The implementation of conversational AI and automation has the potential to bring about a significant transformation in the banking and financial sectors by streamlining repetitive tasks and enhancing the customer experience.
By leveraging AI and automating contact centers, banking and financial services can be made more accessible and user-friendly. The integration of conversational AI in these sectors can facilitate the resolution of both simple and complex queries.
According to the Economist, 37% of financial service providers around the world have adopted AI to reduce operational costs. This is followed by the use of predictive analytics to enhance decision-making processes and enable employees to handle high-volume tasks.
Today, all banks and financial service providers offer mobile applications that customers can use to avoid long queues.
However, a significant population still needs to register on the mobile applications of banks and other financial services, and there could be various reasons behind this lack of engagement, such as:
- Lack of technical knowledge or proficiency: Not everyone is tech-savvy, and people might not know how to register and use the apps.
- Unfamiliarity with the features and benefits: Some people may still prefer traditional methods because they are unaware of the distinctive features and benefits of digital banking apps.
Ongoing issues in banking and financial services in the absence of conversational AI deployment :
- Availability is limited : Without conversational AI, banks may have limited availability to provide customer care, which could pose a problem for consumers who anticipate 24/7 assistance.
- Higher call volume : Banks and financial services often face a high volume of calls and queries from customers, which can lead to long wait times and unsatisfactory experiences. These queries are often simple and straightforward, such as checking account balances or transaction history, and can be addressed through the use of conversational AI, which can automate the resolution of these queries, thus saving time and resources.
- Lack of personalization : Banks may find it challenging to provide personalized service to each customer without conversational AI in financial services. It requires significant resources to handle individualized requests, resulting in a lack of personalisation.
- Difficulty handling complex inquiries : Banks may face challenges in handling complex customer inquiries such as those related to fraud detection or financial planning without the use of AI since they may require specialized knowledge or expertise.
- Limited language support : In the absence of NLP, banks may face limitations in providing customer service in multiple languages, which can be a hurdle for customers who are not fluent in the supported languages.