For Industries: 
Banking
Overview

Background: The National Consumer Assistance Plan (NCAP) is a comprehensive series of initiatives intended to evaluate the accuracy of credit reports, the process of dealing with credit information and consumer transparency. As part of NCAP, the consumer reporting agencies (CRAs) — Experian®, Equifax® and TransUnion® — are changing the data standards and service level requirements of the public record data they maintain.

Overview

Businesses across many industries spend millions of dollars employing advanced analytics to manage and improve their supply chains. Organizations look to analytics to help with sourcing raw materials more efficiently, improving manufacturing productivity, optimizing inventory, minimizing distribution cost and other related objectives. But the results can be less than satisfactory. It often takes too long to source the data, build the models and deliver the analyticsbased solutions to the multitude of decision-makers in an organization. Sometimes key steps in the process are omitted completely. In other words, the solution for improving the supply chain, i.e., advanced analytics, suffers from the same problems that it aims to solve.

For Industries: 
Banking
Overview

Are you prepared for IFRS 9? This major accounting standard change has had the attention of major banks for several years but is an equally high priority for auto finance providers as well.

For Industries: 
Banking
Overview

Some of the biggest challenges facing businesses worldwide relate to security. Increasingly, the domains of fraud protection, cybersecurity and regulatory compliance are merging within institutions, which are taking a more holistic view of financial crime. This is critical, as these areas share a need for rapid action based on real-time threat assessment. With this in mind, we asked four of FICO’s experts in this area to provide their predictions for the year ahead. 

Overview

The increasing availability of data is changing organizations in every industry. As data volumes explode, and as this data both diversifies and arrives at ever-faster rates, organizations need to adopt advanced analytics to drive better outcomes. Success in this environment requires the development of several categories of analytics, especially prescriptive analytics, and their application to a variety of problem domains.

Overview

Unexpected failure or performance erosion of production equipment can significantly impact productivity, product quality and maintenance expenses within any manufacturing organization. It’s also difficult to get operations ‘back on track’ after these failures occur. The good news is that, via the Internet of Things, intelligent use of sensor data, machine learning and optimization can help companies take a proactive approach to predicting failures and re-optimizing processes around them. 

This Q&A with Dr. Michael Watson, Partner at Opex Analytics and Adjunct Professor at Northwestern University, discusses:

  • The evolution of sensors in manufacturing plants, and their increased use as costs decrease
  • How some manufacturers are getting more creative with sensor data – evolving from predictive to prescriptive (optimization) analytics to drive better actions
  • How an optimization-powered approach can help you not only better predict failure, but also determine what to fix today vs. later (or not at all)
For Industries: 
Manufacturing
Overview

Treat data and information as you would any critical business asset: measure, document and manage essential attributes such as value, risk and cost.

Manufacturers depend on information and analytics to help them deal with the complexity caused by global operations, value chains and market. Most recognize that there is tremendous opportunity to use, analyze and apply information all across the business. However, they need to do a better job capitalizing on the information that is and will become available to them and to embed intelligence in how they manage their operations and deliver products and services. 

Overview

With the term “Big Data” now commonplace, there’s no mistaking that today’s volume, variety and velocity of data challenges organizations that follow splintered approaches to data connection, ingestion, processing and analysis. Too many IT departments are still falling short of transcending legacy approaches that limit the value they derive from data. Typically, those organizations find themselves caught in differentiating data treatment by type — particularly between batch and streaming data — and consequently supporting disparate IT infrastructures. That seriously misaligns those organizations with contemporary data realities, and it short-circuits opportunity. 

For Industries: 
Technology
Overview

A proliferation of data and the invention of new technologies are combining to change the very way people make decisions. These forces are also changing the very nature of the decisions we make.

For Industries: 
Banking
Overview

Credit markets have seen many changes in recent years, including tremendous innovation, the rise of marketplace lenders around the globe and new credit products from major technology players such as Amazon. That innovation is driving existing lenders to rethink their infrastructure and processes to become more nimble while regulators begin focusing on the new entrants (e.g., The US Treasury Department recently issued a whitepaper on potential disparate impact and fair lending for marketplace lenders). These changes require traditional firms to be agile and adapt quickly to new innovation, new players and new regulation, all the while improving the customer experience. 

Tim Van Tassel, Vice President and General Manager of FICO’s Credit Risk practice, weighs in on the subject of how marketplace lending is changing the credit landscape, and what that means for both new marketplace lenders and traditional credit-grantors. 

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