AI In Banking: How Banks Use AI (Artificial Intelligence)

6 min readNov 1, 2023

Artificial intelligence (AI) has gained significant popularity within the financial services sector, leading to a transformation in how financial institutions function, engage with clients, and handle their daily transactions and monetary regulations. AI’s remarkable capacity to handle large volumes of data, recognize patterns, and render well-informed decisions has elevated it to a crucial tool for banks and financial establishments.

The financial and banking industry heavily relies on data, and AI excels at the in-depth analysis of extensive datasets, offering valuable insights to aid financial institutions in making more informed decisions. A multitude of potential applications for AI within banking and finance exist, encompassing the enhancement of customer experiences, streamlining back-office operations, the detection of fraudulent activities, risk management, and improvements in compliance procedures. Furthermore, AI enables these institutions to automate repetitive tasks, elevating precision, and accelerating processes, thereby leading to cost reductions and heightened operational efficiency. AI-driven chatbots and virtual assistants stand ready to provide round-the-clock customer support, reducing the need for human interaction.

In this blog, we’ll uncover how banks make use of AI to improve users’ banking experience. AI helps banks with processes like detecting fraud, making banking services more efficient, and even understanding what users might need before they ask. So, let’s step into the world of AI in banks and discover how these smart technologies are making a big difference in the banking and financial sector.

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Use-Cases of AI in Banking & Finance

Traditionally, banks used to take a lot of time to do a single task, such as depositing or withdrawing money, updating account details, etc. But with the help of AI, these tasks can be executed quickly and with utmost accuracy.

Let’s discuss various use cases of AI in the banking and finance sector, which are:

1. Process Automation

Robotic process automation (RPA) algorithms play a valuable role in the banking sector by handling monotonous and time-consuming tasks. This allows employees to focus on more challenging responsibilities requiring human intervention. Banks leverage these tools to expedite transactions and enhance the efficiency of various processes.

2. Data Collection & Analysis

Banks and financial institutions handle an immense volume of daily transactions, and the task of effectively managing and organizing this vast amount of data poses a significant challenge for their employees. However, this is where intelligent AI-powered solutions come into play. They excel in the collection and comprehensive understanding of this data, simplifying processes for all involved parties. These solutions not only benefit the institutions themselves but also elevate the overall customer experience. Furthermore, this advanced technology aids in the detection of fraudulent activities and plays a pivotal role in determining creditworthiness for loan applicants.

3. Cyber Security & Fraud

In today’s digital landscape, individuals routinely utilize digital tools for various financial activities, including bill payments, cash withdrawals, and accessing transaction histories. Consequently, banks face an increased need to intensify efforts in detecting fraudulent activities such as cheating or theft. This is precisely where AI’s role in the banking sector becomes pivotal.

AI and machine learning-driven software serve as valuable assets for banks in identifying potential fraud, pinpointing system vulnerabilities, bolstering online security, and reducing the likelihood of early-stage error in fraud detection.

One noteworthy AI solution, Deep Learning, significantly augments the bank’s fraud detection capabilities by an impressive 50%, while also fortifying the bank’s defenses against cyberattacks and fraudulent activities by a substantial 60%. The AI system further empowers the bank to autonomously make informed decisions, intervening only when human oversight is necessitated.

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4. Predictive Analytics

Artificial intelligence (AI) is highly beneficial in the banking sector due to its ability to swiftly process vast volumes of data, reducing the need for repetitive tasks. It frequently employs predictive analysis to comprehend and anticipate people’s behavior based on their communication patterns. In contrast to conventional technology, AI excels at uncovering intricate data patterns and correlations that were previously challenging to identify.

These identified patterns can reveal opportunities to boost sales, recommend associated products, or provide valuable insights into process efficiency, ultimately contributing to increased profitability.

5. Loan & Credit Decisions

Banks are increasingly turning to AI for more informed loan and credit decisions. Currently, many banks heavily rely on factors like credit history, credit scores, and background when assessing loan eligibility. However, it’s important to acknowledge that these credit reports often contain errors and may overlook genuine financial histories, leading to misclassifications of borrowers.

AI-driven loan and credit systems have the capability to evaluate one’s financial management and detect patterns, even in cases with limited credit history. These systems can also alert banks to behaviors that may increase the likelihood of a borrower defaulting on their loan. In essence, these technologies are reshaping how banks determine loan and credit recipients in the future.

6. Risk Management

At times, global events such as fluctuations in currency values or natural disasters can exert significant influence on banks and financial enterprises. During these uncertain periods, it becomes exceptionally critical for businesses to exercise heightened caution when making pivotal financial choices.

7. Tracking Market Trends

Banks harness the power of AI and Machine Learning to handle vast data volumes and forecast the most current market trends through comprehensive evaluations. With the assistance of this cutting-edge technology, they can delve deeper into market trends and provide exceptionally precise analyses of future market growth.

AI-driven tools within the banking sector can additionally offer insights into opportune moments for stock investments or signal potential market downturns. Thanks to their rapid data processing capabilities, these AI tools expedite decision-making processes for banks and offer valuable support to their customers engaged in trading.

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8. Customer Experience

Customers continually seek greater ease and convenience in their banking experiences. Take ATMs, for example — they garnered widespread popularity because they allowed people to conduct banking transactions like deposits and withdrawals, even outside regular banking hours.

Moreover, chatbots, which learn from user interactions, can offer personalized recommendations to enhance the overall customer experience. Additionally, banks can expedite the loan processing for users, eliminating the lengthy waiting periods experienced in the past.

In customer service, AI excels at accurately handling customer details and swiftly setting up accounts, ensuring a seamless and effortless banking experience for customers.

AMEX

American Express, often referred to as AMEX, employs a range of technologies, including AI, blockchain, cybersecurity, and more, to fortify the security of their application against fraudulent activities. These technologies are actively integrated into AMEX’s daily functions, spanning process automation, loan and credit assessments, cybersecurity measures, and fraud prevention. AI plays a pivotal role in streamlining and minimizing routine and labor-intensive human tasks.

Barclays

Barclays uses AI technology for their business in different forms, such as machine learning, biometrics, smart contracts, etc., which help to prevent and detect fraud. They use an effective fraud management system that helps to assist in spotting and preventing scams and other financial fraud.

Master Card

MasterCard uses AI to detect fraud and reduce the number of unauthorized transactions. Decision Intelligence, a fraud detection tool created by the firm, employs AI algorithms to examine transaction data and spot patterns of fraudulent behavior. Due to this, both Mastercard’s and its customers’ risk of fraud has decreased, and the payment industry’s overall security has improved.

JPMorgan Chase

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JPMorgan Chase has empowered their business using AI-enabled solutions. It has helped them to streamline their business processes, enhance customer experience, and provide better quality outputs. The best AI solutions can provide an early warning if your system is detected with any virus.

Capital One

Capital One uses artificial intelligence to speed up the loan underwriting process. CreditWise, an AI-powered tool created by the bank, analyzes consumer credit data using machine learning algorithms, automating credit checks and approvals. As a result, human credit checks take less time and money to complete, and the bank’s lending operations are now more effective.

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Conclusion

AI has emerged as a transformative force within the banking industry. It empowers financial institutions to efficiently analyze vast volumes of data, enhance customer experiences, automate repetitive tasks, and make more informed decisions, particularly in areas like loan approvals and fraud detection. AI-driven solutions not only improve operational efficiency but also contribute to a more secure and personalized banking environment. As technology continues to advance, banks that harness the potential of AI are better positioned to thrive in an increasingly data-driven and customer-centric financial landscape.