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December 7, 2018
Ernie Buday, FIS | Vice President, Product Strategy
Artificial Intelligence (AI) already is transforming banking for many of the country’s largest financial services organizations. Fortunately for smaller organizations, AI isn’t out of reach.With the right focus, community banks and credit unions can access AI and compete with their larger competitors…bot-to-bot.
AI presents opportunities for financial services organizations of all sizes to reduce costs, mitigate risks, increase revenue and improve customer service. But because this often requires a specialized understanding of data and how to leverage it, many smaller organizations aren’t prioritizing it…yet.
For many, the issue is a lack of resources and skill inside the business. After all, for AI to be effective, it needs high-quality data that is actionable. For many community banks and credit unions, data science is too new to already have employees who understand it. Acquiring these skills is another issue.
So what steps can smaller, resource-restricted banks and credit unions do to make a meaningful difference?
First, drill down on the opportunities or problems you are looking to address and determine how AI can help solve them. Whatever the target use cases – fraud and AML, small-business lending decisions, custom offers triggered by customer life-events – the fundamental fuel is good data.
Then seek an experienced partner like FIS, who helps financial services organizations of all sizes launch AI solutions built on large consortium data and science skillsets. This approach brings economies of scale, readymade interfaces, wider ecosystems at affordable cost, with faster time-to-market and reduced risk.
AI should solve real business opportunities or problems. Following are a few use cases:
When deciding where to apply AI, financial services organizations will encounter some key control and governance considerations when plugging into their respective operating environments. How much authority should AI have? What about regulators? And what if things don’t go as planned? For AI technologies to succeed, they should be audited to explain why their algorithm reached a certain decision.
AI software is only as smart as the data used to train it, therefore, a human review must be conducted to oversee the predictions of the machine to ensure fairness and protection against bias decisions. Don’t forget to think through “off-ramps” that steer customers to human backups when needed. Give AI systems the opportunity to learn from the outcomes of human interactions.
FIS | Vice President, Product Strategy
Ernie drives growth initiatives that accelerate adoption and revenue for the FIS’ Emerging Commerce solutions, including Loyalty and Prepaid. With over 20 years of financial technology experience, Ernie joins FIS from Worldpay in Atlanta where he led brand and product marketing for their US business. Focused on optimizing their digital strategy, he launched the company’s new omni-channel payments product and new merchant onboarding experience.
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