Machine learning protection of automated document processing
An increasing number of companies and financial institutions are moving their activities from physical offices to web-based processes. This trend has been strongly accelerated by COVID-19 and the consequences of the enforced restrictions. Documents previously verified and scanned by employees are now being uploaded directly online or sent via email.
Such a remote process is prone to forgeries on the clients’ side. Some clients try to improve their credit score or even attempt to commit fraud by manipulating the electronic documents before sending them. The repetitive nature of document investigation leads to human errors, unproductiveness and tends to become unpopular among employees and firms at the same time. In many cases it is also impossible to detect advanced fraud techniques with a naked eye.
The solution consists of machine learning and decision-based modules that calculate the overall "Trust & Risk Score" of a document. It automatically inspects digital documents for signs of manipulation and raises an alert when a modification, file corruption, or other anomaly is found as well as marks documents that can be trusted and do not require further investigation anymore. Results of the model are delivered in a few seconds via several channels such as GUI, REST API or UiPath platforms.
- Increased fraud detection
- Strongly reduced manual labor and repetitive tasks
- No human error
- Reduced costs and processing time
- Very low number of false alarms