Next Steps

Arity Corporation

Arity Corporation leads the way in the use of Linked Data and Social Learning for Performance Support.

We build life-preservers for individuals and organizations that are drowning in data and tools. We are passionate about facilitating innovation, insight, and collaboration to enable people to solve complex problems and create breakthrough solutions.

To achieve this, we have solved a great many problems in the understanding of content and context of knowledge within documents and as expressed by people's goals and workflow needs while performing research. We are expert at natural language understanding, knowledge representation, recommendation, and reasoning technologies.

Banking & Finance

Arity has a rich history in the creation of solutions for the Banking and Finance industries. One success story is particularly illustrative:

While EXPRESSway was still a glimmer in our future plans, we were approached by Bank of Boston (now part of Bank of America). They were already a customer of ours using some of our technology to build expert systems for parts of the mortgage origination process. Their request, made very urgently, was for Arity to investigate the problems related to several forms of fraud that hit demand deposit (checking) accounts. Several large account frauds had created some sizable losses for the bank. While they had a group of talented people who were responsible for detecting frauds and had purchased at considerable expense some products that attempted to flag suspects, the process was largely uneffective.

What we realized was this: Everyone creating an account fraud has a system and, whether tracked on the back of an envelope or in a spreadsheet, keeps up a pattern of behavior.

Patterns of behavior from systems leave telltale signs in observed data - even if masked. For account frauds, the fraudulent behavior may be embedded in a sea of legitimate activity, but if you know how to look, you will see it. The way to look is to have some models of fraud in mind, then to see how well the observed data (the credits and debits in this case) can fit into the model. Simply, if the data fits an appropriate model of fraud well enough, then the account is very suspect.

Arity created an application which was predictive of on-going account fraud behavior. And, by being predictive, we could also explain past behavior in ways that would be readily understood by those who needed the evidence to take action (such as freezing the accounts of the suspect).

We sold the product rights to a banking-related subsidiary of IBM and the products are now part of an offering from Fiserv.

The relevance to EXPRESSway and Semantic Studio is this: The nature of our solution was less about the calculation of financial numbers (such as balance) and more about the relatedness (the links) within the data. The way we enabled the fraud group to envision why an account holder was suspect was that we enabled a visualization of the relevant aspects of the account-holders behavior. This is the very essence of EXPRESSway and Semantic Studio.

EXPRESSway can improve understanding, prediction, and decision-making within the Banking and Finance industries by providing faster and clearer access to relevant knowledge within proprietary data, Web-based resources, and other people.