Generative AI enhances banking industry customer service

Generative AI is opening an era for the banking industry, bringing important innovation and becoming an indispensable technology. Generative AI (GenAI) helps the banking industry adapt to continuous market fluctuations, optimize customer service, and improve business performance.

According to McKinsey estimates, GenAI helps create an additional value equivalent to $2.6 trillion to $4.4 trillion annually for the 63 industries and sectors that this unit researches. Among them, banking is considered the industry with the greatest opportunity, with increased productivity that could increase from 200 billion USD to 340 billion USD, equivalent to 9 to 15% of operating profits.

Compared to traditional artificial intelligence, GenAI’s uniqueness lies in its ability to generate new data based on trained data, analyze data, and make predictions. GenAI can work alongside traditional AI to provide more powerful solutions. Especially in the field of banking customer service, GenAI appears as a support, upgrade and supplement partner in applications such as Chatbot, prediction and providing personalized data, freeing up work. for employees and has humanized interaction capabilities, and can even act as a financial advisor in a virtual environment.

GenAI’s applications help improve customer service quality:

1. Enhance customer experience and satisfaction through virtual assistants

Chatbot has become one of the important interaction channels with customers in the service sector. However, due to technological limitations, Chatbots currently cannot understand and interact with humans smoothly. GenAI appeared and transformed Chatbots into intelligent conversation agents, capable of flexible interaction, while being contextual and creative. GenAI is not only a big step forward, but also helps overcome limitations, transforming Chatbot into an “emotional” tool.

Additionally, conversational AI enhances user accessibility by simplifying the provision of multilingual support through virtual assistants and assisting people with disabilities through text navigation options. text and voice.

The use of conversational AI in the banking sector has become increasingly popular in recent years. Large financial institutions such as Bank of America and Wells Fargo have integrated this technology as the backbone of their AI virtual assistants.

Besides, Chatbot/Voicebot equipped with GenAI has the ability to collect and analyze large amounts of customer information data. This information provides valuable feedback about customers’ preferences or problems during the experience, or information about emerging trends in the market. Banks can leverage this data to improve their products, services and marketing strategies to reach customers effectively and subtly.

2. Personalized customer experience

In today’s highly competitive landscape, providing personalized customer experiences has emerged as a key differentiator for banks and financial institutions. By using machine learning models and big data, GenAI can create personalized content and predict future trends for each target customer.

By analyzing extensive customer information, such as transaction history, spending patterns and financial goals, comprehensive AI algorithms can create personalized recommendations tailored to individual circumstances. of each customer.

Banks can take advantage of this information to recommend products according to personal requirements, investment strategies, financial advice or tailor incentives to customers’ needs. This helps increase customer satisfaction and drive deeper engagement.

In fact, 72% of customers believe products are more valuable when they are tailored to their individual needs. By harnessing the power of AI, financial institutions can create more meaningful connections with customers and drive customer satisfaction and loyalty.

3. Free up work for employees

GenAI frees up work for customer service teams by automating repetitive tasks and providing quick access to information resources. As a result, the time to process customer requests is significantly reduced, helping employees reduce work pressure and focus on more complex issues, creating a comprehensive customer service experience. GenAI provides outstanding employee support in the following areas:

Consistency and accuracy: GenAI ensures consistent and accurate responses across all customer interactions. This consistency builds trust and eliminates the risk of miscommunication.

Continuous learning and upgrading: GenAI learns from each customer interaction situation, becoming increasingly proficient and capable of effectively handling future requests.

Increased job satisfaction: With GenAI, employees can confidently and effectively handle customer requests, leading to higher satisfaction and reduced turnover.

Cost savings: Automating repetitive tasks and optimizing staff performance helps banks save costs, as they can handle multiple requests with the same staff.

Gen AI's content creation capabilities: GenAI also redefines customer engagement by helping employees create personalized emails, newsletters and reports. This helps banks maintain continuous communication with customers, provide content tailored to their interests, and contribute to building sustainable interactive relationships.

Challenges and solutions for deploying Generative AI in the banking industry in Vietnam

Challenges when deploying GenAI in Vietnam

Vietnam is lacking a solid AI development ecosystem and appropriate support policies. Additionally, the high cost of GenAI and advanced machine learning, coupled with the scarcity of skilled labor, limits the diffusion of this technology.
GenAI requires large amounts of high-quality data. Inaccuracies in training data can affect the reliability and transparency of the AI model.
Multi-layer infrastructure also poses another challenge for GenAI because this type of AI relies heavily on databases. The banking industry often has limited access to banking data and confidential information.
Banks try to innovate too many things at the same time in the customer care process while they have limited resources such as: capacity, finance, organization, infrastructure and technology.

2. Solutions to deploy AI into the customer care process

Planning and Training

Planning and training human resources with technology expertise and a deep understanding of the organization's goals and processes.

Investing and developing

Investing in measures to prepare, protect and develop high-quality big data

Researching and developing

Continuing to research and develop a unified AI infrastructure solution for GenAI. Enable GenAI to access important information and perform automated processes.

Expanding Ecosystem

The AI ecosystem in Vietnam and supporting policies need to be expanded to help banks maintain competitiveness and prepare for emerging trends, catching up with other countries around the world.

Conclusion

GenAI has truly become an important tool to help improve customer care services in the banking industry. Thanks to automation capabilities, machine learning thinking and responsive interaction, GenAI not only helps the banking industry save costs but also opens up outstanding experiences for customers. Gen AI promises to continue to shape the banking industry, bringing increasingly intelligent and attractive customer care services.

Hekate – A pioneer in AI applications for businesses in Vietnam. One of the GenAI applications used by many businesses in Vietnam is Customer Consulting Service via chatbot. Thanks to the application of large language models, businesses can bring documents, regulations, product and service information into the system. AI will be able to read and understand this data, thereby advising customers like a real consultant.

GenAI’s application brings great value in reducing chatbot training time, thereby helping businesses shorten the time to bring products to market, while also being able to provide conversations close to real people. According to actual statistics, AI chatbots developed by Hekate can help businesses increase operating productivity and reduce operating costs by 30-45%.