Today, the importance of artificial intelligence in many areas of our lives has increased immensely. Actually, the reason for this is pretty obvious. AI makes a great contribution to facilitating our lives and rapidly improving our ways of doing business in a wide range of industries from health to agriculture, from transportation to urban planning.
With many different technological application areas such as natural language processing, machine learning and computer vision, AI can deliver highly valuable, meaningful results. This is the most important fact that increases the interest in AI as well as in the banking and finance industry. According to a survey conducted by financial services experts, 80% of banks are well aware of the potential benefits of AI and machine learning.
For global banking, McKinsey estimates that AI technologies could potentially deliver up to $1 trillion of additional value each year.
In general, there are three main channels through which banks can use AI to improve their workflow processes and save costs by optimization. These channels are the front office, the middle office and the back office.
AI already offers many important technologies to improve customer and employee experience in the front-office, prevent risks, fraud or any possible human errors in the middle-office and enhance workflow at the back-office operations by cognitive process automation.
Here is a great chart from Business Insider that sums up the uses and cost-saving opportunities of AI in banking:
Now let’s discuss the top values that AI brings to the banking and financial industry:
In the past, if you were a customer of a bank, you used to meet with an employee of that bank face-to-face who closely monitored your financial situation, knew your background, and was responsible for guiding you in the most accurate way.
However, with the rise of digital banking, it is clear that there has been an incredible increase in banking transactions. Banking institutions record millions of business transactions every day. Therefore, it is obvious that such a workflow process based on human power will no longer be possible. It is almost impossible for us, humans, to preserve and make sense of this huge amount of information.
AI-based applications keep all this information together, analyze it and enable us to make sense of this data. Thus, it becomes possible for banks to improve the user experience, generate new business ideas, design more efficient processes, and create low-risk and low-cost action plans.
Today, the functionality of AI offers highly refined, personalized and proactive experiences for the end-user in the banking industry. It is even possible to suggest special shortcuts or customize financial products and services for users by monitoring their activities within a mobile application to deliver meaningful customer engagement and loyalty.
AI also provides great convenience in areas such as providing customer support, chatbots, giving advice with Robo-advisory, making automatic transactions, personalized reminders and personal planning.
By using AI, it is now possible for financial institutions to predict possible future trends and scenarios based on behavioral analyses to be prepared in advance and to be able to respond to the needs of users before they even realize it.
Financial institutions that use outdated software and lend that way can face extremely challenging and risky situations. In the first stage, there will be a long time interval between the application and the granting of the loan, which can take up to three weeks.
The small database of credit scoring factors can lead to inaccurate estimates of certain borrowers. Plus the application of unscientific credit models carries a high risk of wrong predictions. And lending or extending money to customers who will not be able to pay their debts can cause huge losses for financial institutions.
AI, on the other hand, enhances all processes and provides highly configurable and scalable processors to eliminate these possible defaults in credit management. It can easily track customers’ transactions and analyze the data of users. And because it does all these by constantly learning and improving itself, it also provides an extremely agile structure to the financial sector.
Cybersecurity, fraud detection and compliance issues are extremely important for banks. Identifying all these possible situations with the help of AI and machine learning is called anomaly detection. And banks have increased the amount of investment they have made in this field in recent years.
According to the research, it is stated that more than 50% of the $3 billion investment in artificial intelligence in the banking sector is provided by vendors specializing in cybersecurity, fraud, compliance and risk management.
Using AI for anomaly detection enables banks to avoid regulatory fines, preserve their reputation and save a significant amount of time and money with the automated processes at scale. To create all these benefits and value for banks, machine learning uses several relevant techniques for anomaly detection:
Using AI-supported solutions is now more than a trend, it has become a necessity for bankers. AI is now an integral part of bankers’ growth strategies to create the benefits and values mentioned above. However, it should be noted that what is more important than using AI technologies is to implement these technologies in the most accurate and appropriate way.
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