finds a corresponding device identification data based on the instant messaging custom identification data in the unique identification data query request, and uses other instant messaging unique identification data corresponding to the device identification data as one or more suspected same user data, and transmits the suspected same user data or such suspected same user data to the bank server.

[0020] In some implementations, for the unique identifier query results of the instant messaging unique identifier and the suspected same user information or such suspected same user information, the bank server finds the match from such customer information to execute a transaction monitoring procedure.

[0021] This invention discloses a cross-industry alliance anti-fraud cooperation method, implemented through a cross-industry alliance anti-fraud cooperation system. This system is adapted to communicate with a police system and includes a bank server and an instant messaging server. The bank server stores multiple customer data entries, each containing an ID number, a bank account, and a unique instant messaging identifier. The instant messaging server is electrically connected to the bank server. The method includes: the bank server receiving fraudster identification data containing an ID number and a bank account from the police system; the bank server identifying a matching customer from the customer data based on the ID number and bank account of the fraudster's identification data as a target customer; and the bank server transmitting suspicious identification data containing the unique instant messaging identifier of the target customer. The query request is sent to the instant messaging server; the instant messaging server responds to the suspicious identification information query request by reading chat group data corresponding to a chat group, the chat group data containing multiple instant messaging unique identifiers of multiple group members and a chat record, one of the instant messaging unique identifiers of the group members matching the instant messaging unique identifier in the suspicious identification information query request; the instant messaging server generates multiple identity prediction results corresponding to the instant messaging unique identifiers of the group members based on the chat record, each identity prediction result indicating a suspected fraudster or a suspected victim; and the instant messaging server transmits the instant messaging unique identifiers of the group members and the corresponding identity prediction results to the bank server.

[0022] The advantages of this invention are as follows: the instant messaging server generates identity estimation results corresponding to the unique instant messaging identification data of the group members based on the chat records, and transmits the unique instant messaging identification data of the group members and the corresponding identity estimation results to the bank server, so that the bank server can execute the transaction monitoring program and the anti-fraud publicity program, thereby establishing an effective collaborative mechanism through cross-industry cooperation and intelligence sharing to carry out real-time fraud warning and asset protection. Simple Explanation of the Diagram

[0023] Other features and effects of the present invention will be clearly presented in the embodiments with reference to the drawings, wherein: Figure 1 is a schematic diagram of the hardware connection relationship of an embodiment of the cross-industry alliance anti-fraud cooperation system of the present invention; Figure 2 is a flowchart of this embodiment, illustrating a suspicious identification data query procedure; and Figure 3 is another flowchart of this embodiment, illustrating a unique identification data query procedure. Implementation

[0024] Before the invention is described in detail, it should be noted that similar elements are represented by the same numbers in the following description.

[0025] Before this invention is described in detail, it should be noted that, unless otherwise defined, the term "electrically connected" in this patent specification refers to the "coupled" relationship between computer hardware (e.g., electronic systems, devices, apparatuses, units, components), and broadly refers to "wired electrical connections" achieved by physically connecting multiple computer hardware components through conductor / semiconductor materials, and "radio connections" that achieve wireless data transmission using wireless communication technologies (e.g., but not limited to wireless networks, Bluetooth, and electromagnetic induction). On the other hand, unless otherwise defined, the term "electrical connection" in this patent specification also broadly refers to "direct electrical connections" achieved by directly coupling multiple computer hardware components to each other, and "indirect electrical connections" achieved by indirectly coupling multiple computer hardware components through other computer hardware components.

[0026] Before this invention is described in detail, it should be noted that the term "unit" in this patent specification refers to computer hardware rather than software. For example, "processing unit" refers to computer hardware with data processing capabilities.

[0027] Referring to Figures 1 and 2, an embodiment of the cross-industry alliance anti-fraud cooperation system 100 of the present invention is adapted to communicate with a police system 200 and includes a bank server 1 and an instant messaging server 2.

[0028] The bank server 1 stores multiple customer records, each containing an identity card number, a bank account, and a unique instant messaging identifier (such as a LINE UID). The instant messaging server 2 is electrically connected to the bank server 1.

[0029] Referring to Figures 1 and 2, the following describes the steps of the cross-industry alliance anti-fraud cooperation system 100 in performing a suspicious identification information query procedure. First, as shown in step S01, the bank server 1 receives fraudster identity information containing an ID number and a bank account from the police system 200.

[0030] Next, as shown in step S02, the bank server 1 uses the identity card number and bank account of the fraudster's identity information to find a matching person from the customer information to serve as a target customer.

