- 1 AI in Banking
- 2 Why AI is Transforming the Banking Industry?
- 3 How Exactly Is Artificial Intelligence Used in Banking?
The use of artificial intelligence in banking has continued to grow, and machine learning has significantly influenced the banking sector. This article will discuss AI in banking, why it is transforming the industry, and what the future holds for artificial intelligence banking.
AI in Banking
AI, or artificial intelligence, is very prominent in banking solutions. These tools allow companies in this sector to make data-driven decisions and automatically processed data in a way that is very similar to how a human would interpret it.
Traditionally AI in banking was limited to computer calculations and accurate data collection, but now machine learning algorithms are used to do everything from making predictions about customer behaviors 2 analyzing the stock market and determining the likelihood of a customer loan default.
There are virtually no departments in banking firms that are untouched by artificial intelligence. Machine learning platforms are incorporated into operations such as auditing and fraud detection, as well as marketing and customer service.
Why AI is Transforming the Banking Industry?
AI is transforming the banking industry in more ways than one, and according to studies by Accenture, artificial intelligence banking is set to add over $1 trillion in value to the industry by 2035. Similarly, their research discovered that machine learning in banking could help companies realize up to $1 trillion in cost savings.
Here are a few specific reasons why AI is transforming the banking industry:
Reducing Operating Costs
Minimizing operating costs is a goal for almost any business, and the banking industry is no different. One of the primary ways artificial intelligence helps financial institutions is by helping them save money by reducing the time and effort it takes to complete manual data collection and paperwork.
Repetitive and time-consuming tasks reduce employee productivity and also expose banks to the risk of human error. Machine learning models can automate many of these tasks, such as collecting, classifying, and entering customer information into forms and documents.
Implementing AI banking into daily operations has been found to reduce costs by up to 25%. This study by Accenture showed promising evidence about the impact that machine learning has in banking.
Enhancing Customer Support
If you’ve ever needed to call your bank on the weekend or holiday, you know how frustrating it can be when no one is available to pick up the phone. Banks typically have shortened hours, and individuals who work full time may have trouble going to a local branch to resolve their issues in person.
This is where AI technology like chatbots and virtual assistants come in. All a customer needs to do is interact with these tools that are available 24/7, regardless of time zone, so that they can resolve their issues quickly and effectively.
These chatbots can have human-like conversations and use the information available on each client to personalize the interaction, thus significantly enhancing the bank’s customer support capabilities.
Compliance, Compliance, Compliance!
Companies in the banking industry are some of the most regulated entities across the globe. They have to implement reasonable policies and procedures to minimize risks, safeguard their customers, and comply with all relevant legislation.
Artificial intelligence in banking is especially helpful when it comes to anti-money laundering frameworks within an organization. Machine learning models can quickly analyze data to perform an accurate risk assessment regarding their customers so that they can minimize the risk of financial crimes.
Not only do these tools perform identity verifications and sanction screenings, but they also continuously monitor client behavior to detect any suspicious changes or unusual activity. For example, AI in banking is what allows systems to automatically notify a client when a purchase has been made far from their location or for an unusually large amount.
How Exactly Is Artificial Intelligence Used in Banking?
So, now that you have an understanding of the ways artificial intelligence is transforming the banking industry, let’s dive into specifics about how AI is used in banking.
Let’s start with virtual assistance, which we briefly touched on above. Virtual assistants allow banks to enhance the customer experience by providing personalized, human-like interactions everywhere from their mobile app to their online website – and they are available 24/7.
Virtual assistants may not be able to handle all customer inquiries, but they can collect the information and transfer it to the right department so that it can be handled right away.
Bank of America has implemented an AI chatbot named Erica, which helps customers manage credit card security and debt reduction. This virtual assistant processed over 50 million requests in 2019 alone, and a wide variety of customers utilized the service.
Erica is continuously learning new information about the client, and based on this, it provides relevant information in personalized customer support. It has multichannel capabilities, so customers can obtain help through voice inputs or text messaging – whichever is most convenient for them.
Since banks are at such high risk for fraud and financial crimes, machine learning in banking has also been applied to fraud detection. These algorithms can analyze massive amounts of data very quickly and can further understand the underlying trends and patterns in the information collected.
For example, an AI platform used in a bank main monitor your transaction history and provide an alert when there is a purchase made at an unusual location or for a dollar amount that exceeds the normal thresholds.
Not only does this help banks remain in compliance with their anti-money laundering regulations, but it also ensures that customers are quickly notified of unusual or suspicious activity on their accounts.
Fraud in the financial sector costs banks up to $600 billion globally. in other words, failing to implement this technology can lead to real financial losses. By implementing AI banking tools that automatically prevent fraud, they can minimize their exposure to these risks and boost their reputation to the public.
Another important application of artificial intelligence in banking is the ability to access your account and process transactions through mobile apps. In today’s technology-driven world, everything is mobile – and that includes banking.
Artificial intelligence allows for features like facial recognition when logging into your bank account from your phone and eliminates the need for you to enter your password manually. This enhances security and allows banks to reduce their operational costs while still allowing customers to access their accounts at any time.
So, how does this work? The machine learning algorithm analyzes the image captured from our phone and compares it to the specific patterns that we have on our face. If there is a match, you will be able to log into your account successfully – however, if the algorithm detects that the user is not you, the account will not be accessible.
The key is that a mobile app is always available. Banks can easily analyze the data that is collected through these channels, and the mobile capabilities facilitate communications between the client and the company.
Loan and Credit Decisions
A unique aspect of AI banking is the ability of machine learning models to predict whether or not a customer would be a good candidate for a loan or a line of credit.
Think about the last time you applied for a new credit card or requested a mortgage. You likely filled out a form online that included some personal information regarding your identity and financial situation.
Depending on the company you applied with, you may have received a pre-approval instantly – even if it was 2:00 AM and the banks were closed! This is made possible by artificial intelligence in banking.
An AI platform analyzes the information you provided, instantly ran your credit, and determined the likelihood that you would default on the loan or have a high credit risk. If the system decided that you would be a good fit, you were offered the credit card – otherwise, you will receive a notice that you were declined.
Future of AI in the Banking Sector
As you can see, artificial intelligence in banking has already permeated many different parts of the industry. However, we live in a digitalized era, and the technology available to banks is still developing.
We expect the use of AI banking to continue to increase, whether it be to reduce internal operating costs or to improve the customer experience. Technology is enabling banks to maximize the resources that they have available to them while empowering their clients to find solutions to their problems by using their virtual assistance and mobile apps.
These tools will only continue to improve, further enhancing the fraud detection and prevention capabilities of companies in the banking industry. Eventually, it will come to a point where if you are not utilizing machine learning in your bank, you will fall behind competitors, and customers will go elsewhere!
The banking industry is facing a major shift towards embracing artificial intelligence for everything from transaction monitoring and fraud detection, to customer service and mobile banking. Customers are continuously looking for a seamless experience and 24/7 access to your company.
With machine learning and banking, businesses can enhance the customer experience and manage the immense amount of data that is collected so that they could make better strategic decisions.
If you’re ready to get started with AI banking, LogicPlum is here to help. We are experts in end-to-end AI platforms, and we will partner with you so that you can successfully transform your organization into one that is driven by technology and data.