Method and system for facilitating risk control of an online financial platform

1. A computer-executable method, comprising:

monitoring, by a computer, types and numbers of risk-control commands issued by a risk-control system, wherein the risk-control commands correspond to transactions associated with users which receive service from an online financial platform;

obtaining statistics associated with the monitored risk-control commands;

determining, based on the obtained statistics, whether a subset of risk-control commands meets an anomaly condition, wherein the subset comprises at least one of: a particular type of risk-control command; and a particular type of risk-control command associated with a particular set of a plurality of sets of risk-control policies,

wherein the plurality of sets of risk-control policies identify risks associated with a particular type of transaction,

wherein the plurality of sets include at least one of: a first set for identifying risks associated with fund transfers; a second set for identifying risks associated with deposits; and a third set for identifying risks associated with withdrawals,

wherein the first set further includes at least one of: a first policy for dealing with fraud risk; a second policy for dealing with money-laundering risk; and a third policy for dealing with identity theft risk, and

wherein the anomaly condition is based on the obtained statistics and a ratio between a number of risk-control commands within the subset and a total number of risk-control commands issued by the risk-control system over a predetermined time interval, wherein the anomaly condition specifies a higher threshold and a lower threshold, and wherein the subset of risk-control commands meets the anomaly condition if the number or the ratio is greater than the higher threshold or less than the lower threshold;

in response to determining that the subset of risk-control commands does not meet the anomaly condition, forwarding the subset of risk-control commands to the online financial platform to facilitate the online financial platform in performing corresponding transactions according to the subset of risk-control commands;

in response to determining that the subset of risk-control commands meets the anomaly condition, preventing the subset of risk-control commands from being forwarded to the online financial platform;

subsequent to preventing the subset of risk-control commands from being forwarded to the online financial platform, continuing to monitor the subset of risk-control commands to determine whether the subset of risk-control commands no longer meets the anomaly condition; and

in response to determining that the subset of risk-control commands no longer meets the anomaly condition, forwarding the subset of risk-control commands to the online financial platform.

2. The method of claim 1 ,

wherein the particular type of risk-control command is configured to instruct the online financial platform to perform a particular action associated with a corresponding transaction;

wherein the particular set of risk-control policies is associated with a particular type of transaction; and

wherein the subset of risk-control commands further comprises a particular type of risk-control command associated with a particular risk-control policy, wherein the particular risk-control policy is associated with a particular type of risk.

3. The method of claim 1 , wherein the statistics associated with the monitored plurality of risk-control commands comprises one or more of:

the number of risk-control commands within the subset issued by the risk-control system over the predetermined time interval; and

the ratio between the number of risk-control commands within the subset and the total number of risk-control commands issued by the risk-control system over the predetermined time interval.

4. The method of claim 3 , wherein the anomaly condition is determined based on historical data associated with the subset of risk-control commands.

5. The method of claim 4 , wherein the anomaly condition is determined based on probability distribution of the number or the ratio and a predetermined confidence interval.

6. The method of claim 1 , wherein preventing the subset of risk-control commands from being forwarded to the online financial platform further comprises:

substituting the subset of risk-control commands using a second subset of risk-control commands, wherein the subset and second subset of risk-control commands are of different types; and

forwarding the second subset of risk-control commands to the online financial platform to facilitate the online financial platform in performing corresponding transactions according to the second subset of risk-control commands.

7. A computer system, comprising:

a processor; and

a storage device coupled to the processor and storing instructions which when executed by the processor cause the processor to perform a method, the method comprising:

monitoring, by a computer, types and numbers of risk-control commands issued by a risk-control system, wherein the risk-control commands correspond to transactions associated with users which receive service from an online financial platform;

obtaining statistics associated with the monitored risk-control commands;

determining, based on the obtained statistics, whether a subset of risk-control commands meets an anomaly condition, wherein the subset comprises at least one of: a particular type of risk-control command; and a particular type of risk-control command associated with a particular set of a plurality of sets of risk-control policies,

wherein the plurality of sets of risk-control policies identify risks associated with a particular type of transaction,

wherein the plurality of sets include at least one of: a first set for identifying risks associated with fund transfers; a second set for identifying risks associated with deposits; and a third set for identifying risks associated with withdrawals,

wherein the first set further includes at least one of: a first policy for dealing with fraud risk; a second policy for dealing with money-laundering risk; and a third policy for dealing with identity theft risk, and

wherein the anomaly condition is based on the obtained statistics and a ratio between a number of risk-control commands within the subset and a total number of risk-control commands issued by the risk-control system over a predetermined time interval, wherein the anomaly condition specifies a higher threshold and a lower threshold, and wherein the subset of risk-control commands meets the anomaly condition if the number or the ratio is greater than the higher threshold or less than the lower threshold;

in response to determining that the subset of risk-control commands does not meet the anomaly condition, forwarding the subset of risk-control commands to the online financial platform to facilitate the online financial platform in performing corresponding transactions according to the subset of risk-control commands;

in response to determining that the subset of risk-control commands meets the anomaly condition, preventing the subset of risk-control commands from being forwarded to the online financial platform;

subsequent to preventing the subset of risk-control commands from being forwarded to the online financial platform, continuing to monitor the subset of risk-control commands to determine whether the subset of risk-control commands no longer meets the anomaly condition; and

in response to determining that the subset of risk-control commands no longer meets the anomaly condition, forwarding the subset of risk-control commands to the online financial platform.

