7 Applications of AI in banking IMPORTANT most striking 2024

In the digital era today, artificial intelligence (AI) has become one of the breakthrough technology, plays a key role in the conversion of numbers for many industries, in which the banking sector. App AI in banking is becoming an indispensable solution to help the bank optimize the operation process, improve customer experience.

For banks wishing to integrate AI into data system, understanding the potential of this technology will play a key role in the transition of sustainability. This article Lac Viet Computing will go deep into the analysis of the specific application of AI in the banking industry, helping financial institutions to seize the opportunity optimize operational efficiency.

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1. The progress of the application AI in banking

The bank as Vietcombank, VPBank, TPBank have and are investing heavily in AI to develop the chatbot virtual assistant, bringing trading experience quick, convenient for customer.

Specific examples:

• TPBank is one of the first bank in Vietnam to deploy chatbot AI called T’Aio. Chatbot is capable of 24/7 customer support, answer questions about services, accounts, transactions, loan product. TPBank also use AI in process, credit approval, to help reduce the approval time from 3 days to minutes.

• VPBank use AI to detect the fraudulent transactions, monitor millions of transactions per day. System, AI have helped the timely detection of unusual transactions, minimize the risk of financial losses for the bank.

2. 7 Applications of AI in banking IMPORTANT most striking 2024

App AI in banking has been widely deployed in many aspects of the bank focus on areas such as:

1. Applications of AI in service support 24/7 customer care
2. Applications of AI in the analysis to detect fraud in banking transactions
3. Applications of AI in risk management in the way of banking operations
4. AI helps automate the process profile approval loan
5. Enhancing efficiency, asset management, cash flow
6. Applications of AI combined OCR in dissection data, enter data automatically
7. Applications of AI in personalization products customer service

2.1 Applications of AI in service support 24/7 customer care

Chatbot AI 24/7 customer support: currently, the requirements of the customers about the ability to support fast, wherever are increasingly high. AI chatbot plays a pivotal role providing services 24/7 customer support from answering the basic questions to handle the request complex transaction. A study from Accenture indicates that about 53% of the banks in the world have integrated AI chatbot to improve customer experience, helping to save millions of dollars each year thanks to minimize personnel handle directly.

Process optimization, auto-reply, information-processing for fast, accurate: app NOBODY in the bank help automate the process of customer service from the update account information, checking of balance, to support open a new account. Customers do not have to wait long when all queries can be processed quickly and accurately through AI. According to McKinsey, the bank can save up to 25-30% of the operating costs through the application AI to these services. This not only improves the processing speed but also increase the satisfaction of customers.

Practical examples from the bank has successfully implemented chatbot AI:

• Bank of America: With virtual assistant, Erica, this bank has supported more than 10 million users in just one year early deployment. Erica has the ability to solve millions of transaction requests per day from the lookup account to investment advice.
• DBS Bank: Bank of Singapore has this app chatbot AI can solve 82% request from the client, without the intervention of humans, help save $ 30 million per year in the cost of customer support.

2.2 Applications of AI in the analysis to detect fraud in banking transactions

AI has the ability to handle large amounts of data, analyze the trading behavior of customers in real-time to detect the signs of abnormalities. Algorithm machine learning (machine learning) can learn from patterns of fraud earlier to determine the behavior repeat. A report by J. P. Morgan indicates that the app AI help detect fraud with higher accuracy by 27% compared with the traditional method, minimize losses due to fraud amounted to 30%.

Using AI to detect unusual transactions risk warning: AI can analyze transactions in real time to detect unusual signs, such as transactions in excess or from locations strange. The integration of AI into security systems not only help risk warning early but also helps to anti-money laundering (AML) effective. 

The ability to protect data, systems, network security: AI not only detecting fraud, but also have the ability to protect the system from network attacks. With the ability to analyze the behavior detection system models new attack help the bank to stop the attack before it causes damage. According to IBM, the security system, AI can detect attacks faster than 60% and help reduce response time down to seconds, instead of several hours as the old method.

