The AI Gap study, a PYMNTS and Brighterion collaboration, analyzes the survey response data of more than 200 financial executives from commercial banks, community banks and credit unions across the United States to provide a comprehensive overview of how financial institutions leverage AI and ML technology to optimize their businesses. To this end, we gathered more than 12,000 data points on financial institutions with assets ranging from $1 billion to more than $100 billion. This report details the results of our extensive research.
Key Findings from the study include:
- 70.5% Share of FIs that used data mining to fight fraud
- 4.1 Average number of algorithmic tools used by banks with more than $100 billion in assets
- 2.5% Share of FIs that used AI systems to enhance payments services
To download the study, fill out the form below:
February 14, 2019
Artificial intelligence (AI) and machine learning (ML) aren’t part of a far-off future. They are here, and they are at the bank. In fact, 100 percent of modern financial institutions (FIs) use some type of AI, ML or other learning system in varying forms and capacities. Today, nearly 70.5 percent use data mining, and nearly 60 […]
January 31, 2019
Artificial intelligence is making the leap from the imagination of sci-fi authors and computer scientists into consumer and corporate life. But even as the theories become reality, the general idea about AI — the lens through which the technology is viewed — often carries with it misconceptions and faulty assumptions that, over time, could impede […]
November 29, 2018
It’s said an ounce of prevention is worth a pound of cure, and the maxim can be applied to debt recovery efforts that average a dismal 20 percent. AI can help. Brighterion CEO Akli Adjaoute tells Karen Webster that true AI and smart agents form a 360 degree view of the customer that helps firms target which debts to collect at the first signs of consumer troubles.
November 21, 2018
It’s the age of algorithms, but not all algorithms are the same — and not all of them constitute true AI. A new PYMNTS report finds that FIs have adopted various forms of machine learning, but that AI’s deployment remains low. What will it take to get more AI involved in fraud prevention and other tasks? What are the long-term costs of settling for lower capability algorithmic technology? Get your algorithm on and have a read.
November 16, 2018
Brighterion CEO Akli Adjaoute says there’s only one measure of AI’s true potential: When the tech is adaptive enough to understand that John at 23 is the same John at 43, even though he has two kids, a wife and a house in the ‘burbs. That behavioral context, he tells Karen Webster, can help FIs stop fraud and personalize services — in much the same way that the corner shopkeeper could for his customers decades ago.
November 8, 2018
Let’s play buzzword bingo: “AI” is so abuzz right now, it’s positively ablaze. However, does its usage live up to the label that the financial services and payments industry has given it? Not really. In the new study, The AI Gap, PYMNTS interviews executives at 200 FIs and analyzes over 12,800 data points. The research discovers that only 5.5 percent of banks actually use what experts call “true AI” to reduce false-positives and fight AML, as well as optimize credit and other payments and banking products. Get all the details here.