Fair Isaac Corporation

Sergei Tolmanov

Stuart L Crawford

Megan Thorsen

Navin Doshi

Michael Steele

Kashyap Babu Rao Kolipaka

Gaurav Chhaparwal

Chris Erickson

Ashutosh Joshi

Shailesh Kumar

Prasun Kumar

Helen Geraldine E Rosario

Colin Little

Victor Miagkikh

Fraud detection is facilitated by developing account cluster membership rules and converting them to database queries via an examination of clusters of linked accounts abstracted from the customer database. The cluster membership rules are based upon certain observed data patterns associated with potentially fraudulent activity. In one embodiment, account clusters are grouped around behavior patterns exhibited by imposters. The system then identifies those clusters exhibiting a high probability of fraud and builds cluster membership rules for identifying subsequent accounts that match those rules. The rules are designed to define the parameters of the identified clusters. When the rules are deployed in a transaction blocking system, when a rule pertaining to an identified fraudulent cluster is triggered, the transaction blocking system blocks the transaction with respect to new users who enter the website.

Systems and methods for fraud detection via interactive link analysis

A product space browser (PSB), which comprises a graphical user interface (GUI) that facilitates insight discovery through exploration and analysis of product space graphs generated by applying a product affinity engine to retailer's transaction data in a market basket context, is disclosed.

Product space browser

Techniques for visualization of decision logic are provided. In one aspect, the techniques can be implemented by providing a control within a graphical user interface to a user. The control can display a plurality of graphical user interface elements corresponding to linked nodes within a hierarchical structure. An input identifying a selected graphical user interface element within the control can be generated by a user. A selected node within the hierarchical structure can be identified based on the selected graphical user interface element. In response to a request from a user, modifying an appearance of a subset of the linked nodes within the hierarchical structure based on a desired visualization criteria, the linked nodes within the hierarchical structure and the selected node.

Visualization of decision logic

A request to compare strategies is received. The first strategy can be graphically represented by a first set of linked nodes arranged in a first form of decision logic. The second strategy can be graphically represented by a second set of linked nodes arranged in a second form of decision logic. The first set of linked nodes can be converted to a first modified set of linked nodes arranged in a third form of decision logic. The second set of linked nodes can be converted to a second modified set of linked nodes arranged in the third form of decision logic. A color-coded visual representation of the first modified set of linked nodes and the second modified set of linked nodes can be provided to a user. Related apparatus, techniques, and articles are also described.

Color-coded visual comparison of decision logic

Data characterizing a plurality of related action graphs is received. Thereafter, the plurality of related action graphs are transformed into a logically equivalent structure so that rendering of the logically equivalent structure can be initiated. Related interfaces, apparatus, systems, techniques and articles are also described.

Construction of decision logic with graphs

Techniques are described for logically comparing strategies. In one aspect the strategies can be compared by receiving a request to compare a first strategy to a second strategy, the first strategy graphically represented by a first set of linked nodes, the second strategy graphically represented by a second set of linked nodes, each set of linked nodes linking a root node to at least one action node; identifying a subset of linked nodes from at least one of the first set of linked nodes and the second set of linked nodes based on an equivalence of a first subset of the first set of linked nodes to a second subset of the second set of linked nodes; and, providing a visual depiction of the identified subset of the linked nodes to a user, the visual depiction corresponding to the equivalence of the first subset to the second subset.

Decision logic comparison and review

The invention provides a purchase sequence browser (PuSB), i.e. a graphical user interface (GUI) that facilitates insight discovery and exploration of product affinities across time, generated by a purchase sequence analysis of a retailer's transaction data. A purchase sequence browser allows the user to browse the most significant product phrases discovered by an exhaustive search of the product affinities across time; explore the retail grammar to create both forward and backward phrase trees or alternate purchase paths starting from, or ending in, a product; generate consistent purchase sequences given some constraints on the products and their order; and profile the value of a product across time with regard to other products fixed in time.

Purchase sequence browser

The invention comprises an article and method for transforming a complex or large decision tree having multiple variables; multiple values for each variable; and, multiple outcomes for each combination of variables and their associated values, into a compact, efficient graphical representation to provided enhanced ease of use and interaction by a human user. More particularly, the invention comprises a computationally efficient method for transforming an input decision tree into an optimal compact representation by computing a particular ordering of variables in the decision tree that first leads to a Directed Acyclic Graph, or 'DAG,' with a minimum number of nodes. The method then converts the DAG into an exception-based DAG, or 'EDAG,' with exactly one exception, having an optimal, minimum number of nodes with increased comprehensibility for a user.

Growing community of inventors

Walnut Creek, CA, United States of America

Sergei Tolmanov