Behavioral profiling approaches are extremely important in tackling fraud that happens when banks share financial data with third parties through application programming interfaces.
FICO’s capabilities in a broad range of anti-fraud functions resulted in consistently good scores across the defined categories for the Chartis enterprise fraud report.
Scott Zoldi discusses using advanced analytics to deliver highly personalized customer experiences and how to "operationalize" those analytics.
Dynamic pricing, a practice started by American Airlines in the 1980s, has now become a common marketing discipline for many corporations across industry sectors. From airlines, hotels, and entertainment events to perhaps the most well-known e-retailer, Amazon, these companies have been using dynamic pricing to improve profitability relative to rapid changes in supply and demand. Personalization: Using AI to deliver optimal customer experiences, in real-time As technologies for machine learning and artificial intelligence become more advanced and the dimensions of available data expands, dynamic pricing is going beyond its traditional inventory management function enabling companies to deliver optimal customer experiences, in real-time. In essence, pricing is becoming dependent on the ability to make offers which continuously adjust to changing consumer behavior and preferences while also responding to organizational inventory and profit requirements, as well as other external pricing influences. Today, enterprises are able to marry rich data sets with sophisticated pricing... [Read More]
The Chartis 2019 RiskTech100® report ranked FICO as one of the top 10 companies and FICO won awards in Innovation, AI, and Cyber Risk Quantification.
My presentation on “Transparency by Design: An Explainable AI Approach to Credit Risk Scoring” discusses our application of recent machine learning technologies to challenge the US FICO® Score.
I’m excited to welcome Network International to the Falcon Intelligence Network, the largest payments data source in the world, with data on more than 2.6 billion payment devices.
AI and machine learning have become popular concepts in payment integrity. But how can they help reduce your losses to health care fraud, waste and abuse?
Fraud analytics is an umbrella term covering a lot of technologies — let’s look at the two big categories.
Greetings from sunny (and humid) Miami! I had the pleasure of speaking on a panel at ABS East yesterday, entitled “Traditional vs Non-Traditional Underwriting, Does Machine Learning Teach Us Anything New?” The panel primarily focused on the opportunities and challenges associated with the use of Machine Learning (ML) in credit underwriting. I called out some highlights from FICO’s recent white paper on this subject. (We will dive into this further in future blogs so keep an eye out.) On the ‘opportunity’ side, I cited: The speed to powerful insights that ML offers, making it ideal for R&D efforts aimed at assessing new analytic challenges, and/or the potential of new data sources to add incremental lift. The great strides we’ve made at FICO as far as developing explainable artificial intelligence (AI)/ML and how that enables us to understand better than ever before what the key variables and risk patterns are that... [Read More]