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Leverage AI in
Banking & Finance
Sector to drive
Growth

OVERVIEW

Artificial Intelligence (AI) technology has revolutionized systems and processes in various sectors, and banking is one of those industries. The adoption of AI in banking applications and processes has streamlined the customer experience and technological relevance.

AI technology reduces costs by improving the analysis to make better decisions and increases productivity by cutting manual tasks. They can spot fraudulent activities in a matter of seconds because of their intelligent algorithms.

A study conducted by the businessinsider reveals that the adoption of AI applications in the banking sector will estimate $447 billion in cost savings by 2023. These overwhelming benefits have encouraged 75% of bank respondents with over $100 million in assets to implement AI strategies by using chatbots in the front office and use it to detect anti-payment fraud transactions.
In this article, we will explore the key benefits of AI in the finance and banking sector and learn how this technology will reshape the banking industry in terms of customer experience and improving security.

How can AI be leveraged in the banking & finance sector to drive growth ?

Artificial Intelligence is now being widely used worldwide, and the banking sector has recognized its potential by integrating these technologies into their system to scale their product and services.

We have listed some of the major use cases of AI technology in the banking sector where the customer and the bank can reap its benefits. Let’s find out!

CUSTOMER EXPERIENCE

Customers often expect new features for a better experience and convenience. A study found that 80% of customers say they are most likely to associate with brands that offer a customized experience. AI tools and technology enable the banking sector to create personalized experiences for customers with advanced insights using data analytics.

With AI technology, customers can perform quick transactions, less time to record customer KYC information and avoid errors. Customers can avoid going through a manual process with AI automation when applying for loans or credit. And the application of AI-based software can fasten loan approval time for loan allotment. AI banking has also helped customers create accounts with no error, which further improves the customer experience.

Eliminate Cybersecurity and Fraud Activities

The banking sector deals in vast quantities of daily digital transactions where users deposit cheques, pay bills, withdraw money, transfer amounts, do online shopping, and more with online accounts. Thus, it has become important for banks to adopt AI technology to increase their cybersecurity and fraud detection efforts to avoid payment defaults.

AI can help banks detect fraudulent activities and provide solutions to eliminate any loopholes in the system. Several banks are using AI and machine learning to identify fraudulent activities to send alerts to the customers and the banks of any possible cyber attack.

Denmark’s largest bank, Danske Bank, implemented a fraud detection algorithm by replacing the old fraud detection system.
AI helped increase fraud detection capability by 50% and reduced the false positives by 60%. They also automated many crucial processes to streamline transactions and create a much more agile management system for the team and customers.

As the banking sector is more susceptible to cyberattacks, AI can help to manage cyber attacks more efficiently and tackle complex invasions.

StreamlineLoan and Credit Decisions

AI software applications have helped banks make smart, safer, and informed decisions in approving profitable loans and credit. Generally, banks verify the credit history, credit scores, and customer details to determine the creditworthiness. This process is often time-consuming and tedious, and also there are chances of misclassifying creditors by skipping checking their real-world transaction history.

AI-powered banks streamline the loan and credit process by looking into the behavior patterns of customers based on their credit history. Also, they identify any behavior that can lead to any defaults.

Chatbots

Chatbots are undoubtedly one of the best examples of AI technology in banking, as they have improved the customer experience over time. The likelihood of having a banking assistant helping you 24*7 with various queries and doubts is now possible with AI. The best part of the AI is that they keep on learning the customers’ behavior patterns to provide a much more personalized experience.

Banks that have integrated AI into their banking apps can ensure that they can provide round-the-clock assistance to their customers.

Predict Market Trends

The banking sector deals in heavy portfolio investment that delivers excellent returns, but it can also lead to huge net loss. AI, along with machine learning, predicts the upcoming market trends, stocks, or currencies for better investment decisions. AI suggests the best time to invest and alert for potential risk. It has helped banks minimize their loss of investments and gain good returns.

Process Automation

Banks have observed increased operational efficiency and reduced cost by automating specific tasks. As some banks are still practicing old book-keeping and management process methods, it has often led to customers switching to new banks that provide seamless services. Adopting AI helps automate time-consuming, repetitive tasks and enables management to focus on the complex processes that require attention.

Many banking institutions leverage robotic process automation (RPA) to increase efficiency and transaction speed.

Predictive Analytics

AI is often used for predictive analytics to detect specific patterns in the data. Such data can help discover untapped opportunities or disclose operational data metrics to streamline certain processes, eventually reducing cost and increasing revenue.

Manage Regulatory Compliance

Banking and Finance is one of the most highly regulated sectors worldwide to ensure that the banking institutions and customers do not engage in financial crimes that may lead to large-scale defaults.

Generally, banks have an internal compliance team that strictly follows all regulatory compliance. But, this manual process of checking compliances usually takes a lot of time and investment. With the use of AI with deep learning and natural language processing, the application can read the new compliance requirements and keep all the processes up-to-date that reflect the latest compliance.

Risk Management

External factors such as natural disasters, currency fluctuations, market collapse, and political unrest affect the banking and finance industry. Under such circumstances, businesses have to be extra careful. AI-powered with data analytics can help managers understand the market better and make timely decisions.

Summary

In the banking and finance sector, AI technology will provide new opportunities to create value and revamp the process to increase efficiency and reduce cost. This technology is proven to combat financial crime, increase profitability, drive financial inclusion, and boost growth.

Banks are now being transformed into consumer tech firms deeply rooted in finance. The online banking platform won’t be limited to a place for banking transactions but also create a space for the financial world with its robust ecosystem and APIs. Hence, leveraging the latest advanced technology in the banking and finance sector will be the key to strengthening data protection protocols and increasing efficiency and collaboration.

At UsefulBI, we work with financial and banking institutions and offer custom AI and ML-based models to reduce cost, mitigate risk and improve revenue. If you are looking for an AI expert for implementing AI in banking strategy, you can get in touch with us, and we will provide you with a robust strategy that is cost-effective and tech-friendly.

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