8. The computer system of claim 7 ,

wherein the particular type of risk-control command is configured to instruct the online financial platform to perform a particular action associated with a corresponding transaction;

wherein the particular set of risk-control policies is associated with a particular type of transaction; and

wherein the subset of risk-control commands further comprises a particular type of risk-control command associated with a particular risk-control policy, wherein the particular risk-control policy is associated with a particular type of risk.

9. The computer system of claim 7 , wherein the statistics associated with the monitored plurality of risk-control commands comprises one or more of:

the number of risk-control commands within the subset issued by the risk-control system over the predetermined time interval; and

the ratio between the number of risk-control commands within the subset and a total number of risk-control commands issued by the risk-control system over the predetermined time interval.

10. The computer system of claim 9 , wherein the anomaly condition is determined based on historical data associated with the subset of risk-control commands.

11. The computer system of claim 10 , wherein the anomaly condition is determined based on probability distribution of the number or the ratio and a predetermined confidence interval.

12. The computer system of claim 7 , wherein preventing the subset of risk-control commands from being forwarded to the online financial platform further comprises:

substituting the subset of risk-control commands using a second subset of risk-control commands, wherein the subset and second subset of risk-control commands are of different types; and

forwarding the second subset of risk-control commands to the online financial platform to facilitate the online financial platform in performing corresponding transactions according to the second subset of risk-control commands.

13. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising:

monitoring, by a computer, types and numbers of risk-control commands issued by a risk-control system, wherein the risk-control commands correspond to transactions associated with users which receive service from an online financial platform;

obtaining statistics associated with the monitored risk-control commands;

determining, based on the obtained statistics, whether a subset of risk-control commands meets an anomaly condition, wherein the subset comprises at least one of: a particular type of risk-control command; and a particular type of risk-control command associated with a particular set of a plurality of sets of risk-control policies,

wherein the plurality of sets of risk-control policies identify risks associated with a particular type of transaction,

wherein the plurality of sets include at least one of: a first set for identifying risks associated with fund transfers; a second set for identifying risks associated with deposits; and a third set for identifying risks associated with withdrawals,

wherein the first set further includes at least one of: a first policy for dealing with fraud risk; a second policy for dealing with money-laundering risk; and a third policy for dealing with identity theft risk, and

wherein the anomaly condition is based on the obtained statistics and a ratio between a number of risk-control commands within the subset and a total number of risk-control commands issued by the risk-control system over a predetermined time interval, wherein the anomaly condition specifies a higher threshold and a lower threshold, and wherein the subset of risk-control commands meets the anomaly condition if the number or the ratio is greater than the higher threshold or less than the lower threshold;

in response to determining that the subset of risk-control commands does not meet the anomaly condition, forwarding the subset of risk-control commands to the online financial platform to facilitate the online financial platform in performing corresponding transactions according to the subset of risk-control commands;

in response to determining that the subset of risk-control commands meets the anomaly condition, preventing the subset of risk-control commands from being forwarded to the online financial platform;

subsequent to preventing the subset of risk-control commands from being forwarded to the online financial platform, continuing to monitor the subset of risk-control commands to determine whether the subset of risk-control commands no longer meets the anomaly condition; and

in response to determining that the subset of risk-control commands no longer meets the anomaly condition, forwarding the subset of risk-control commands to the online financial platform.

14. The computer-readable storage medium of claim 13 ,

wherein the particular type of risk-control command is configured to instruct the online financial platform to perform a particular action associated with a corresponding transaction;

wherein the particular set of risk-control policies is associated with a particular type of transaction; and

wherein the subset of risk-control commands further comprises a particular type of risk-control command associated with a particular risk-control policy, wherein the particular risk-control policy is associated with a particular type of risk.

15. The computer-readable storage medium of claim 13 , wherein the statistics associated with the monitored plurality of risk-control commands comprises one or more of:

the number of risk-control commands within the subset issued by the risk-control system over the predetermined time interval; and

the ratio between the number of risk-control commands within the subset and the total number of risk-control commands issued by the risk-control system over the predetermined time interval.

16. The computer-readable storage medium of claim 13 , wherein preventing the subset of risk-control commands from being forwarded to the online financial platform further comprises:

substituting the subset of risk-control commands using a second subset of risk-control commands, wherein the subset and second subset of risk-control commands are of different types; and

forwarding the second subset of risk-control commands to the online financial platform to facilitate the online financial platform in performing corresponding transactions according to the second subset of risk-control command.