AI in Banking: Market Stats, Benefits, and Use Cases! | by Gautam Raturi | Jul 2022

Even with the negative economic effects of COVID-19, the banking sector is one that is growing. Even more than before, the banking sector is adapting to the new realities of the world by implementing cutting-edge technologies, including the use of artificial intelligence.

AI has the potential to overcome many traditional banking challenges. But how?

Let’s find out!

In this blog, we will discuss everything you need to know about AI in banking. We will also discuss the benefits and use cases of AI in banking!

So, without taking much of your time, let’s quickly start with,

Key market statistics!

  1. According to a study by McKinsey, AI technology could increase the value of global banking services by up to $1 trillion per year. By adapting services and reducing costs by improving the efficiency of internal operations, the AI solutions for banking and finance can also help increase income.
market statistics AI in banking

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2. According to Forbes, one in three financial services workers expect AI to increase their company’s annual revenue by at least 20%.

As you have seen, key market statistics point to the potential of AI application development services for the banking and finance industry.

Now, let us move forward and discuss the main component of this blog, which is,

Also read- How to develop a highly secure FinTech application?

The key benefits of using custom AI solutions for banking are:-

#1. Lower workload

By being accessible 24/7, AI-powered assistants and chatbots can reduce the manual workload of banks and their employees. Customers can use chatbots to help them with basic banking tasks, including opening or closing accounts, transferring money, and opening investments, among others.

#2. Strengthen data security

The use of intelligent AI solutions in banking and finance reduces fraud while improving accuracy and security and spotting potential fraudulent activity before it occurs. For remote operations in particular, banks can leverage AI and ML to verify the identity of their customers and improve the accuracy of the identification process. The banking industry must rely on technology as online activities proliferate to ensure data accuracy and reduce the risk of fraud.

#3. Better customer experience

Banks and financial services companies will be able to better understand their consumers by leveraging big data and AI. This allows them to move from a customer-centric to a product-centric approach, enhancing their offering with tailored services. Offering automated on-demand support, chatbots, and AI-powered virtual assistants can also improve the customer experience. Additionally, loan applications, which once took weeks to process, can now be processed in days. AI is able to conduct fair analysis based on a variety of credit factors.

#4. Risk management

Through accurate reporting, these technologies reduce risk for both customers and banks. After extending credit to customers, predictions can be generated using transaction history. Bank employees have more knowledge about credit risk analysis. Early identification of errors and knowledge of potential future risks contribute to the banking industry’s ability to plan ahead.

#5. Improve operational efficiency

By processing large amounts of data and improving the accuracy and speed of mathematical calculations, AI algorithms can help banks streamline their operations. By reviewing historical data, for example, banks can quickly identify the best trades to reduce initial margin. They can then use the knowledge acquired to test models for evaluating risk models and improve capital optimization.

As you have seen the benefits of AI in banking, now let’s check,

The main use cases for AI in banking are:

#1. Robi advisor

Robo-advisors are not only cheaper alternatives to traditional financial advisors, but they can also help a large number of consumers receive financial advice and make better financial decisions. Additionally, AI-powered, data-driven robo-advisors can offer investors advice on estate planning, retirement, and other topics, which can make the account opening process more engaging.

#2. Credit report assessment

In order to assess the complete financial situation of the client, AI is used to review investment, cash and credit accounts. As AI generates tailored advice based on any new incoming customer data, it helps banks track changes in real time.

Banking institutions can now handle much more information about their customers than in the past. To determine if the customer is eligible for the goods or services they are requesting, this data is reviewed and assessed.

#3. AI chatbots

Chatbots and personal digital assistants have changed the way customer service and communication are provided. In order to provide customers with a highly personalized experience, chatbots have been developed. The use of AI in banking has the potential to completely transform the way customers access banking products and services.

As AI improves, banking industry chatbots are becoming more accurate and convenient. AI software applications known as chatbots communicate with users via text and speech. With the use of machine learning, deep learning and natural language processing, the operational capabilities of chatbots are enhanced. With the integration of AI at its core, chatbots can leverage contextual knowledge to offer appropriate recommendations and provide informed responses to customer inquiries.

#4. AI-powered mobile banking apps

Artificial intelligence technology is mainly used by banks to improve and personalize the customer experience.

Mobile banking services are frequently used by Generation Z. This indicates that AI-powered banking apps can provide contextual, personalized and predictive services to meet customer expectations among young people. AI-powered mobile banking apps can monitor user activity and provide personalized advice and information on payments and financial matters.

#5. Fraud prevention

Fraud has always been a problem in banking. However, credit card issuers are integrating predictive analytics into their anti-fraud workflows using artificial intelligence, dramatically reducing false positive results. AI-powered analytics solutions collect and analyze data by seeing and learning patterns of user behavior. This is then done to identify scarcity and any indicators of fraud attempts and incidents.

#6. Quantitative trade

Using large data sets to identify patterns that can be used to make strategic trades is known as quantitative trading. Banking institutions can assess any number of complex data sets faster and more efficiently through the use of AI-powered solutions. By automating trades, this algorithmic trading method can help the service provider save valuable time and resources.

Read also:- Development of personal finance management applications — A complete guide.

The potential of AI in banking continues to evolve as we enter a whole new digital era. Innovations based on artificial intelligence have given the banking sector considerable leverage. As a result, banks and other financial institutions are increasingly offering their customers premium financial services.

In order to create portals, mobile applications and web applications leveraging AI for banking and many other industries, contact one of the best AI development company.