BOZEMAN, Mont.--(BUSINESS WIRE)--

FICO (NYSE: FICO):

Highlights:

• FICO has been awarded 12 patents in AI, digital decisions, and blockchain model governance.
• New patents provide demonstrated innovation and creation of unique industry IP that help enterprises make better, more accountable decisions.
• To date, FICO’s patent portfolio consists of 213 active patents, with an additional 80 patent applications filed and pending.
• For more than three decades, FICO has built a culture of innovation to develop unique IP in AI operationalization, model governance, and machine learning applications.

Global analytics software firm FICO (NYSE: FICO), has been awarded 12 patents related to digital decisioning in the areas of blockchain model governance and artificial intelligence (AI) and machine learning technology. FICO’s culture of innovation and leading position in AI solutions provides the ability to operationalize personal customer experiences and business outcomes at scale and in a timely manner. These innovations are part of and other FICO solutions.

“FICO has been a global trailblazer in industry-specific AI and machine learning inventions for more than three decades,” said Scott Zoldi, chief analytics officer at FICO. “We have built a culture of innovation to develop unique IP in AI operationalization, model governance, and machine learning applications. Our advances in AI and machine learning drive the operationalization of responsible AI capabilities, which in turn power better decisions, increase revenues, and provide more rewarding customer experiences for businesses worldwide.”

FICO’s new patents include:

• “Efficient Association of Related Entities” – Relating to identification and tracking of associations between related entities in a distributed computing environment to readily determine associations between entities known to be involved in fraud.
• “Blockchain for Data and Model Governance” – Covering the concept of a shared ledger that is leveraged to track end-to-end provenance of the development, operationalization, and monitoring of a machine learning models in an immutable manner. The solution and underlying methodology enforce the use of a corporate model development standard to ensure Responsible AI practices are abided by organizations.
• “Providing Insights About Dynamic Machine Learning Models” – Encompassing the use of visual indicators of features and training data, along with global or local explanations, to provide a broader summarization of a machine learning models behavior.
• “Managing Missing Values in Datasets For Machine Learning Models” – Addressing missing value data, imputing values, and encoding reasons for why data may be missing. This invention is for use in the development of analytic models in environments where data quality is suspect.
• “Facial Recognition for User Authentication” – Covering the use of facial liveness recognition for the purpose of providing secure access to electronic content or systems. The facial features of the user are continually scanned to detect facial movements indicative of the user’s liveness, as opposed to static representations.
• “Deployment of Self-Contained Decision Logic” – Encompassing the generation of executable code associated with the decision logic and makes it amenable to storage in a repository.
• “Devices And Methods for Efficient Execution of Rules Using Pre-Compiled Directed Acyclic Graphs” – Pertaining to making optimal transformations of business rules into executable code for rapid execution.
• “Systems and Methods for Scalable, Adaptive, Real Time Personalized Offers Generation” – Covering improvements to hyper-personalization offers by updating user profiles in real-time with each new transaction or event, generating an affinity score for each user based on the updated profile.
• “Density Based Confidence Measures of Neural Networks for Reliable Predictions” – Claiming innovations in assigning confidence estimates to predictions, thus allowing practitioners to better trust the model. This invention opens new applications in which knowing the certainty of the predictions is critically important to the implementation of responsible AI.
• “Efficient Value Lookup In A Set Of Scalar Intervals” – Encompassing improvements to sorting and comparing scalar intervals to determine overlaps and make decisions faster.
• “Entity Resolution Based on Character String Frequency Analysis” – Addressing the generation of similarity scores between one or more pairs of character strings based on degrees of commonality or rarity, generating a similarity score.
• “Advanced Learning System for Detection and Prevention of Money Laundering” – Covering automated detection of money laundering using hyper personalization of linked list behavior to known risky entities. This innovation is used to create money laundering threat scores to help detect and stop money laundering.

To date, FICO’s patent portfolio consists of 213 active patents, with an additional 80 patent applications filed and pending approval.

About FICO

FICO (NYSE: FICO) powers decisions that help people and businesses around the world prosper. Founded in 1956, the company is a pioneer in the use of predictive analytics and data science to improve operational decisions. FICO holds more than 200 US and foreign patents on technologies that increase profitability, customer satisfaction and growth for businesses in financial services, telecommunications, health care, retail, transportation and supply chain, and many other industries. Using FICO solutions, businesses in nearly 120 countries do everything from protecting 2.6 billion payment cards from fraud, to helping people get credit, to ensuring that millions of rental cars are in the right place at the right time.

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FICO is a registered trademark of Fair Isaac Corporation in the U.S. and other countries.

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