Dynamic validation of system transactions based on machine learning analysis

A system for applying machine learning to dynamically validate a sales transaction document created by a user in a computing system, the system comprising:

• one or more data processors having memory storing instructions, which when executed result in operations comprising:
• receiving data comprising the sales transaction document;
• applying a machine learning model to the sales transaction document to verify that the sales transaction document meets at least one compliance standard;
• dynamically generating, using the machine learning model, a probability of compliance with the at least one compliance standard based on first sales transaction data;
• alerting the user if the sales transaction document does not meet the at least one compliance standard;
• receiving second sales transaction data from the database;
• and
• adjusting the machine learning model based on the second sales transaction data,
• wherein the machine learning model is trained by:
• receiving the first sales transaction data from a database;
• training the machine learning model using the first sales transaction data;
• determining and subsequently analyzing patterns based on the first sales transaction data, wherein the patterns indicate that corrective data was created to compensate for at least one error in original data, the at least one error indicating that the original data did not meet at least one compliance standard, wherein the corrective data comprises a change to a noncompliant sales transaction document in the first sales transaction data;
• and
• training the machine learning model, after the training using the first sales transaction data, based on the determined patterns.

A non-transitory computer readable storage medium storing one or more programs configured to be executed by one or more data processors, the one or more programs comprising instructions for applying machine learning to dynamically validate a sales transaction document created by a user in a computing system, the instructions comprising:

• receiving data comprising the sales transaction document;
• applying a machine learning model to the sales transaction document to verify that the sales transaction document meets at least one compliance standard;
• dynamically generating, using the machine learning model, a probability of compliance with the at least one compliance standard based on first sales transaction data;
• alerting the user if the sales transaction document does not meet the at least one compliance standard;
• receiving second sales transaction data from the database;
• and
• adjusting the machine learning model based on the second sales transaction data,
• wherein the machine learning model is trained by:
• receiving the first sales transaction data from a database;
• training the machine learning model using the first sales transaction data;
• determining and subsequently analyzing patterns based on the first sales transaction data, wherein the patterns indicate that corrective data was created to compensate for at least one error in original data, the at least one error indicating that the original data did not meet at least one compliance standard, wherein the corrective data comprises a change to a noncompliant sales transaction document in the first sales transaction data;
• and
• training the machine learning model, after the training using the first sales transaction data, based on the determined patterns.