Turn Data into Revenue with Customer Insights, Artificial Intelligence, and Machine Learning
In the financial industry, artificial intelligence (AI) and machine learning (ML) have dominated technology discussions, strategies, and roadmaps.
AI can be defined as “the study of how to train the computers so that computers can do things which at present we associate with human minds.” There is a misconception that artificial intelligence is a system. Rather, AI is implemented into a system.
Machine Learning, an application of AI, is when a machine can learn by its own without being explicitly programmed. It provides the system with the ability to automatically learn and improve from experience.
Embracing these technologies is more of a top priority than ever before, with customer experience and revenue performance at stake. At the core of each is data.
At the 2019 Paris Fintech Forum, Carlos Torres Vila, executive chairman of Spanish BBVA Group, in a panel alongside Christine Lagarde, managing director of the International Monetary Fund, concluded that “data is where the value lies”. The opportunity to realize this value is at the fingertips of financial institutions. Turning data into revenue with customer insights comes from making sense of the data available. Artificial intelligence and machine learning play a key role in unlocking this opportunity.
Yet, according to the study “Artificial Intelligence in Banking”, less than 20% of financial institutions have implemented one or more AI solutions. Some of these leaders have already seen success. The Bank Administration Institute (BAI), a US non-profit organization advising financial institutions, shared some examples:
- Bank of America rolled out Erica, its virtual assistant, in 2018. The chatbot uses predictive analytics and cognitive messaging to provide 24/7 financial guidance to customers. Erica can help with balance information, simple transactions such as transferring money between accounts, view past transactions and schedule payments. Customers can also chat with Erica through voice or text message, similarly to Amazon’s Alexa.
- Wells Fargo piloted an AI-driven chatbot through Facebook Messenger as early as in 2017. It delivers live information to help customers make better financial decisions, from how much they spent on food the week before through account balances and payment due dates to the nearest ATM.
- The Royal Bank of Scotland (RBS) is using an automated lending process to approve commercial real estate loans up to $2.7 million in less than 45 minutes. This process normally takes several days. The 2017 AI-driven launch is part of the bank’s broader digital and innovation agenda. RBS has also adopted a cognitive chatbot, powered by IBM Watson Conversation, to answer customer questions.
AI promises to progress quickly in the financial industry. The landscape and capabilities will change dramatically in the next five years. The longer banks wait to implement AI into their processes, the steeper the learning curve will be to catch up and compete. Bank Administration Institute (BAI) suggests three ways to leverage the power of AI:
- Make the most of customer data. Banks have the data and their customers, often millennials and Gen Xers, are willing to share more personal information in exchange for a more customized, streamlined service.
- Use AI savings to fund AI customer experience initiatives. Banks can make room for a larger innovation budget in part through reduced costs for employees to execute routine, repetitive tasks in the back office, thanks to AI.
- Form a special team to drive AI programs. Wells Fargo created its AI Enterprise Solutions Team in 2017. The cross-functional unit, which sits under the umbrella of its Payments, Virtual Solutions and Innovation Group, works to create more connectivity among the bank’s staff with technological experts, who in turn can help create a seamless, rewarding experience for customers.
Consumers are no strangers to artificial intelligence thanks to tech and e-commerce giants such a Google, Amazon, Facebook and Apple. AI implementations are setting the standard across industries and consumers are embracing these technologies. Automated assistants, such as Google Home, Apple’s Siri and Amazon’s Alexa, are emerging as new channels high time banks which clients are coming to expect their financial institution to understand and be accessible on.
How is your financial institution turning data into revenue with customer insights? We’d love to hear how you are integrating artificial intelligence and machine learning to achieve this success. Share with us at email@example.com.