Data & Analytics

Alternative financial services data gives lenders access to powerful and predictive supplemental credit data that better detect risk and benefits consumers.

Given the option between offshore and onshore data science resources, how do you decide? Let’s discuss a few things to consider.

An analytics environment can have enterprise-wide impact. Instant access to customer data, actionable analytics and intelligence tools drive the most value.

Issues to evaluate during data sample selection and design for model development and an overview of traditional data sampling techniques.

There's a lot of talk about alternative credit data today, but not all of it is factual. Dispel the myths and learn what the truth about alternative data.

Gavin Harding, Senior Business Consultant, continues in this Q&A with insight that spans across all lenders and their use of alternative data.

In banking, as in baseball, data and analytics are key to making informed, data-driven decisions for your team and your business.

It’s not enough to just dig into the sales number of electric vehicles — It’s important to understand the consumers most interested.

Any analytical environment is only as good as the data you put into it. Check these four key features when choosing the right one for your organization.

Electric vehicles are here to stay – and will likely gain market share as costs reduce, travel ranges increase and charging infrastructure grows.

You want to use big data, but how do you make your analytics truly actionable to stay ahead of the competition? Using an analytical sandbox is the answer.

There are a lot of people talking about big data who are not fully leveraging the value of their data. How do you use data to innovate and stay competitive?

Demand for data scientists is off the charts, but nationally there is a data science skills shortage. Many companies are filling this gap by outsourcing.

Experian recently interviewed Philip Bohi, Vice President for Compliance Education of AFSA, to learn more about his perspective on alternative data.

A summary of common resampling techniques that can be used to create a robust model development and validation sample.