CLIAMS:We claim:
1. An organizational fraud detection (OFD) system, for flagging one or more transactions as a potential fraudulent activity, in an organization, the OFD system comprising:
a processor;
a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, cause the processor to:
receive a suspected transaction for investigation, wherein the suspected transaction comprises one or more sub-transactions;
classify the suspected transaction into one or more groups of fraudulent activity;
select, based on the classification, a set of investigation rules for investigating the suspected transaction;
determine, based on data selection rules, the data associated with the suspected transaction;
ascertain an accuracy score and an impact score associated with the suspected transaction; and
classify the suspected transaction as a potential fraudulent activity on at least one of the accuracy score and the impact score exceeding a pre-defined threshold.

2. The OFD system, as claimed in claim 1, wherein the investigation rules are selected based on a People, Location, Object, Time (PLOT) model.

3. The OFD system, as claimed in claim 1, wherein the instructions, on execution, further cause the processor to:
receive feedback on whether a suspected transaction, classified as a potential fraudulent activity, is one of a false positive or a fraud activity;
determine, based on the received feedback, modifications to be made to at least one of the investigation rules and data selection rules; and

amend at least one of the investigation rules and data selection rules, based on the determined modifications.

4. The OFD system, as claimed in claim 1, wherein the instructions, on execution, further causes the processor to:
determine one or more data repositories which store the data associated with the suspected transaction; and
generate queries to retrieve the data associated with the suspected transaction from the one or more data repositories.

5. The OFD system, as claimed in claim 1, wherein the instructions, on execution, further causes the processor to:
analyze at least one of an organizational graph, related sub-transactions, and related transactions to determine patterns in the suspected transaction;
ascertain relationships between the users involved in at least one of the related sub-transactions, related transactions, and sub-transactions of the suspected transaction to identify group involvement in the suspected transaction; and
revise at least one of the accuracy score and the impact score associated with the suspected transaction, based on at least one of the determined patterns and the ascertained relationships.

6. The OFD system, as claimed in claim 1, wherein the instructions, on execution, further causes the processor to:
generate, based on at least one of the accuracy score and the impact score associated with the suspected transaction, one or more subsequent actions to mitigate the risks associated with the suspected transaction; and
execute the generated one or more subsequent actions.

7. The OFD system as claimed in claim 1, wherein the instructions, on execution, further cause the processor to:
monitor one or more sub-transactions in an organization;
identify breaches in the monitored sub-transactions;
determine patterns in the identified breaches;
ascertain the accuracy score and the impact score associated with the sub-transactions, based on the determined patterns;
classify the sub-transactions as a single fraudulent transaction, based on the determined patterns and at least one of the accuracy score and the impact score.
8. A computer implemented method for flagging one or more transactions as a potential fraudulent activity, in an organization, the method comprising:
receiving a suspected transaction for investigation, wherein the suspected transaction comprises one or more sub-transactions;
classifying the suspected transaction into one or more groups of fraudulent activity;
selecting, based on the classification, a set of investigation rules for investigating the suspected transaction;
determining, based on data selection rules, the data associated with the suspected transaction;
ascertaining an accuracy score and an impact score associated with the suspected transaction; and
classifying the suspected transaction as a potential fraudulent activity on at least one of the accuracy score and the impact score exceeding a pre-defined threshold.

9. The method as claimed in claim 8, wherein the investigation rules are selected based on a People, Location, Object, Time (PLOT) model.
10. The method as claimed in claim 8, wherein the method further comprises:
receiving feedback on whether a suspected transaction, classified as a potential fraudulent activity, is one of a false positive or a fraud activity;
determining, based on the received feedback, modifications to be made to at least one of the investigation rules and data selection rules; and
amending at least one of the investigation rules and data selection rules, based on the determined modifications

11. The method as claimed in claim 8, wherein the method further comprises:
determining one or more data repositories which store the data associated with the suspected transaction; and
generating queries to retrieve the data associated from the one or more data repositories.
12. The method as claimed in claim 8, wherein the method further comprises:
analyzing at least one of an organizational graph, related sub-transactions, and related transactions to determine patterns in the suspected transaction;
ascertaining relationships between the users involved in at least one of the related sub-transactions, related transactions, and sub-transactions of the suspected transaction to identify group involvement in the suspected transaction; and
revising at least one of the accuracy score and the impact score associated with the suspected transaction, based on at least one of the determined patterns and the ascertained relationships.

13. The method as claimed in claim 8, wherein the method further comprises:
generating, based on at least one of the accuracy score and the impact score associated with the suspected transaction, one or more subsequent actions to mitigate the risks associated with the suspected transaction; and
executing the generated one or more subsequent actions. .

14. The method as claimed in claim 8, wherein the method further comprises:
monitoring one or more sub-transactions in an organization;
identifying breaches in the monitored sub-transactions;
determining patterns in the identified breaches;
ascertaining the accuracy score and the impact score associated with the sub-transactions, based on the determined patters;
classifying the sub-transactions as a single fraudulent transaction, based on the determined patterns and at least one of the accuracy score and the impact score.

15. A non-transitory computer readable medium comprising a set of computer executable instructions, which, when executed on a computing system causes the computing system to perform the steps of:
receiving a suspected transaction for investigation, wherein the suspected transaction comprises one or more sub-transactions;
classifying the suspected transaction into one or more groups of fraudulent activity;
selecting, based on the classification, a set of investigation rules for investigating the suspected transaction;
determining, based on data selection rules, the data associated with the suspected transaction;
ascertaining an accuracy score and an impact score associated with the suspected transaction; and
classifying the suspected transaction as a potential fraudulent activity on at least one of the accuracy score and the impact score exceeding a pre-defined threshold.

Dated this 15th day of January, 2015

Swetha S.N
Of K&S Partners
Agent for the Applicant
,TagSPECI:TECHNICAL FIELD
The present subject matter is related, in general to compliance monitoring of transactions in an organization and, in particular but not exclusively to, a method and system for flagging one or more transactions as a potential fraudulent activity, in an organization.