Increase the Percentage of Fraudulent Checks Identified by System in Real-time

100 %

Reduction in fraudulent transactions.

$ 0 M

Annual savings on fraud losses.

0 %

Reduction in manual check validation operating costs.

The Process

Even with lower check-processing times due to electronic payments and automated clearing house (ACH) transactions, banks must still manually verify millions of handwritten checks. Annually, banks risk losing millions as a result of check fraud by counterfeiters. Because a percentage of the funds is made readily available to the depositors, it’s critical to identify counterfeit checks quickly. To reduce the incidence of check fraud, a global bank partnered with us to build a solution based on Artificial Intelligence (AI) machine learning to speed up check verification.

The Solution

The solution needed to identify fraudulent checks in real-time, as well as reduce the number of checks requiring manual review. Aiwozo achieved this using its Optical Character Recognition (OCR) and deep learning technology to scan checks, process data, and verify signatures. Aiwozo’s model, based on Google TensorFlow™, uses a neural network to parse a historical database of previously scanned checks, including those known to be fraudulent. We trained the neural network to use a set of comparative algorithms to distinguish proper checks from anomalous ones. By automatically comparing various factors on scans of deposited checks to those in the database.