Abstract: Techniques for expense report submission are disclosed. An expense report submission system receives, via a graphical user interface, a user query that corresponds to requesting whether a particular expense is allowed. The expense report submission system applies the user query to a machine learning model configured to evaluate data associated with expenses against one or more expense policy rules. The expense report submission system generates a response to the user query based at least on a result of applying the user query to the machine learning model. The response to the user query indicates whether the expense is allowed based at least on the expense reporting rule(s). The expense report submission system presents, in the graphical user interface, the response to the user query.

Abstract: Techniques for expense report submission are disclosed. An expense report submission system receives, via a graphical user interface, a user query that corresponds to requesting whether a particular expense is allowed. The expense report submission system applies the user query to a machine learning model configured to evaluate data associated with expenses against one or more expense policy rules. The expense report submission system generates a response to the user query based at least on a result of applying the user query to the machine learning model. The response to the user query indicates whether the expense is allowed based at least on the expense reporting rule(s). The expense report submission system presents, in the graphical user interface, the response to the user query.

Abstract: Techniques for expense report submission are disclosed. An expense report submission system receives, via a graphical user interface, a user query that corresponds to requesting whether a particular expense is allowed. The expense report submission system applies the user query to a machine learning model configured to evaluate data associated with expenses against one or more expense policy rules. The expense report submission system generates a response to the user query based at least on a result of applying the user query to the machine learning model. The response to the user query indicates whether the expense is allowed based at least on the expense reporting rule(s). The expense report submission system presents, in the graphical user interface, the response to the user query.

Abstract: Techniques for real-time expense auditing and machine learning are disclosed. An expense auditing system trains a machine learning model to compute audit risk scores as a function of expense descriptions. The auditing system receives an expense description associated with an employee. The expense auditing system computes, using the trained machine learning model, an audit risk score associated with the expense description. The expense auditing system compares the audit risk score with an audit trigger. The audit trigger includes one or more conditions that, when satisfied, identifies expense descriptions that are at risk of being audited. The expense auditing system determines that the audit risk score satisfies the audit trigger. Responsive to determining that the audit risk score satisfies the audit trigger, the expense auditing system alerts the employee that the expense description is at risk of being audited.

Abstract: Techniques for expense report submission are disclosed. An expense report submission system receives, via a graphical user interface, a user query that corresponds to requesting whether a particular expense is allowed. The expense report submission system applies the user query to a machine learning model configured to evaluate data associated with expenses against one or more expense policy rules. The expense report submission system generates a response to the user query based at least on a result of applying the user query to the machine learning model. The response to the user query indicates whether the expense is allowed based at least on the expense reporting rule(s). The expense report submission system presents, in the graphical user interface, the response to the user query.

Abstract: Techniques for presenting an expense report reviewing interface are disclosed. An expense auditing system receives expense descriptions associated with expenses incurred by one or more employees. The expense auditing system determines associations between the expense descriptions and geographical locations where the expenses were incurred. The expense auditing system presents a graphical user interface that includes: (a) a geographical map representing the geographical locations where the expenses were incurred; and (b) an expense auditing overlay that, based at least on the associations between the expense descriptions and the geographical locations where the expenses were incurred, visually associates the expenses with corresponding locations on the geographical map.

Abstract: Techniques for generating an expense report are disclosed. An expense report generation system monitors one or more data sources to obtain data corresponding to an employee's target activity. The expense report generation system compares the data corresponding to the employee's target activity with an expense trigger. The expense trigger includes one or more conditions that, when satisfied, identify an expense associated with the employee's target activity. The expense report generation system determines that the data corresponding to the employee's target activity satisfies the expense trigger. Responsive to determining that the data corresponding to the employee's target activity satisfies the expense trigger, the expense report generation system generates an expense description for the expense. The expense report generation system generates an expense report including the expense description.