Artificial intelligence is increasingly immersed in the world we live in and banking is no stranger to this trend. The financial industry needs to implement this type of technology to remain competitive. The application of AI in banking apps and services allows you to increase revenue through greater personalization of your portfolio for customers, reduce costs through automation, limited margin of error, and better utilization of resources.
According to Business Insider, 80% of banks are aware of the benefits of AI. In addition, banks are projected to save $447 billion through the use of AI applications.
As new technologies are introduced, banks are continuously adopting the latest innovations to redefine the interaction they have with users. Disruptive AI technologies can dramatically improve banks’ ability to achieve four key outcomes: increased profits, personalization at scale, distinctive omnichannel experiences, and rapid innovation cycles.
Applications of AI in financial services
Financial solutions businesses can use artificial intelligence in their different digital channels. Let’s look at three of the many applications that occur through this disruptive technology.
Chatbots: By integrating them into apps, banks can ensure that they are available to their customers 24/7. In addition, by understanding their behavior, chatbots can offer personalized attention and recommend appropriate financial services and products.
Cybersecurity and fraud detection: AI can significantly improve the effectiveness of cybersecurity systems by leveraging past threat data and learning patterns and indicators that may seem unrelated to predict and prevent attacks, as well as identify fraudulent activity.
Data analysis: FIs record millions of transactions daily. Given this scenario, AI-based solutions can aid in efficient data collection and analysis. This, in turn, improves the overall user experience.
How Banks Can Transform to Adopt AI
According to research by McKinsey & Company, there are four interdependent keys that, when working as one, allow a bank to provide distinctive omnichannel experiences. They also support customization at scale and drive rapid innovation cycles critical to remaining competitive.
- Reimagine the customer experience: Customers are increasingly expecting their digital journeys. You need to know their context and needs no matter where they interact with the bank. In order for the business to be ubiquitous and solve emerging needs while delivering intuitive omnichannel experiences, you’ll need to redesign customer engagement and make the necessary changes. This means integrating personalization decisions (what and when to offer, through which channel) into core journeys and designing value propositions that go beyond the core banking product. This should include AI that automates decisions and activities.
- Decision-making: Delivering personalized messages and solutions to millions of users in real-time requires the bank to develop an AI-powered decision-making layer at scale. To establish it, you should try to develop specific use cases and point solutions to an enterprise-wide roadmap through the implementation of advanced analytics models. The development process must be repeatable and therefore able to deliver solutions effectively and on time. In addition to strong collaboration between teams from different areas, this requires robust tools for model development, efficient processes (e.g., reusing code between projects), and the dissemination of knowledge across teams.
- Strengthen technology and data infrastructure: Implementing capabilities requires a scalable, resilient, and adaptable set of core technology components. For a core backbone to be solid, it must have the necessary investments for its modernization, which contributes to increasing its effectiveness at the levels of decision-making and user engagement.
- Transition to an operating model: The AI bank of the future will need an operating model capable of being agile to generate value. Through the integration of business and technology into jointly owned platforms led by cross-functional teams, FIs can increase velocity and improve alignment of goals and priorities across the enterprise.
The journey to becoming an AI-pioneering bank involves transformational capabilities in the four layers of a core banking seen in the previous point.
How Topaz Can Help
Artificial intelligence is built into many of our solutions. One of them is Online Fraud Detection, a market leader that helps businesses and their users prevent fraud in an innovative and efficient way in transactional channels, digital services and e-commerce. Thanks to the connected and collaborative intelligence ecosystem, we use transactional, biometric, and risk-based authentication machine learning, enabling real-time transaction analysis that prevents fraud before it occurs.
Learn about our digital, anti-fraud and cybersecurity solutions that alleviate the operability of your business by automating complex processes, ensuring efficiency, business competitiveness and increasing customer satisfaction.