Merchant Boost | Compliance Aspects for AI & ML: Part 2
Merchant Boost is the live data solution provider equipping financial service companies with solutions that fill the gap between historical, real-time and live data information, to improve marketing, underwriting, and collections. We are transforming fintech with innovative payment instrument data and solutions, increasing credit access to the financially underserved, and reducing processing fees for borrowers and creditors.
OLA, underwriting, AI, ML
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Compliance Aspects for AI & ML: Part 2

Compliance Aspects for AI & ML: Part 2

By Jesse Berger

We had a great session presenting about artificial intelligence and machine learning at the OLA conference last week. It was a great group of people and a great organization discussing relevant topics. Here’s a snippet of our presentation on artificial intelligence and machine learning.

Artificial intelligence and machine learning is not new. The concept is actually over one hundred years old. It’s recent resurgence and gain in popularity is being promoted through many use cases including marketing, servicing, support, as well as risk and credit decisions. However, as fancy as artificial intelligence and machine learning sounds, it’s really just math.

But what kind of math? It’s definitely more sophisticated math; math that is able to more easily handle large and diverse sets of data. More traditional predictive models incorporate a handful or maybe dozens of data sets to base their decisions. With more sophisticated math we can leverage data from dozens, hundreds, and even thousands of data sets.

The real question and challenge becomes managing the use of this technology. Leveraging thousands of data sets is great, but it presents its own set of challenges. Our next blog post will discuss the most relevant challenges using artificial intelligence and machine learning.