In this webinar, Micronotes CEO Devon Kinkead and the company’s Stanford-educated Data Scientist, Margreth Mpossi, discuss how bank marketing needs to change to take advantage of innovations such as artificial intelligence and machine learning.
When you work for an artificial intelligence software company that uses machine learning to help financial institutions to engage more effectively with online banking users, you tend to notice things related to your work. One day, while coming around the corner of the building I work in, I happened to see a sign in the window of People’s United Bank advertising attractive CD interest rates. It got me thinking.
USALLIANCE has used Micronotes' AI-driven marketing automation platform to conduct more than 200,000 conversations with its digital user community. As a result, USALLIANCE has been able to thrive during a time where branch visits to banks and credit unions have dwindled and online and mobile banking has exploded.
Recently, I received an inheritance and deposited it into the local bank I’ve done business with for a long time. And because my job is to sell Micronotes’ AI-driven marketing engagement solution to banks, I conducted a little experiment. I wanted to see how long it would take my bank to recognize this deposit, and engage me in a discussion about what I could do to maximize the funds. And I wanted to see what form the engagement would take.
FinTech innovations are changing the way banks and credit unions engage with their customers and members. But one of the most frustrating aspects of introducing new technologies is how long it can take to get them up and running. Watch this video and learn how Micronotes helps clients, including Pioneer Bank in New Mexico, go Live in One Day.
Here’s how Micronotes helps financial institutions retain customers at risk of attrition: We consume 6 months of historical data from the banking institution and build a list of customers who were lost during that time period. Those lost customers now become the predicted variable in our propensity scoring procedure.
The only thing worse than losing a profitable customer is knowing that you’re systematically losing profitable customers! As an AI-driven marketing technology company focused on deepening customer relationships, it was a natural evolution for Micronotes to begin offering our customers propensity risk scoring. In short, here’s why is matters and how it works.
Following our recent webinar Regulating AI in Banking (watch the replay), we received some thoughtful questions from a chartered financial analyst at a major commercial and investment bank about a new AI-enabled offering from Bank of America.
The smarter technology gets, the more independent it becomes.
On June 13, 2018, Micronotes CEO and founder Devon Kinkead and Mark Casady, a former member of the Financial Industry Regulatory Authority board of governors, now a general partner with Vestigo Ventures, discussed how the rapidly growing use of artificial intelligence and machine learning in banking—particularly in marketing applications—will affect compliance.
One of the major benefits of machine learning is its ability to understand complex systems. For example, you can look at hundreds of variables and ML systems can identify which of those provide the most information gain. ML won’t necessarily tell you the direction in which each variable is likely to move, but I would assert ML does help users understand complex systems.
As machines take on a larger role in creating and executing conversations with digital banking users, our clients need to know what report they can run to demonstrate their compliance with regulations. That’s something we’re going to build to help our clients manage future regulatory responsibilities as easily as they do today’s.
One of the issues that arises with fast-moving technologies, such as artificial intelligence and machine learning, in a highly regulated industry such as banking is the question of legal liability should something go wrong. Since regulation may not be in place beforehand, who is responsible if a perceived violation occurs? Do you blame the AI, do you blame the programmers? Who do you hold responsible?
As Artificial Intelligence and Machine Learning become more integral to the way financial institutions engage with digital users, the question of how to regulate AI in banking will become a hot topic. Micronotes will host a webinar on June 13 to examine this issue and discuss the implications for the industry.
Branch visits are down. Online banking continues to grow.
How can financial institutions prevent attrition and delinquency—and drive more business from existing users—when face-to-face interactions are rare and people are blind to banner ads?
Watch the webinar and learn about the results achieved by fast-learning financial institutions that are using AI-driven interview marketing to engage with users.