[0031] Next, as shown in step S03, the bank server 1 sends a suspicious identification information query request containing the target customer's information and the instant messaging unique identification information to the instant messaging server 2.

[0032] Next, as shown in step S04, the instant messaging server 2 responds to the suspicious identification data query request by reading a chat group data corresponding to a chat group. The chat group data includes multiple instant messaging unique identification data (e.g., LINE UID) of multiple group members of the chat group and a chat record. One of the instant messaging unique identification data of these group members matches the instant messaging unique identification data in the suspicious identification data query request.

[0033] Next, as shown in step S05, the instant messaging server 2 generates multiple identity prediction results based on the chat history, each corresponding to a unique instant messaging identifier for a member of the group. Each identity prediction result indicates a suspected fraudster or a suspected victim. For example, conversations involving suspected fraudsters often involve investments, coupons, bonuses, or requests for sensitive personal information (such as account numbers, passwords, etc.), while conversations involving suspected victims often involve expressing panic or revealing their vulnerability. These conversation characteristics can be identified through natural language processing technology.

[0034] Next, as shown in step S06, the instant messaging server 2 transmits the instant messaging unique identification information of the group members and the corresponding identity estimation results to the bank server 1.

[0035] Next, as shown in step S07, for each identity speculation result indicating a suspected fraudster, the bank server 1 finds a match in the customer data to execute a transaction monitoring procedure. In addition, for each identity speculation result indicating a suspected victim, the bank server 1 finds a match in the customer data to execute an anti-fraud education procedure.

[0036] Referring to Figures 1 and 3, the following describes the steps of the cross-industry alliance anti-fraud cooperation system 100 in performing a unique identification information query procedure. First, as shown in step S11, the bank server 1 receives fraudster online identity information (e.g., LINE ID) containing instant messaging custom identification information from the police system 200.

[0037] Next, as shown in step S12, the bank server 1 sends a unique identification information query request containing the fraudster's online identity information and custom identification information to the instant messaging server 2.

[0038] Next, as shown in step S13, the instant messaging server 2 responds to the unique identification data query request by finding a corresponding instant messaging unique identification data based on the instant messaging custom identification data in the unique identification data query request, and sends a unique identification data query result containing the found instant messaging unique identification data to the bank server 1. The instant messaging server 2 also finds a corresponding device identification data based on the instant messaging custom identification data in the unique identification data query request, and identifies other instant messaging unique identification data corresponding to the device identification data as one or more suspected same user data, and sends the suspected same user data or such suspected same user data to the bank server 1.

[0039] Next, as shown in step S14, for the unique identification data query result of the instant messaging unique identification data and the suspected same user data or such suspected same user data, the bank server 1 finds the match from such customer data to execute a transaction monitoring procedure.

[0040] In summary, the cross-industry alliance anti-fraud cooperation system 100 of the present invention uses the instant messaging server 2 to generate identity estimation results corresponding to the unique instant messaging identification data of the group members based on the chat records, and transmits the unique instant messaging identification data of the group members and the corresponding identity estimation results to the bank server 1, so that the bank server 1 can execute the transaction monitoring program and the anti-fraud publicity program. In this way, an effective cooperation mechanism is established through cross-industry cooperation and intelligence sharing to carry out real-time fraud warning and asset protection, thus achieving the purpose of the present invention.

[0041] However, the above description is merely an embodiment of the present invention and should not be construed as limiting the scope of the present invention. Any simple equivalent changes and modifications made in accordance with the scope of the patent application and the contents of the patent specification of the present invention shall still fall within the scope of the patent of the present invention.

[0042] 100: Cross-Industry Alliance Anti-Fraud Cooperation System 1: Bank Server 2: Instant Messaging Server 200: Police System S01~S07: Steps S11~S14: Steps

Claims

1. A cross-industry alliance anti-fraud cooperation system, suitable for communicating with a police system, and comprising: a bank server storing multiple customer data entries, each customer data entry including an identity card number, a bank account, and an instant messaging unique identifier; and an instant messaging server electrically connected to the bank server; the bank server receiving fraudster identity information containing an identity card number and a bank account from the police system; the bank server identifying a matching individual from the customer data based on the identity card number and bank account of the fraudster identity information as a target customer; and the bank server transmitting a suspicious identification data query request containing the instant messaging unique identifier of the target customer information to the instant messaging server; In response to the suspicious identification information query request, the instant messaging server reads chat group data corresponding to a chat group. This chat group data includes multiple unique instant messaging identifiers (IMIDs) for multiple group members and a chat log. One of the IMIDs of these group members matches the IMID in the suspicious identification information query request. Based on the chat log, the instant messaging server generates multiple identity prediction results corresponding to the IMIDs of these group members, each indicating a suspected fraudster or a suspected victim. The instant messaging server transmits the IMIDs of these group members and the corresponding identity prediction results to the bank server. The bank server receives fraudster online identity data containing a custom instant messaging identifier from the police system. The bank server then sends a unique identification information query request containing the custom instant messaging identifier of the fraudster online identity data to the instant messaging server. In response to the unique identifier query request, the instant messaging server finds a corresponding unique identifier for the instant messaging custom identifier in the query request and sends a unique identifier query result containing the found unique identifier to the bank server.

