User data augmented propensity model for determining a future financial requirement

A system, comprising:

• a hardware processor and memory;
• and
• software instructions stored in the memory and configured to execute on the hardware processor, which, when executed by the hardware processor, cause the hardware processor to:
• obtain a propensity model that models how data of a business entity relates to a future financial requirement of the business entity;
• obtain audit history data including a record of discrete actions, previously performed on a platform, by users associated with the business entity;
• obtain clickstream data including a record of performed actions that are performed on the platform by the users associated with the business entity, wherein the platform records, as at least a portion of the clickstream data being obtained, a navigation to a reports portion of the platform, a trigger for generation of a payroll report, and a view of the payroll report;
• gather the data of the business entity,
• wherein the data includes financial data of the business entity and metadata,
• wherein the metadata includes the audit history data,
• wherein the metadata includes the clickstream data, and
• wherein the data matches at least a subset of the propensity model;
• score the business entity by applying the propensity model to the financial data, the audit history data, and the clickstream data;
• generate, based on the score of the business entity from the propensity model, the financial data, the audit history data, and the clickstream data, a classification of the future financial requirement of the business entity;
• and
• transmit a message to the business entity based on the classification of the future financial requirement of the business entity.

A non-transitory computer readable medium storing instructions, the instructions, when executed by a computer processor, comprising functionality for:

• obtaining a propensity model that models how data of a business entity relates to a future financial requirement of the business entity;
• obtaining audit history data including a record of discrete actions, previously performed on a platform, by users associated with the business entity;
• obtaining clickstream data including a record of performed actions that are performed on the platform by the users associated with the business entity, wherein the platform records, as at least a portion of the clickstream data being obtained, a navigation to a reports portion of the platform, a trigger for generation of a payroll report, and a view of the payroll report;
• gathering the data of the business entity,
• wherein the data includes financial data of the business entity and metadata,
• wherein the metadata includes the audit history data,
• wherein the metadata includes the clickstream data, and
• wherein the data matches at least a subset of the propensity model;
• scoring the business entity by applying the propensity model to the financial data, the audit history data, and the clickstream data;
• generating, based on the score of the business entity from the propensity model, the financial data, the audit history data, and the clickstream data, a classification of the future financial requirement of the business entity;
• and
• transmitting a message to the business entity based on the classification of the future financial requirement of the business entity.