The Banking Industry is undergoing a new dimensional shift in customer services. Technologies like Artificial Intelligence into banking processes are giving them a new edge. By leveraging this, the banks aim to minimize their expenses, exceed customer expectations, and meet margins.
To maintain competitiveness and stay ahead of the game, the financial organizations are growing in leaps-n-bounds with Blockchain, Machine Learning, and Cryptocurrency technologies. These technologies with AI are revolutionizing the banking industry like never before.
The impact of AI in the banking industry has been extraordinary. It is entirely redefining its functioning, products, services, and customer experience.
The AI technology can be applied to various traits of the banking industry to simplify the financial processes, let’s discuss them step by step.
Applications of AI in Bank and Finance Industry
1. Cybersecurity
On a daily basis, billions of banking transactions take place globally under a variety of payment modes. As a result, the customer’s finances and all personal data are prone to threat.
Threats could be in the form of data theft and loss of finances. Hence, banks are turning to AI technology-enabled Cybersecurity to fight against such attacks.
Along with AI, the other supporting technologies, such as blockchain, machine learning, natural language processing, etc. are noticing and managing threats automatically. These technologies are maintaining efficiency and accuracy as well.
A huge number of user information is available on the World Wide Web. Thus, a tiny flaw could turn out to be severe. Cybercrime leads to disruption in customer services. So, strict cyber security regulations are implemented by government bodies to empower banking industry data adequacy.
2. Risk Management
Banking services are always open to threats and risks. For example, in loan approval, the authorized person has to verify all the details and credentials of the customer. It includes checking financial status, document verification, etc. After all such processes, the loan is approved. Yet the risk always exists due to manual inability in data analysis and research.
On the other hand, the use of AI in this process can deal with the situation quickly and accurately while maintaining customer’s privacy.
The application of AI in banks and finance is expanding its reach under the banking security processes. This enables security of each step with the proper authentication process. AI in the banking industry can minimize expense and manpower to automate the ‘Know Your Customer’ (KYC) process. It enables customer identity verification within seconds while removing potential inaccuracies.
3. Fraud Detection
Fraud is the most common issue the banking industry faces. With the innovation in technologies, such issues have been controlled to a great extent.
AI in the banking industry helps to detect and predict system irregularities to prevent fraud. Despite that, businesses struggle with such issues. The occurrences of such scenarios can be eliminated. Though, it requires regular training and updates.
There are numerous machine learning algorithms that are specially designed for detecting irregularities. The algorithms are very effective in analyzing fraudulent activities or transactions. It can also analyze various aspects to detect transaction-related concerns and raise a warning quickly.
4. AI Chatbots
Chatbots are the most user-friendly conversational interface by AI in the banking industry. It provides a personalized banking experience to customers, at any time of the day. The NLP-enabled Chatbots can easily identify customer emotions. Based on that they can modify their responses instantly without any human intervention.
AI chatbots in the banking industry can reduce the workload from internet banking, contact centres, and other departments. Such tools also support banks to get free from repetitive manual tasks and improve the customer service quality.
No doubt, banks with AI chatbots can have better cost control.
5. Enhances Customer Service Experience
To gain new customers and retain the existing ones, the best bet is to upgrade services at minimum charges. Customers are the major source of revenue generation for every business. The automated and anytime services will add brand value to the business.
For example; Chatbots can enhance customer experience by providing 24x7 customer support. Likewise, ATM services are a success globally. At an ATM, customers can perform basic banking, such as cash deposit and withdrawal even when the banks are closed.
Demand for higher customer convenience has attracted more innovation. Such as, customers can clear their bills and other payments with just a few clicks. They can even open new bank accounts from the banking apps. All these handy services and upgrades in service delivery can improve overall customer experience with banking services.
6. Data Collection and Analysis
On a daily basis, the banking and finance industry generates a huge amount of data. It could be a tedious task for employees to store and manage it structurally. Under such situations, AI can support the banking industry to perform quick data collection and analysis. The detailed analysis of data enables the user to experience more personalized data or assistance.
The application of AI in banks and finance enables easy data analysis. This ultimately improves the overall user experience. It also helps to detect fraud or make most suitable decisions.
7. Regulatory Compliance
Compliance means abiding by the law and rules & regulations. It is crucial for the banking industry to follow ethical methods. It introduces transparency in their processes while maintaining high standards.
Mostly, banks build an internal compliance team to handle such issues. These issues require more time and heavy investment for banks, if done manually.
The AI-enabled banking software can instantly look for the valid rules and ensure to abide by those rules. With continuous changes in technologies and business activities, these compliance regulations can also be changed or updated whenever required.
AI uses NLP and Deep Learning technology to read new regulatory compliance for banks. It also improves the decision-making process. AI supported banking software enhances compliance officers’ skills and supports them to improve operations.
8. Process Automation
AI has a lot to offer when it comes to automation. Technology like Optical Character Recognition (OCR) can enhance the pace or efficiency of boring and time-consuming tasks of employees.
On the other hand, the Robotic Process Automation (RPA) algorithm increases accuracy, operational efficiency, and minimizes expense by automating repetitive and uninteresting tasks.
In an automated process, high-level security can be presented. Such as, making it mandatory to present a unique ID to avoid fraud. The AI software verifies the presented ID details to check its authenticity.
9. Analyzing Market Sentiments
The use cases of AI in banks are infinite. AI in the banking industry can study the piles of data quickly. Based on that data analysis, one can deduce the ongoing trend or sentiments of the financial market. The advanced ML techniques help to evaluate market sentiments. It also suggests the most suitable investment options.
AI in the banking industry can also predict the most suitable investment options. It can generate alerts from the potential risk. All these automated data analyses and market sentiments prediction allows customers to take instant and correct decisions in the trading and banking processes.
10. Utilizes Knowledge Database
AI-enabled systems comprise a wide pool of data. It stores all the relevant details of registered users. A well-formed and organized database allows us to make accurate decisions. It is based on business model plans and strategic improvements.
These AI-enabled tools are like humans in decision-making and perceptive thinking. The study of previous data can help to analyze the business growth, trends, customer demands, online transactions, etc.
Based on all such data study, banks can formulate strategies to introduce new marketing strategies. This helps to attract and retain more customers, which ultimately results in improved ROI.
Conclusion
The banking industry is leveraging technology with both hands to transform their businesses and customer experience. The growing adoption of AI in banking is transforming the industry. It is also demanding an instant shift from traditional banking.
Such transformations promote embedded banking, open data, instant payment, and more. Given this, banks must quickly shift and adopt trending technologies. It includes AI and machine learning in their daily operations. This supports reducing expenses and increasing efficiency with greater accuracy and precision.