Artificial intelligence will affect the banking business (AI). Customers are getting more interested in online-only businesses. Even banks that have been around for a long time have started to add more online services.
The use of artificial intelligence makes business operations more efficient. It improves the quality of their decisions. It helps them better handle customer support needs while using fewer resources.
Also, it is a very important part of risk management because it stops fraud and stops the laundering of illegal funds in real-time. AI can enhance banking in many ways. Here we’ve described AI’s most prevalent banking uses.
Key Challenges Faced By The Banking Industry
Here are some of the biggest problems the banking industry is facing right now:
1. Customer expectations
Customers’ expectations are growing as more and more people use their smartphones, tablets, and computers to do their banking on the go.
Traditional institutions’ old ways of doing business and giving services are being put to the test by the rise of digitization.
Competition in this industry has gotten tougher than fintech companies. Also, other large technology companies have joined the market.
Companies need to continually adapt their business practices to comply with the regulations.
5. Staying Relevant
AI technology is used in all parts of the most successful businesses. Because of this, others need to stay up-to-date on how technology is changing so they can stay ahead of the competition and keep being useful.
How AI Can Help The Banking Industry?
Let’s look at some common and unusual ways that AI technology is helping the banking industry.
1. Process Optimisation
Modern banks are always looking for new ways to increase their profits while lowering their costs of doing business. Activities on the front end and the back end are necessary for this.
In Customer Service
How well the bank takes care of its customers has a direct effect on how its customers feel about their banking experience as a whole. It includes services like creating an account, making deposits and withdrawals of money from an account, using an ATM card, transferring funds between accounts or accounts held at other banks, and so on.
AI can help by using smart chatbots to speed up tedious customer service tasks. In these processes, you can automatically handle simple customer requests and sort tickets.
Chatbots can also be used to notify customers, give them information about their account balances, and suggest ways for them to save money. It can keep them up to date on their credit reports, helps them pay their bills, and helps them with simple transactions.
Here is the graph on how banks are using AI in the UK:
The operations function of a bank is the part of the bank that is in charge of making sure that all parts of the bank’s operations are done well. This includes a wide range of tasks, such as customer service operations, back-office support, contact centre operations, and ATM operations.
AI can handle large amounts of information quickly utilising machine learning. This can improve accuracy and efficiency while lowering operating costs.
Here are the statistics on the state of machine learning in UK financial services:
In the United Kingdom, more and more financial services companies are using machine learning (ML). 72% of the companies that took part in the poll said that they already use ML applications or are in the process of making them.
These applications are becoming more common in a growing number of business areas quickly. This trend is likely to keep going. Businesses expect that the average number of machine learning applications will grow by a factor of 3.5 over the next three years.
In terms of absolute growth, the insurance industry is expected to grow the most, followed by the banking industry.
Fraud in the banking industry is when someone uses financial services dishonestly or intentionally to get money. Fraud at a financial institution can be done by customers, bank employees, or even people who aren’t supposed to be there, like cybercriminals who break into bank computers.
A common example of banking fraud which came into limelight recently. In this fraudsters pose as agents who give instalments loans for bad credit from direct lenders only and then dupe the customers. They ask for a hefty registration fee at first and then ghost them.
In the past, rule-based solutions have been used by businesses to stop fraudulent payment attempts. But more fraud could happen because more people are using digital technology. As the number of services available is growing.
When it comes to making decisions about fraud, banks need to be quick, accurate, and efficient. They also need to grow quickly and look for ways to spot fraud that don’t cost a lot of money.
AI and ML technologies can help with this. It involves running hundreds of thousands of queries and comparing the behaviour of individual customers to “normal” customer behaviour in order to find outliers. Everything happens in the present moment.
3. Trading and Wealth Management
Trading in banking is when a bank buys and sells securities for its account. In trading, underwriting, dealing, and financing of transactions are also included. A key part of wealth management is giving clients all-around advice and services for investing.
The term “Robo-Advisor” refers to a certain type of online wealth management service. It uses pre-programmed algorithms to make recommendations about how to manage investment portfolios.
AI-powered tools can help traders speed up the process of making new accounts and give them advice on how to grow their portfolios. This includes, among other things, making a financial plan and giving advice about planned property purchases, retirement, security needs, and other parts of state planning.
A stock market helps investors purchase and sell company shares.
AI and ML can be used in the stock markets for several things, such as getting objective information, processing data, putting data into categories, stock analysis, and recognising patterns.
AI can also help asset managers and hedge funds in several ways. The AI-based tool can find hidden linkages, news, and look-ahead bias. Also, other online information that might modify investing decisions and halt massive losses.
Security and Compliance
When we talk about security, we mean keeping IT systems safe from attacks by hackers and viruses and from people who don’t have permission to use them.
Artificial intelligence can find security flaws. For example, by looking at documents for account registration or finding problems within accounts.
To improve cybersecurity, banks may use unsupervised machine learning algorithms to create a “pattern of life” for each person. You can use a device that is part of the business to find outliers and real security risks.
AI can also help make sure that data is safe and private. Banks protect critical customers’ information. Machine learning algorithms may now be used to look at data. It can determine where it’s held and if it’s encrypted, and make any necessary modifications.
The financial industry is highly regulated. This means that financial institutions must follow all of the rules and laws that are set by regulatory authorities. The main reason why these rules and laws were made was to make sure that the money in the bank was safe.
Using AI and robotic process automation, a corporation may make real-time regulatory modifications.
AI-based systems can scan and analyse millions of lines of regulatory information. You can easily access legal documents, commentary, advice, and court cases. You can also find relevant requirements much more quickly and make compliance easier.
In short, artificial intelligence is likely to play a big role in the banking industry. Everything will be different. It will change how the companies run on the inside to the products and services they offer customers online and on different devices.
AI is not the future of banking, even though it is being used there now. The important time is now. Quantum, edge, and cloud computing will shake up the business as more data becomes available.
Apart from the baking industry, there are several other industries that are opting for AI for their operations. Even small businesses are making their way through AI. They are reaching out to banks or direct lenders for loans to make technological advancements in their operations. However, it is observed that most of them reach out to direct lenders to apply for loans such as instalment loans for bad credit from direct lenders only or quick cash as these loans don’t require any credit checks and often come with negotiable risks.
To be successful, you will have to make a big change. It must affect many parts of the business and brings together the people, processes, and data that will be working together. It is no longer a choice for these companies. Instead, it is a strategic need for them to make sure that AI technologies are used throughout the whole company.