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Analytics Magazine

FICO: Four analytic breakthroughs that drive smarter decisions

Denis Ismagilov http://www.123rf.com/profile_ismagilov

Photo Courtesy of 123rf.com | © Denis Ismagilov

Four analytic technologies recently patented by analytic software firm FICO are being incorporated into solutions for cyber security, the Internet of Things (IoT), model governance and optimization.

“Patents are the currency of innovation, in software or any other technology sector,” says Scott Zoldi, chief analytics officer at FICO, posted on the FICO Blog. “These technologies have made the jump from FICO’s research labs to our solutions, where they will help our customers solve some of the most challenging and strategic problems.”

The patents include:

Collaborative profiling. FICO’s patent for collaborative profiling provides an efficient way to recognize when a person’s behavior is changing and to rank-order the significance of those behavioral changes across many individuals.

FICO’s method distills a history of events/transactions down to a limited number of behavioral “archetypes.” Individuals become described in continually adjusting archetype distributions that can distinguish normal anticipated behaviors from risky/abnormal changes in behavior. This technology can be used to monitor for cyber security threats and fraudulent payment activity. The deep insights of the archetypes also allow marketers to focus campaigns on the most relevant consumers.

Structuring IoT messages. The IoT is composed of billions of devices that emit vast amounts of data, often in free-form text messages. Organizations are trying to better leverage this massive, yet largely unstructured, set of data producers in more automated and effective ways. To do this, the log messages must be parsed efficiently so advanced analytics can be used to recognize anomalies and predict future events.

FICO earned a patent by inventing a way to statistically parse unstructured data and determine typical temporal sequences. The key to this method for IoT is fast-streaming self-learning analytics that run efficiently at a very large scale. This technology is intended to improve the management and security of IoT devices, which can be anything from cars to factory equipment to household appliances to cable TV boxes.

Neural networks in model governance. Model governance is a challenge for organizations that use predictive analytics for mission-critical tasks, such as making lending decisions. Models tend to lose their effectiveness over time. FICO’s patented autoencoder self-diagnostic technology provides ongoing model validation to help ensure models in production environments are properly suited to future changes in data and behaviors.

Autoencoding is a class of neural network. Autoencoders learn to mimic input data through a representation of complex interactions between different latent factors. This can be used to understand data that moves away from what a model was originally trained on, or to identify segments of data that are underrepresented in a model.

New optimization technology. As firms in every industry pursue decision optimization, FICO patented a new method of automating complex analytic tasks required to optimize marketing offers. FICO’s technology creates a dynamic system capable of self-learning the optimal strategy after a few iterations of a test-and-learn cycle. This will allow companies to respond more quickly to the challenge of changing market conditions and customer demands.

“While these four patents have specific use cases today, they can also be applied to many additional business problems,” Zoldi says. “FICO is working aggressively to build these patented technologies into new products as well as work on the next generation of machine learning technologies.”

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