Artificial intelligence (AI) in banking is not a new concept. The ability for machines to interact and learn to complete tasks previously done by humans goes back decades. The availability of data, open-source software, cloud computing, fast processing speeds, and the adoption of AI are contributing to a massive disruption of an industry that impacts virtually every consumer and business alike: banking. This has significant implications for financial institutions as new technical capabilities and contextual mobile services can help them stay relevant in the market.
It seems like every week there’s a technological breakthrough where a new task is completed using AI. From Siri to Amazon’s Alexa, the idea of having a personal assistant to help tackle everyday tasks is becoming more welcomed by users everywhere as consumer expectations are at an all-time high for personalization.
AI can be used in different ways in varying industries, ranging from less robust applications — such as Apple’s Siri — to more complex deep learning algorithms where a machine can function similarly to the human brain. Although “strong AI” is still in the distance, we are seeing technical capabilities advance with every passing week.
Artificial intelligence can be classified as a group of related technologies including natural language processing, machine learning, and expert systems. These functionalities can comprehend and behave similarly to how the human brain does, which have already transformed the way in which companies look at the overall customer experience.
The McKinsey Global Institute separates AI into five broad categories: computer vision, natural language, virtual assistants, robotic process automation, and advanced machine learning. The research institute predicts that by 2030, 70% of companies might have adopted at least one type of the AI technologies listed above. The banking industry has generous experience leveraging data insights, but for the most part, banks have yet to build scalable AI strategies focused on creating value for their customers.
While the banks do not operate round the clock; users want to complete their banking transactions round the clock. For them, the best bank is one which offers them the flexibility to perform their transactions 24×7. This demand is satisfied easily by mobile banking. But then comes another big question mark. While mobile banking can help the users complete banking transactions round the clock but what about the customer support. This is where the need for artificial intelligence in banking comes to the fore. With help of machine learning and predictive technologies, AI has been enhancing the efficiency of mobile banking and has been helping banks offer a better experience to their users.
Most banks, however, are just in the early stages of adopting AI technologies. According to a survey conducted by Narrative Science and the National Business Research Institute, 32% of financial services executives confirmed that they are already using AI technologies such as predictive analytics, recommendation engines, and voice recognition. Further signaling banks’ commitment to AI adoption, The Royal Bank of Canada recently added the Siri functionality to its iOS mobile app. Traditional retail banking providers are now finding themselves exploring AI technologies with more urgency to enhance the customer experience and remain relevant in today’s market.
The functionality of AI in mobile apps is becoming increasingly proactive, more personalized, and further refined overall. Just last month, Apple introduced Siri Shortcuts alongside the release of iOS 12. Siri now monitors user activity and suggests shortcuts based on normal in-app behaviours. Users can also customize this AI feature with unique voice commands and search queries to accomplish routine tasks. Banking institutions can enhance their mobile app with AI to send helpful reminders at times when customers have specified they need them the most. Simplifying user actions with voice technology will quickly become an indispensable part of user experience. Again, banks will have to offer simple, yet rich AI experiences to stay relevant with mobile customers.
J.D. Power cited that 47% of Canadian retail bank customers described themselves as "digital-centric," and 32% claimed to be "digital-only" customers. In Canada, mobile apps account for 85% of total mobile time and mobile-only audiences are growing. In only a year, 5% of Canadians have dropped desktop as a contender in their list of digital devices. In other words, financial institutions need to offer both an error-free mobile app experience, as well as personalized functionality to maintain customer satisfaction.
Varo Money is a company that is already reinventing how banking is done, entwining financial experiences into their users’ daily lives. Their app Varo, is an intelligent mobile banking app that improves consumers’ financial health by encouraging positive spending, savings, and borrowing habits. Intelligent banking apps can provide customers with personalized insights and recommendations wherever and whenever they want. Here are a few main ways in which AI can personalize the mobile banking experience:
Customer Support: Users are expecting the same level of personalized interactions and support that they are already accustomed to with services such as Amazon and Netflix. Gathering data from mobile devices and using analytics and machine learning on the back end can either provide users with hyper-relevant information or redirect them to the correct channel without having to deal with any other departments. This eliminates the pains of not being able to reach the appropriate customer service representative. Questions and concerns the user has can be answered immediately in real-time.
Advising: Users are more likely to share their personal information if they can receive custom advice, offers, and service based on this shared insight. Personalized communications and advice enabled by AI can be provided by robo-advisors, which are online wealth management services that generate automated, algorithm-based portfolio management advice without the assistance of a human representative.
Personal Planning: In addition to providing personalized advice using chatbots, AI can help customers plan for events in their future. AI-enabled mobile banking apps can provide specific strategies for users depending on the stage of life they’re entering. For example, if a user is purchasing a house for the first time, the app can generate a budget with forecasted expenses in the near future.
Automated Transactions: Users can automate transactions and bills according to the dates they’re due, eliminating the tedious task of manual entries.
Personalized Reminders: Reminding users of their current balance will help them stay within their budget. The reminders can also be set for pending bill payments and other upcoming expenses.
Mobile service companies such as Moven, lets users track their spending and boost their savings with automated, personalized recommendations via a specialized debit card linked with their mobile app. This kind of innovative thinking allows banks to push the boundaries of what they can offer their users to enhance the overall customer experience.
Transforming the customer experience in banking requires a degree of speed and accuracy that traditional banking can’t meet. The most forward-thinking financial institutions will be able to deliver value in real-time.
New innovations in data analytics empower financial institutions with systems that are so smart, they learn on the go, refining each algorithm and improving their results over time. However, adopting AI in your mobile strategy can be complicated. An Efma/Finacle study found:
While many barriers still exist and banks are slow to adopt, AI technologies are gaining momentum and have the potential to transform the industry in completely new ways.
Moving forward, financial institutions will have to align their AI and data analytics priorities the strategic vision of their mobile apps and implement those strategies in an agile cycle of testing and learning. Iterating continuously creates an environment where weaker AI test cases can fail quickly and high-performing applications can succeed sooner to deliver real-time value based on user feedback. Enhancing the customer experience with AI requires a detailed roadmap which identifies specific areas where AI will enrich the mobile app experience in line with overall business objectives.
AI in banking started with transactional analytics, risk management and fraud detection. Today, AI has revolutionized the way people bank on a daily basis. With mobile apps, banks can create consistent, high-quality touchpoints that connect their customers to solutions and products that simplify their financial life. The world is seeing a huge shift towards personalization as machine learning is being used to elevate transactions using millions of data points.
With the ability to fully understand their users’ behaviours, financial institutions are in the best position to apply AI technologies to their mobile strategy. Soon, all financial institutions will be leveraging the power of AI to deliver better experiences to their customers, all with lower costs, reduced risks, and increased revenues. Banking institutions need to pay attention to technological advancements within the AI landscape and plan ahead for what’s to come. What may be recognized as “amazing” today will be commonplace in the near future, which is why it’s important for banks to remain relevant in the mobile app market.