2. The cross-industry alliance anti-fraud cooperation system as described in claim 1, wherein, For each identity speculation result indicating a suspected fraudster, the bank server identifies the corresponding instant messaging unique identifier from the customer data to execute a transaction monitoring procedure.

3. The cross-industry alliance anti-fraud cooperation system as described in claim 1, wherein, For each identity speculation result indicating a suspected victim, the bank server identifies the corresponding instant messaging unique identifier from the customer data to perform an anti-fraud awareness program.

4. The cross-industry alliance anti-fraud cooperation system as described in claim 1, wherein, When the instant messaging server responds to the unique identification data query request, it also finds a corresponding device identification data based on the instant messaging custom identification data in the unique identification data query request, and regards other instant messaging unique identification data corresponding to the device identification data as one or more suspected same user data, and transmits the suspected same user data or such suspected same user data to the bank server.

5. The cross-industry alliance anti-fraud cooperation system as described in claim 4, wherein, For the unique identifier information of the instant messaging service and the suspected same user information or such suspected same user information in the query results, the bank server finds the match from such customer information to execute a transaction monitoring procedure.

6. A cross-industry alliance anti-fraud cooperation method, implemented through a cross-industry alliance anti-fraud cooperation system, the cross-industry alliance anti-fraud cooperation system being adapted to communicate with a police system, and including a bank server and an instant messaging server, the bank server storing multiple customer data, each customer data including an identity card number, a bank account, and an instant messaging unique identifier, the instant messaging server being electrically connected to the bank server, the method comprising: the bank server receiving fraudster identity information including an identity card number and a bank account from the police system; the bank server identifying a matching person from the customer data based on the identity card number and bank account of the fraudster identity information as a target customer; the bank server transmitting a suspicious identification data query request including the instant messaging unique identifier of the target customer information to the instant messaging server; In response to the suspicious identification information query request, the instant messaging server reads chat group data corresponding to a chat group. This chat group data includes multiple unique instant messaging identifiers (IMIDs) for multiple group members and a chat log. One of the IMIDs of these group members matches the IMID in the suspicious identification information query request. Based on the chat log, the instant messaging server generates multiple identity prediction results corresponding to the IMIDs of these group members, each indicating a suspected fraudster or a suspected victim. The instant messaging server transmits the IMIDs of these group members and the corresponding identity prediction results to the bank server. The bank server receives fraudster online identity data containing a custom instant messaging identifier from the police system. The bank server sends a unique identifier query request to the instant messaging server containing the fraudster's online identity information; and the instant messaging server responds to the unique identifier query request by finding a corresponding instant messaging unique identifier based on the instant messaging custom identifier in the unique identifier query request, and sends a unique identifier query result containing the found instant messaging unique identifier to the bank server.

7. The cross-industry alliance anti-fraud cooperation method as described in claim 6 further includes: for each instant messaging unique identification data corresponding to the identity speculation result indicating a suspected fraudster, the bank server finds a match from the customer data to execute a transaction monitoring procedure.

8. The cross-industry alliance anti-fraud cooperation method as described in claim 6 further includes: for each identity speculation result indicating a suspected victim corresponding to the instant messaging unique identification information, the bank server finds a match from the customer data to perform an anti-fraud awareness program.

9. The cross-industry alliance anti-fraud cooperation method as described in claim 6, wherein, When the instant messaging server responds to the unique identification data query request, it also finds a corresponding device identification data based on the instant messaging custom identification data in the unique identification data query request, and regards other instant messaging unique identification data corresponding to the device identification data as one or more suspected same user data, and transmits the suspected same user data or such suspected same user data to the bank server.

10. The cross-industry alliance anti-fraud cooperation method as described in claim 9 further includes: for the instant messaging unique identifier and the suspected same user information or such suspected same user information in the query result of the unique identifier, the bank server finds the match from such customer information to execute a transaction monitoring procedure.

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