The Age of Conversational AI in Retail Banking
Retail banking is becoming increasingly competitive due to many existing banks and unorthodox new players entering the market, such as neo-banks. They were first ancillary service providers before becoming financial institutions. They offer a wide range of unconventional banking services, and their in-house developed technologies even allow them to adapt to changing customer demographics. To fill gaps in service delivery, BFSI participants cannot afford to fall behind.
Marketing but also sales
Millennials are the customer with disposable income, and their behavior will determine how the bank will change next. They demonstrate greater financial sophistication and are comfortable with banking applications. The desire for instant banking experiences is already established, but a Capgemini report indicates that 58% of millennials say they are attracted to personalized goods and services.
Collecting insights into customer preferences using conversational AI tools that seamlessly integrate with omnichannel analytics suites is simple. In retail banking, voice robots can improve results by streamlining marketing and sales procedures. For better conversion, they can be configured to meet prospect criteria during the window of opportunity.
Long call wait times, tedious questions that frustrate customers and agents, delays, routine case transfers, etc., are annoying. According to IBM, chatbots can help companies save up to 30% of customer support costs by speeding up response times, freeing up agents for more difficult tasks and answering up to 80% of routine questions. . To handle higher call volumes, voice bots can help contact centers. Due to their familiarity with an authentic human voice, users love voice calls over IVR calls or chatbots.
Conversational AI can be used to create retail banking software that gives users more interface options. Automating repetitive manual operations can reduce expenses, increase productivity and improve efficiency.
Bot-based bill payment
Voice bots can help send important payment reminders. Transaction requests can be made more securely and in a language familiar to the user. Additionally, voice robots can be programmed to answer basic questions such as setting credit card spending limits or asking for an account balance. IVRs and inaccessible contact center managers only compound people’s problems, such as stolen cards, broken PINs, and more. They can follow the instructions provided by the voice bots to report these issues and continue the process.
How retail banks can benefit from AI
With the right tools, banks can double their transaction volume while maintaining accurate headcount through artificial intelligence. Ai can result in significant cost savings. These are the benefits of AI for banking and finance.
Fraud detection and regulatory compliance
Early detection of fraud and complete audit documentation are both possible through the use of a decision management system. Large-scale data analysis by artificial intelligence identifies suspicious transactions. These transactions are inaccurately analyzed by hand. It is easy for offenders to launder money or fund illegal activities when there is no AI fraud prevention system in place.
An improved customer experience
Convenience is something that customers are always looking for. To illustrate, the ATM was successful because it allowed users to access a critical service even when establishments were closed. This degree of comfort only sparked more incredible inventions. Customers can now open bank accounts and identify themselves using smartphones while relaxing on the couch.
Improved investment appraisal
Human evaluators are still tasked with making an investment choice. The method is simplified and can handle additional variables through investment analysis software. Access to information may be lengthy if the institution has cross-border interests. The right AI software is key to speeding up the process of evaluating a new environment, which can be difficult.
Lower operating costs and risks
Even though we value interpersonal relationships, there is a huge downside. Errors occur frequently and can have adverse effects. Even with seasoned staff in charge, pressing a key incorrectly could put the institution at risk of legal trouble and damage its reputation beyond repair. By incorporating logical flows into data collection and using prescriptive and predictive methods to solve business problems, decision-making systems reduce this risk.
The future of conversational banking
The near future will be dominated by banking using conversational interfaces. Here’s a look at what conversational banking could accomplish in the near future.
- Conversational AI will handle complex queries, understand consumer sentiment, etc., and provide FAQ answers for highly personalized dialogues.
- The commitment in context will prevail. The dialogue will continue from the same place as a consumer moves from channel to channel to maintain it.
- Customers will be offered a variety of alternatives, including voice, human, and more, as AI for conversational banking develops.
Any technological developments in the banking industry would make the conversational banking roadmap difficult. Banks must implement innovative marketing techniques to succeed and create a compelling vision of the future.
(The author is the founder and CEO of Twixor)