2.3 Applications of AI in risk management in the way of banking operations

Automate the process of risk assessment, credit, financial forecast: App AI in the bank help automate the process of credit analysis based on the historical data, assessing repayment ability of the customers with high accuracy. According to a report from Deloitte, AI can reduce the time credit rating from 7 days down to just a few hours, to help the bank decide quickly improve the speed of processing the loan request.

Analyze customer data to make decisions suitable loan: AI uses big data analytics (Big Data) to provide more insight about the customer, thereby making the loan decision based on many factors such as income, credit history, spending habits. Banks such as Wells Fargo, CitiBank has apps, AI to take out loans more flexible for customers, help to increase the rate of approved loans of up to 15-20%.

Improve model risk management, minimizing bad debts: Thanks to AI, the bank can continuously monitor the financial health of the customer, automatic alert when there are signs of decline in solvency. This helps banks active in the management of bad debt risk reduction. Report by Moody's Analytics, said the bank application AI has reduced bad debt ratio to below 3%, compared with an average of 6-7% ago.

2.4 AI helps automate the process profile approval loan

One of the applications AI in banking important is the ability to automate the process of handling profile approval of the loan, which helps shorten the processing time from several days down to a few hours. AI can analyze handle thousands of profiles loan in short time thanks to the ability to identify classified information automatically. According to a report by McKinsey, the bank has applied AI can reduce the time of processing the loan to 60%, while reducing the percentage of errors in approved up to 25%. This not only helps the bank processing the loan request quickly but also increase the satisfaction of customers.
A typical example is HSBCthe bank has applied AI technology, to process credit approval and processing millions of records of loan each year. As a result, the processing time profile is reduced from 5 days down to 24 hours, saving millions of dollars in operating costs each year.

2.5 Enhance efficiency, asset management, cash flow

The AI algorithms can analyze data, transaction history, financial market trends, in order to optimize the asset allocation, cash flow projections. Help banks not only improve investment performance but also make financial decisions more accurate. A study from the Boston Consulting Group showed that banks use AI to asset management can increase yield investment up 15%, while reducing 10% of the cost of managing cash flow.

2.6 Applications of AI combined OCR in dissection data, enter data automatically

Technology OCR (Optical Character Recognition) combined with AI to help the bank automatically crawls the data from paper documents such as loan contracts, invoices and statements. AI has the ability to handle large volumes of data to help banks reduce manual work, avoid errors during data entry. According to estimates from KPMG, the application of OCR technology combines AI can save up to 80% and processing time reduced by 50% input errors compared with traditional methods.
JP Morgan bank system has been implemented OCR AI for processing the contract, help analyze more than 12,000 cases each year in just a few seconds, instead of requiring thousands of hours of craft work.

2.7 Applications of AI in personalization products customer service

Analyze user behavior to personalize the customer experience: AI can track transaction history, habits, consumer online behavior of customers, thereby providing the financial service is personalization. A study from IBM showed that 79% of customers are likely loyal to the bank than when the service experience is personalized.
For example, Capital One have applied AI to analyze customer behavior and suggest the appropriate services as increase the credit limit or deliver the package to save peculiarities, thereby increasing revenue product sales up 25%.

Proposed financial products is suitable based on big data analytics (Big Data): AI help banks not only understand our customers, but also can auto-suggest financial products is suitable, such as package loan, credit card or investment program. Using big data to analysis, AI can predict the financial needs of each customer, and make recommendations accordingly a more accurate way. 

App AI in marketing, cross-selling products (cross-selling): Through the analysis of customer data, AI can identify opportunities to sell additional products based on shopping behavior and use of services. For example, if a customer has open a savings account, AI can propose more investment products or insurance accordingly. Wells Fargowith the AI system automatically analyzes customer data, has increased the success rate of campaigns, cross-selling, up 15% compared with traditional methods.
In addition, AI also has the ability to optimize marketing campaigns, help the bank reach the right customers with the right message.

