Check fraud results in the loss of billions of dollars a year for banks, financial institutions and retailers, regardless of size or location. Identity falsification, in particular, formerly the specialty of professional forgers, has become widespread. Advances in technology are partly to blame. Highly-sophisticated and low-cost technology is now available to criminals, allowing them to hone their skills in creating counterfeit checks and forging signatures. The result is a new level of perpetrator sophistication that requires an increased level of alertness for institutions looking to protect themselves from check fraud losses. Banks and financial institutions are now turning to advanced fraud protection tools for assistance.

As with any new technology, there are challenges and opportunities: while criminals have access to more sophisticated technology with which to attack institutions with weak defenses, new technology arms financial institutions with multiple effective means to fight fraud. Today, the market offers a variety of extensive, efficient fraud prevention solutions that are cost effective for both large banks and smaller institutions. The goal for any organization is to identify the main areas of fraud risk, define the scope of the fraud prevention measures that can be supported and use the most advanced, efficient and cost effective technology available in the market to combat fraud. State-of-the-art automated signature verification, for instance, is a technology that can be easily adapted to a financial institution's needs and efficiently applied to detect and prevent fraud regardless of the organization's type and size. Manual signature verification has been one of the most common fraud prevention methods and has remained unchanged for many decades. Meanwhile, signature forgery has become one of the biggest security problems challenging financial institutions. According to recent studies, 26% of all fraudulent checks are signature forgeries1, and over 500 million checks are forged annually in the United States. Clearly, with 32.3 billion checks written each year in the United States2, it is neither practical nor cost-effective to visually compare signatures on the hundreds of millions of checks processed daily. Nor has visual comparison proven to be reliable; many banks have found that due to the increased volume of lower dollar checks and higher quality of forgeries, many pass through a visual review undetected. Consequently, as the need to guarantee the authenticity of each document remains urgent, this task requires more efficient, controlled and reliable methods of signature verification. New signature verification systems leverage artificial intelligence and exploit the most comprehensive and advanced methods available for automated signature verification. In such systems, automatic comparison is executed by a powerful combination of verifiers using multiple, fundamentally different algorithms and techniques. In particular, they combine a human-like holistic analysis of a signature and signature segmentation with a subsequent analysis of the signature elements, using geometrical analysis, an analytical method based on signature segmentation and finding correlations between the fragments of reference and suspect signatures, dozens of neural networks and many other innovative techniques. The whole verification process can be described as the work of a group of highly-skilled experts. Each of them has a favorite approach, which is especially efficient in specific cases and “good enough” in others. Additionally, each of them has a special area of expertise, which may be viewed as a distinctive characteristic of a particular verifier. When they are combined, their areas of expertise complement each other to result in excellent performance. Similarly, all signature verifiers apply various approaches to analyze dozens of characteristics of a signature.

New systems employing advances in pattern recognition technology and biometric authentication techniques outperform both automation products of previous generations and visual verification in their abilities to detect signature forgeries. This performance breakthrough allows financial institutions to automatically and accurately process up to 99% of suspects, reducing the number of signatures that have to be manually reviewed by up to one percent.