Abstract: The present disclosure relates to a method for determining optimal process flow (107) for a process performed by users (101) in a computing system. The method comprises receiving plurality of keystroke level events for each of plurality of process flows associated with the process, performed by plurality of users (101). Further, the method comprises determining one or more subtasks (105) for each of the plurality of process flows (102). A subtask comprises a set of events occurring together in the plurality of keystroke level events (103). Furthermore, the method comprises grouping one or more process flows from the plurality of process flows (102) to form one or more clusters (106), based on the one or more subtasks (105). Each cluster comprises the one or more process flows with similar subtasks. Thereafter, the method comprises determining an optimal process flow (107) in each cluster.

Abstract: The present disclosure relates to method and system for extracting information based on user interactions performed on screen of a computing system. Method includes receiving processed input data comprising video capturing screen and user interactions events occurring from user interactions, and co-ordinate information. Thereafter, computing system determines Regions of Interest (RoI) on screen based on captured user interactions, events and co-ordinate information, and identifies type of user interaction performed with at least one screen element in the RoI, as either keyboard or mouse type interaction. Subsequently, computing system performs one of: determining type of screen element as a text box or a table based on pattern recognition when type of user interaction is identified as keyboard type interaction or determining type of screen element to be selectable User Interface elements and extracting content and label of selectable UI elements, when interaction is identified as mouse type interaction.

Abstract: The present disclosure relates to a method for determining optimal process flow (107) for a process performed by users (101) in a computing system. The method comprises receiving plurality of keystroke level events for each of plurality of process flows associated with the process, performed by plurality of users (101). Further, the method comprises determining one or more subtasks (105) for each of the plurality of process flows (102). A subtask comprises a set of events occurring together in the plurality of keystroke level events (103). Furthermore, the method comprises grouping one or more process flows from the plurality of process flows (102) to form one or more clusters (106), based on the one or more subtasks (105). Each cluster comprises the one or more process flows with similar subtasks. Thereafter, the method comprises determining an optimal process flow (107) in each cluster.

Abstract: An organizational fraud detection (OFD) system and method for flagging one or more transactions as a potential fraudulent activity, in an organization is disclosed. The OFD system comprises: a processor; and 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, 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.