Artificial intelligence (AI) is taking hold in digital banking. Financial institutions are using AI for real-world, value-add applications, from automating digital experiences to providing proactive insights. And they're prioritizing data strategies and development of dynamic experiences to drive deeper engagement and help them compete in a changing market
AI in financial services takes advantage of underlying technologies now readily available in digital banking platforms. That infrastructure is key to providing the financial insights and self-service tools users need to effectively manage and move money. And the same techniques can extend to use cases across industries.
The Importance of Accessing Data Dynamically
Users pose financial questions in different ways, but AI needs to understand those questions whatever the form or context. Then, to respond with the right information, the AI engine needs access to the appropriate underlying data. Finally, the answer must be formatted for the channel in use, including online and mobile channels.
Traditionally, financial data has been presented in a static view, which forces users to interact with information in a one-dimensional way. That has varying levels of success, depending on the different financial challenges and questions each person may have.
The static presentation of data continues to be the norm. But as technology evolves, users will expect to be able to ask any question about their financial health and receive relevant information through intelligent engagement tools. Building that sort of platform allows financial institutions to solve more problems digitally and without human interaction, which helps alleviate extended call wait times and other frustrations.
That requires bringing together separate platforms.
People pose financial questions in different ways, but AI needs to understand those questions whatever the form or context.
Building a Conversational Experience
The first step for financial institutions is leveraging best-in-class conversational natural language understanding and natural language processing (NLU/NLP) technology trained in personal finances. Developing AI tools that understand financial context requires an extensive amount of training, an understanding of context and appropriate response guidelines.
Most importantly, training humanizes the experience, whether through the interaction model, which normalizes conversation, or by the creation of a dynamic experience that allows users to ask relevant questions. That's crucial because when it comes to finances, consumers need personalized financial advice that addresses their specific situations.
AI applications with deep knowledge of financial topics can provide the right data to fulfill requests to lock a credit card or dispute a transaction, for example. That AI application will know how to respond when consumers ask if they can afford to spend extra money.
Deep integration into a financial institution's ecosystem provides categorized, aggregated data and can facilitate transactions, including payments and account opening. That requires integration into online and mobile channels. An experience that employs visualizations, insights and nudges will likely become a user's go-to method for interacting with a financial institution. Building native, deep integrations into digital banking engages users and helps provide a reliable one-stop shop and true source of data.
A fully integrated assistant brings together the critical components – underlying AI, enriched data and visual components – as an out of-the-box SaaS product. That allows for a dynamic solution that can be leveraged across channels without the heavy logistics required to design a dynamic conversational experience.
The Next Frontier of AI
Predictive assistants that are deeply integrated into financial services platforms, across every digital channel, help solve for more complex problems. Predictive technology will know when a consumer makes a payment and how much he or she typically spends each month. It will provide an alert, if necessary, to slow down spending or perhaps encourage investing extra money. Based on behavioral insights that leverage key data, those types of nudges and alerts proactively encourage financial health.
The next generation of banking is taking hold. Digitizing financial capabilities allows financial institutions to help users with their personal financial needs, and digital assistants will lead the charge.