siliconindia | | May 20179As we continue to rely on wet ink signatures, the role and responsibility of signature verification automation will be to eliminate all the negative aspects of human verificationPreventing Fraudulent TransactionsRelying on human experts to authenticate signatures is nei-ther error-free nor cost effective. Unfortunately, this means that many businesses and financial institutions focus on having their staff verify only the highest risk, high-value transactions which can leave those organizations vulnera-ble to fraud. Many examples are available directly from news headlines where fraud has been perpetrated through simply forging signatures. Forgeries can be divided into three basic categories:· Random Signature Forgery: Random forgeries do not attempt to match the name or the style of the individual's genuine signature. It is simply a signature (e.g., Tabatha Smith to John Prasad).· Blind Signature Forgery: Blind forgeries match the signature name (e.g., John Prasad to John Prasad), but do not attempt to match the style of the individual's genuine signature.· Skilled Signature Forgery: Skilled forgeries are the most difficult to identify because they try to match the name and style of the individual's genuine signature (e.g., John Prasad to John Prasad).Signature verification automation software can play a critical role here in fraud prevention, ensuring that all documents (checks and other signed documents) undergo signature verification. This can be extremely high volumes of documents-many 100s of thousands daily if not more. There are many instances where signature verification is necessary in automated fraud management, transaction au-thorization, absentee ballots, voting registration, timesheets and much more. The entire automated verification process itself can be compared to the work of a group of highly skilled experts. Each verification process uses a specific approach and set of algorithms, looking at particular characteristics, which is especially efficient in some cases and `good-enough' in others. Once these approaches are combined and optimized, their areas of expertise complement each other, which re-sults in excellent overall performance and accurate fraud detection. Signature verification software is very efficient, accurate and consistent. It has proven to outperform humans on even the most difficult types of forgery. Software can use many dif-ferent authentic reference images to improve accu-racy; humans typically do worse when dealing with more than two or three reference signatures.And yet, humans con-tinue to be integral to signa-ture verification and fraud prevention. Human scrutiny is highly analytical and com-plements the steady, unwavering predictability of software algorithms. To eliminate fraud, the best solutions use soft-ware verification automation and human exception-han-dling that reviews less than one percent of signatures in cases where the software reports low confidence levels.How Does AI Succeed Over Humans?Several different techniques and technologies are employed to mimic the best of what the human brain can achieve, which would take a book to describe in sufficient detail. At the highest level though, there are simply three key areas to highlight that signature verification AI software uses:1. Special descriptive language2. Signature segmentation, and 3. Neural networks These three key elements when combined with a stellar `supporting cast' of other complementary techniques, drive a reliable and thorough verification `engine'.Heading into the FutureAs we continue to rely on wet ink signatures, the role and responsibility of signature verification automation will be to eliminate all the negative aspects of human verification. Software doesn't get tired or have a bad day. It can pro-cess dramatically higher volumes of signatures at a fraction of the time and cost, as well as consistently demonstrate higher accuracy. For skilled forgeries, the most difficult, where the fraudster understands common ways to copy a signature and may even implement variations just to try and fool deeper analysis, these most rare instances that confound even the most advanced AI will continue to require the eye of a highly trained signature verification expert who can analyze the signature based on the individual's genuine signature and validate whether the signature in question is truly authentic. Mark Gallagher
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