The Emerging World of Data Science

Written by Di Princell

April 20, 2021

If we can choose, we can change. If we can’t change, then choice means nothing.
~The Rhythm of War

Defining data science is challenging enough, so let’s cut to the chase and focus on the goal – show me the money! Utilizing data science in business is the future, the now, and the forevermore. It’s an insightful and complex process that merges statistics with businesses acumen to make smarter decisions so that profitable opportunities can be expanded, examined, measured, and implemented. As technology advances, so does the scope and storage of data, increasing prospects for more accurate and relevant customization of products/services.

Data is the new black gold . . . so, understanding how to manipulate, program, and analyze the numbers and statistics that are unearthed is the constant challenge to increasing profits based on smart, calculated, and predictive insights. Key word – predictive – the data by itself is only half the formula; it’s what the scientists do with the data that makes it meaningful and valuable. Understanding the monetary value of information and how it operates within the business domain to generate and guide constant improvements is at the core of data science.

The old guard sitting in a meeting room, brainstorming what consumers will buy, and hoping to hit the nail on the head wasn’t the most reliable method of forecasting. Data science turns the tables as the ideal combination of the human brain and technology, aka augmented intelligence, resulting in a complex and precise customer profile. Computer gathered data, analyzed by expert minds armed with the right technology, takes a lot of the guess work out of product innovation while providing a profitable roadmap that predicts where and when to sell products.

RIBBIT, a Data Analytics company providing risk assessment products for lenders, FinTechs, retailers and banks, is an example of the applicability of data science. Powered by a team of data scientists, RIBBIT provides predictive analytics on non-credentialed and credentialed bank account insights to improve customer loan and payment performance. Drawing on data results using algorithms and statistics, RIBBIT’s risk formula, measuring thousands of consumer attributes, is proven superior to traditional, credit risk techniques. RIBBIT empowers financial decisioning with predictive insights on 99% of bank accounts, painting a heightened landscape of customer affordability. The revolutionary blueprint is a win-win for lenders and their customers.

Steven Thompson, RIBBIT’s Chief Data Scientist, explains “Data science at RIBBIT is a melding of decades of experience of analytical intuition and hard statistical insights. In a sense we are creating a recipe for deeper affordability and behavioral outcomes from better ingredients – carefully curated bank account data. The benefits are obvious – more complete and predictive credentialed and non-credentialed bank account products.”

Stay tuned . . .

 

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