By Kevin Flanagan, Marketing Director, Micronotes
When someone asks me “What does Micronotes do?” I typically respond: “We’re a cloud software company that provides an artificially intelligent marketing automation solution for digital banking.”
Often, that elicits a response along the lines of “Oh, that sounds interesting.” But I know that many of those I’m talking to really don’t understand exactly what we do.
That’s because the concept of artificial intelligence is still pretty abstract for most people. Just about everyone has heard the term, but unless you work in the industry or regularly use an AI-based application, you probably aren’t clear on precisely what it means.
And when I say our solution leverages machine learning, the stares grow blanker.
So, I thought this would be a good opportunity to define AI and ML, and explain how they are related:
Artificial intelligence is the science of training a machine to perform human tasks.
Machine learning is a specific subset of AI that trains a machine how to learn. Machine learning models look for patterns in data and try to draw conclusions.
In a nutshell, ML is an application of AI. It’s not a separate technology category. Micronotes doesn’t use “AI and ML,” our platform leverages “artificial intelligence machine learning.”
The Micronotes platform uses machine learning to pinpoint high-propensity buyers so our clients can engage and offer the right product or service to each customer. Then it continuously improves buyer targeting by leveraging user response data to automatically reduce targeting errors. Essentially, the machine learns from those interactions, making each subsequent engagement with every customer that much more effective.
Micronotes Predict™, another key component of our platform, uses AI machine learning to provide actionable information to clients. It applies ML to predict which profitable customers are at risk of leaving their financial institution, enabling bankers to initiate account reviews and customer outreach. The platform also predicts which digital banking users are at risk of delinquency. This enables institutions to encourage the use of skip-a-payment products and schedule meetings with a banker to work through financial rough spots, before problems become loan losses.
So, there you have it. AI and machine learning are two sides of the same coin. And that coin pays off big for our fast-growing roster of clients.