Applications of artificial intelligence in banking

Digital disruption is about redefining industries and changing the way businesses operate. Each sector is evaluating options and adopting ways to create value in a technology-driven world. The banking sector is seeing exceptional changes: above all, an increase in customer-centricity.

Tech-savvy customers who are exposed to sophisticated technologies in their daily lives, expect banks to offer seamless experiences. To meet these expectations, banks have expanded their industry landscape to retail, IT and telecoms to enable services such as mobile banking, e-banking and real-time money transfer.

These advances enable customers to access many banking services at any time, anywhere, and at their fingertips, which can be costly for the banking sector as well.

The integration of the banking and IT, telecom, and retail sectors transmitted critical information through cyberattacks and fraudulent virtual networks. These events not only affect the profitability of the banks, but also the banks’ confidence and relationship with customers.

Learn more about: What Can AI Do for Cyber Security?

The rise of online security threats in banking transactions has tightened government regulations. These terms can be used to monitor online financial transactions, but this impedes banks’ ability to sustain the digital transformation. Banks are unable to invest in technology because they need to maintain a capital adequacy ratio according to the guidelines of the international regulatory framework.

AI in the banking and finance industry

Banking on Artificial Intelligence:

The use of cognitive technology with Artificial Intelligence (AI) brings the benefit of digitization to banks and helps them to compete with Fintech players. In fact, according to research by the National Business Research Institute and Native Science 2, 32% of financial services firms are already using AI technologies such as predictive analytics and voice recognition.

AI in Banking: Top Use Cases of Artificial Intelligence in Banking Sector

Artificial intelligence is the future of banking (the importance of AI technology through industry) because it brings the power of sophisticated data analytics to deal with fraudulent transactions and improve compliance. The AI algorithm achieves anti-moneylending actions in a few seconds. If not, it can take hours and days.

AI allows banks to manage record-level high-speed data to get valuable insights from it. Features such as AI bots, digital payment advisors and biometric fraud detection systems lead to high-quality services for a wider customer base. All these increased revenues reduce costs and increase profits.

AI strengthens banks’ competitiveness by:

Improved Customer Experience: Based on past interactions, AI builds a better understanding of customers and their behavior. It enables banks to customize financial products and services by adding personalized features and intuitive interactions to provide meaningful customer engagement and establish strong relationships with their customers.

Predicting Future Results and Trends: AI helps banks to predict future outcomes and trends by analyzing past behaviors, with the power to predict future scenarios. This allows banks to detect frauds, identify the anti-moneylending model, and make customer recommendations. Moneylenders, through a series of actions, portray the source of their illicit money as legitimate.

With the power of machine learning and knowledge, AI can identify these hidden actions and save millions for banks. Similarly, AI can detect suspicious data patterns in enormous data to help manage fraud.

Furthermore, with its key recommendation engines, AI has previously studied how to predict the future behavior of data points, which helps banks to successfully market and sell.

Cognitive Process Automation: This feature enables the automation of a variety of information-intensive, expensive, and error-prone banking services, such as claim management.

It secures ROI, reduces costs, and ensures accurate and fast processing of services at every stage. Cognitive process automation automates a set of tasks that improve their previous iterations through consistent machine learning.

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