3. Applications of Chatbot AI Lac Viet support the bank optimal performance, superior

Chatbot AI Lac Viet is one of the Application of AI in banking bring superior performance in the customer support, process automation, improve user experience. 

Below is a the specific features of chatbot AI Lac Viet, the bank can consult.

• Chatbot AI customer support 24/7: Chatbot AI Lac Viet capable of answering the common questions of customers such as check account balance, account information, transactions, instructions on products and services the bank without the intervention of staff. 
• Process automation technical support: Chat AI Lac Viet can handle the requirements related to engineering, such as the installation instructions app, troubleshoot login or helps to restore password to help reduce the workload of parts, technical support, and help customers quickly get the assistance you need. 
• Support advice personal finance: Integrated chat AI Lost Vietnam to the database of the bank to analyze transaction data, financial habits of customers to give suggestions consulting personalization. For example, the chatbot can propose solutions to save based on your spending habits or making recommendations on investment products, in accordance with the financial records of the customers.
• Handle the request loans, credit counseling: Chatbot AI can help customers apply for loans, providing information about the type of loan, credit conditions at the same time answer the question about the interest rate or payment schedule. Chatbot Vietnam also can guide customers to prepare the necessary documents to complete the loan process.
• Detectable warning fraudulent transactions: Chatbot AI that can detect and warn about the unusual transactions in the account of the customer. When the current transaction has signs of fraud, the chatbot will immediately notify the customer via sms or banking application requires authentication transaction.

4. Development trends applications of technology AI in the future

Although has achieved many accomplishments, app, AI in banking is still on the rise perfection. PwC predict that in the next 5 years, more than 70% of the bank will switch to use the digital platform based on AI to provide quick service, more accurate, reducing the dependence on manual operations. AI is also expected to help the bank expand the new financial product, from consulting services, automated (robo-advisors) to the system asset management.

4.1 AI combined with Blockchain and Fintech

Blockchain provides security platform, decentralized, while AI helps optimize the data analysis, a quick decision. When combining AI and Blockchain can bring improvements in transaction security, transparency, optimize the payment process.

How in practical applications:

• AI can be used to analyze the chain of data blocks (blockchain) for the detection of unusual transactions or fraud.
• Blockchain help secure data input of AI, ensuring that data used in the models AI have not been tampered with or changed.

Actual data: According to the study of PwCby 2030, the combination of AI and blockchain can help banks save up to 50% of the cost of processing the transactionthanks to automating processes, reducing fraud.

4.2 Bank of completely with AI support

One of the trending apps in ONE of the largest bank is the development of the bank of completely (fully digital banks), where all the transactions that interact with customers is done through the digital platform with the support of AI. Bank number allows customers to open accounts, make transactions, financial management, without the need to branch of physics. AI plays a key role in the personalization of the user experience, process automation to optimize services.

Bank N26 of Germany and Chime of America is the bank of pioneering the use of AI to provide banking services without papers. In Vietnam, the bank as TPBank also are strong to bank model number with AI assistant to automate services such as open account, browser loans.

4.3 Automate the process more complex by AI

AI current has automated many processes underlying transactions such as check account balances, transfer money, but in the future, AI will progress farther when that can handle the complex process like consulting, financial analysis, credit risk, predict market trends.

Practical application: Robo-advisor – Ethis is the system investment advisory automatically using AI, allows customers to get advice on financial investments based on your personal data without direct contact with financial advisors. AI has the ability to handle large amounts of information from the market, the individual propensity of customers to make recommendations more accurate.

Integrated AI into the system bank data is not only trends but also the core element to the financial institution holding competitive advantage. With respect to the bank are considering adopting AI, the preparation of a plan to deploy a comprehensive technology infrastructure to training personnel will be key to take maximum advantage of the potential that AI brings.

Deployment Application of AI in banking not only helps to improve operational efficiency but also improve the user experience, automate processes, enhance security. The chatbot AI is becoming an integral part of the modern banking help with optimizing customer service and risk management more effective.