Uses of Artificial Intelligence in Banking

Artificial intelligence has become a key disruptor in various industries, including banking. The introduction of AI in the banking sector has increased productivity, enhanced security, and helped make better decisions based on crucial information.
Artificial Intelligence in Banking
The technological penetration in this sector is restructuring workplace skills. Therefore, professionals consistently upgrading their skills have the advantage of better career prospects in the banking sector.

The banking industry continuously competes to reduce its liabilities and increase its asset size. A fast-track strategy is required to achieve this goal systematically and cost-effectively. Artificial intelligence in banking is a vital component that helps to achieve optimization goals and deliver dependable banking services.

It has surged the interest of working professionals in AI technology and its deployment in the banking sector. An AI engineer's average salary in India is Rs.10 lakhs annually. The evolving technology and its extraordinary impact on the banking sector have led to a high demand for skilled AI professionals.

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Applications of AI in Banking

The banking industry deploys AI technology to streamline the efficiency of operations and to reach new heights in customer relationship management. The major applications of AI and machine learning in the banking sector are elaborated on in the following list.

1. Enhancing Consumer Experience

Banks maintain vast data about their customers' information and preferences. AI technology processes and understands these large chunks of variable data better than humans. With these insights, banks can come up with valuable information about every customer and create personalized experiences matching their requirements. It helps to strengthen the customer base by increasing satisfaction rates and trust factor among the users. A banking institution providing improved customer support adds value to the brand and increases customer retention rates.

The Interactive Voice Response System (IVRS) is an example of this AI-led system. It understands customers’ queries and guides them in the right direction by routing the calls to the correct department and assisting them with other banking-related issues in real-time.

2. Upgrading Crucial Data Security

AI can dive deep into the consumers' data from the past. Combining this ability with machine learning, banks can get data-driven predictions that can help them identify fraud and counter cases of capital laundering. In addition, it helps to upgrade the security and recommend changes by identifying loopholes in the existing system.

Machines with AI technology can crunch vast amounts of data by applying a combination of algorithms, with minimal chances of making mistakes. In addition to this, banks can also detect deceptive emails and log reports, data breach patterns, etc., to provide better security to the existing methods. As a result, there is an increasing benefit to financial firms with an optimized data collection method and willingness to upgrade their AI algorithms constantly.

3. Examining Knowledge Database

AI is a boon for extracting powerful insights from the massive treasury of user data. Integrating this database with AI technology provides a more meticulous decision-making process and optimizes strategic and business plan models. It is equivalent to the cognitive thinking capabilities of a human.

4. Controlling Risks

AI helps to mitigate potential risks by understanding user patterns, studying failed business strategies, and eliminating maximum errors, leading to high growth potential. Since banks already contain a vast amount of data, AI-powered systems are necessary to spot the relevant threats and potential risks, including human error, encrypt data to authenticate transactions, and eliminate the chances of fraudulent attempts.

5. Reduction in Operational Costs

Although the banking industry operates digitally, certain operational aspects are riddled with human processes and involve intense paperwork. To overcome this, banks are deploying AI-based RPA software that imitates rule-based digital tasks performed by humans.

It eliminates much of the time-intensive and error-prone work involved in gathering and putting together customer data from various sources. In addition, these RPA bots can handle a wide range of banking workflows that previously required considerable human resources.

6. Improved Loan and Credit Decision-Making Process

This relatively new aspect of AI is being tested and applied in the banking sector. For example, they have developed AI-based systems that detect the behavioral patterns of customers who are likely to default or might be a good credit customer based on their credit history.

7. Wealth Supervision

Few banking institutions are delving deeper into the world of artificial intelligence in banking and including machine learning aspects to manage the wealth of their consumers. They deploy intelligent systems to look for untapped investment opportunities and help make investment decisions. With the help of personalized chatbots and customer-specific models, Robo-advisors are available whenever the customer needs assistance with their portfolio management.

8. Realistic Interactive Interfaces

AI-enabled chatbots identify the context and emotions in the text chat and respond appropriately using the right choice of words. It saves time and improves the efficiency of the work systems and resources. These AI-led machines provide completely new digitized and personalized interactive experiences to banking customers.


With the increasing use of Artificial intelligence in the banking sector, there is a high demand for a skilled AI workforce. Proficient engineers from fields like machine learning, big data, and artificial intelligence are required to provide credibility and bring efficiency to the workflow systems of the banking sector.

The banking industry is adapting to the digital revolution to increase the bottom line. These emerging technologies have vast application areas, from tightening data security to reducing operational overheads. The introduction of artificial intelligence has a lot of benefits for the banking and finance sector. To adapt to these changes, leaders in the banking sector must equip themselves with the necessary skills to reap the maximum benefits of AI technology.