How financial institutions can get the most out of artificial intelligence
- Artificial intelligence is a complex technology with a variety of applications. For best results, financial institutions should implement AI with a specific need, plan, and strategy in mind.
- AI can help financial institutions move beyond a transactional, generalized digital banking experience, and deliver branch-like banking on digital channels at scale.
Mark Ryan, Co-Founder and Chief Analytics Officer, Finalytics.ai
Financial institutions face a unique dilemma whereby large volumes of data are instrumental to their effectiveness as a business, but without the proper tools, the quantity and complexity of this information can overwhelm staff and be difficult to apply in beneficial ways.
When used properly, AI can analyze large amounts of data with speed, accuracy, and scale to produce valuable and actionable insights about a financial institution’s current and prospective customers. Access to such insights provides organizations with a decisive advantage against the rest of the field.
However, it is important not to use new technology just because it’s trendy. Financial institutions may see their competitors try AI and then react tactically rather than plan strategically. This “shiny object” adoption cycle happens with many new, innovative technologies and often delays the application of a technology’s full potential across an industry.
So, how can financial institutions determine what the right AI technology is for them?
There are several areas to address when considering what AI technology is best for a specific financial institution. To start, basic questions must be asked, such as what is the financial institution trying to accomplish by acquiring AI? Is the goal to create internal efficiencies that will free up time for bankers to spend with clients, or to implement a user-friendly tool that will speed up customer service requests, e.g. a chatbot? According to Finalytics.ai internal research, organizations that define goals and ask the right questions see growth rates at 15-25% year-over-year, more than double the ones that don’t.
Utilizing return on investment models created to consider the full scope of the technology’s impact can also help financial institutions determine where they should or shouldn’t implement AI. However, these models shouldn’t be focused just on sales, profit, or income, but also on customer satisfaction. For example, while financial institutions have flocked to chatbots or targeted email marketing due to their lower costs and immediate short-term results, these methods only truly impact 5-10% of customers, according to Finalytics.ai data.
Though perhaps more expensive, an AI model that can analyze large volumes of data quickly, accurately and in real time can add hundreds of millions annually to an institution’s top line. By analyzing insights to predict the needs of consumers at a specific moment in time, this type of AI can help financial institutions deliver segment-of-one digital experiences at scale. This approach brings a relational digital banking experience, rather than a purely transactional one, benefiting all customers, increasing member satisfaction, boosting retention rates, and introducing new opportunities for cross-sale.
Once the goals are set, a strategy can be built for the use of AI. Financial institutions should set an AI budget and undergo a market evaluation of AI vendors to determine what provider best suits their needs, goals, and culture. A good technology partner should be able to support a financial institution throughout every stage of the process, from testing to implementation and the day-to-day operation of the system, while also helping the organization save costs by eliminating the need to invest in data warehouses and an in-house IT department.
With margins constantly under pressure and modern digital capabilities demanded by consumers, AI can help financial institutions deliver what their customers need and want, at a specific moment in time, faster and more precisely than a human or any other technology currently available can. AI can also help organizations save costs; in fact, according to Insider Intelligence, the potential savings banks will get from AI applications this year is an estimated $447 billion. In addition, AI can help eliminate bias in banking, enabling financial institutions to better serve the underbanked, and also support organizations in determining risks and being more prepared to combat financial crime.
AI is everywhere right now, but to be effective, it should be applied in areas where it can have the most impact. By gauging customers’ needs, putting together a plan, setting a budget and analyzing the AI vendor market, financial institutions are more likely to invest in the right technology for them – one that will render the best results, save costs, and increase consumer satisfaction, truly giving these organizations a competitive advantage in the market.
Mark Ryan is co-founder and Chief Analytics Officer at Finalytics.ai. Throughout his career, Mark has worked with some of the largest community financial institutions in the U.S., helping them through digital transformation, design, development, and data analytics.