What’s the Real Promise of Artificial Intelligence (AI)?
January 12, 2018
In our blog of December 7, 2017, we asked the question, “How long do you believe it will be before AI will impact your business model and strategy?” With options of less than 2 years, 2-5 years, 5-10 years, and greater than 10 years, the responses were heavily weighted toward the shorter end of around 2 years. Also of interest were the comments, which touched on a range of topics, from the number of jobs that will be lost, to how far down the road it will be before we see artificial intelligence (AI) taking over high-level tasks.
Some made the point that AI is already here, and we interact with it every day in the form of Apple’s Siri and Google Assistant. Along those same lines, a credit union recently announced that its members will be the first to have the ability to converse with Alexa, Amazon’s voice-activated virtual assistant, to conduct their financial transactions (Source: Alexa Becomes Enrichment FCU Members’ New Banking Buddy).
The reality is that AI is a broad term encompassing natural language processing (like Siri), the ability to see patterns and relationships in data and derive insights, and far beyond. In fact, financial institutions are already using AI for fraud detection, investment robo-advisors, help with regulatory requirements, and more. It holds great potential for lowering expenses, improving the member experience, and helping to create deeper “relationships” as the definition of relationships evolves in the digital world.
To get a better feel for what might be next, here are a few examples of what some large financial institutions have been up to recently in the AI arena:
COIN – In June of 2017, JP Morgan Chase introduced COIN, short for Contract Intelligence. Using machine learning technology, COIN has exponentially reduced the time it takes to review the 12,000 commercial-loan agreements the bank processes each year and resulted in fewer mistakes.
Chatbots – Also called virtual assistants, chatbots are designed to use artificial intelligence to enable customers to interact via natural language (voice or text). Bank of America’s erica is one example. Erica will be incorporated into the mobile app, allowing customers to conduct routine transactions as well as providing financial guidance in the form of smart recommendations.
RPA Bots – Robotic Process Automation (RPA) bots are software applications that utilize artificial intelligence, and are programmed to automate tasks that are typically performed by staff but are repetitive in nature. RPA technology mimics a human worker, logging into existing applications, entering data, completing tasks, and logging out. It is designed to eliminate the need to reprogram underlying systems for speedy implementation. Bank of NY Mellon Corporation has been using this technology to improve efficiency and reduce costs (Source: BNY Mellon’s Automation Efforts Draw Industry Accolades).
Artificial intelligence can clearly improve efficiencies, but holds real promise in making it possible to know members better. It can process vast amounts of data from multiple sources, and make connections with the end goal of better understanding members. There’s a good chance that back when your credit union was founded, staff knew every member personally. Those days are gone for most, but AI could make it possible to “know” members like that again.
For many credit unions, the member relationship is part of the differentiator that drives their business models. Having deep, individual knowledge of members available to the front line and in marketing could propel relationship-building to new levels.
For now, just like other developing technologies, it’s best to keep artificial intelligence on your radar screen. Spend some time imagining how various applications of AI might change your credit union, and continue to broaden your thinking on what it could mean for your membership going forward.
