Since the end of the 1990s WonderNet has been the market leader in personal digital signature capturing and identification based on electronic biometric signature data. Together with the Hebrew University in Jerusalem, WonderNet investigated the nature of the human signature and developed mathematical methods to compare such electronic biometric signatures against pre-enrolled signature profiles. Bank Hapoalim, Israel’s largest bank and financial group, and WACOM Co. Ltd. Japan, were both investors in WonderNet at that time.

Early adopters helped to improve this technology:

• The Israeli Air force uses this technology; for example, to check signatures on airplane maintenance protocols.
• Ono Academic College (OAC), a leading Israeli institution of higher education, facilitates contract signing with SIGNificant. Lecturer recruiting became easy to manage administratively, with controlled budget approvals which are biometrically authenticated in real-time, in order to secure the process.
• …and many more, including Bank Hapoalim as mentioned above.

On February 14, 2008 xyzmo shareholders bought the entire IP rights of WonderNet Ltd. (Penflow) including the most prominent technology for electronic biometric signature authentication. By incorporating this technology from WonderNet, xyzmo SIGNificant became a major international company in its field, with offices in Austria, the US and Germany, and represented by many Value-Added Resellers worldwide.

The major advantage over other solutions on the market today is that our technology is able to compare a signature against a profile which is self-learning over time. Only this approach guarantees appropriate results for signature verification and authentication, respectively, because it is human nature never to sign twice in exactly the same way, and also to alter the signature constantly over a life-time.

• A comparison with only one sample signature is mathematically much easier to handle, and thus some companies offer essentially inaccurate solutions. These “low level” solutions merely pick one random signature as a basis for the comparison. This approach only works for people who always sign in exactly the same way. Most human beings do not behave like that, and thus this approach is simply not feasible for a broader usage of that technology. Anyone can easily prove this by asking 10 random people to sign 6 times in a row, on a blank sheet of paper, in order to see how different most of these signatures are.
• A more sophisticated but still not satisfactory approach is to build a solution which takes several signatures – a profile – into consideration at the time of real-time comparison, but still using a static profile which is not self-learning. This will deliver, at the start, better results than a comparison with just one signature, but the comparison will get less and less accurate over time. This will happen for nearly 100% of human subjects.

To summarize: only the xyzmo SIGNificant approach – based on self-learning profiles – really works in the long run with sufficient accuracy.

The SIGNificant Biometric Server takes the ability of self-learning profiles one step further, by using a sophisticated algorithm when building a signature profile, initially by recognizing if such a profile is of sufficient quality or not. In particular, when people sign for the first time on a signature pad they change their signing behavior a little bit, and adjust it after they get used to this new technology, or new way of signing on a signature tablet, until it becomes the “usual” way. Thus it is business-critical to take more than 2 or 3 samples for each profile and, on top of that, to check by intelligent algorithms if these profiles are a robust base for the later verification. It is much better to reject improper signatures out of a profile at this stage, namely, at the time of creating such a profile, and ask a customer to sign one additional time, instead of generating a wrong profile and “try” to use this for later comparison.

The area of electronic biometric signature verification/authentication on a large scale has just started with such high-quality standards as xyzmo introduces them to the market. There are, meanwhile, early adopters in Europe like a German company  for checking signatures on quality assurance documents, or a bank which authenticates all their customers in real-time based on their handwritten electronic biometric signature with our advanced and superior technology as described. This will become a huge market over the next few years, and xyzmo sees itself clearly in the leading position and far ahead of the competition with the best and most advanced solution available. Self-Learning profiles will be the key!