Trendspotting in Personalized Financial Services
A rising trend is leaning towards minimizing customer involvement while maintaining complete transparency. Customers now expect timely and accessible information during the consumption process, a demand that poses both challenges and opportunities for the financial industry. The growing importance of handling the vast amounts of data generated in the consumption process points to the indispensable role of Machine Learning (ML) for event clustering and classification.
Navigating the Data Ocean: ML’s Role in Trust Building
In the vast ocean of data, ML is necessary for event clustering and classification, a crucial aspect for providing precision in personalized financial services. This precision is pivotal in building trust and cultivating lasting partner relationships. A significant shift has been identified in the evolving role of customers, who expect service availability and seek active participation in their financial experience, albeit focusing on decision-making rather than the execution of operations.
Advantages of Utilizing the Virtual Assistant Experience
AI virtual agents offer businesses the opportunity to improve customer service, reduce costs and improve efficiency. They can provide a consistent, convenient and responsive user experience, ultimately leading to increased customer satisfaction and improved operational performance.
- Communication: Users can communicate naturally and ask the virtual assistant questions like they would ask a person. Assistant handles most situations. Even when the user’s writing contains grammatical errors or is spoken with an accent, and the voice is briefly lost.
- Availability: Virtual assistants can “work” around the clock, providing answers anytime. This improves the quality of services and ensures that users can receive timely assistance.
- Efficiency: Virtual assistants reduce operational costs by automating routine tasks, ensuring multitasking and constant availability.
- Scalability: Virtual assistants can handle many dialogues simultaneously.
- Dynamics: Assistants can provide immediate responses, as the information base can be updated in real-time and respond with the newly available information.
- Multilingual support: Assistants support up to 30 of the most common languages, effectively allowing businesses to serve a global customer base.
- Synthesis of information: Virtual agents help users find the information they are looking for at the moment. This dramatically reduces the need to search or navigate complex interfaces and read incredible amounts of text.
- Fewer errors: Assistants do not succumb to fatigue or lack of attention and can consistently provide accurate information without errors.
A Series of Challenges FinTech Companies Face with Virtual Assistants
- Limits of NLP systems - Prompt Engineering: Prompt instructions program the assistant’s behaviour. Creating effective prompts is critical to getting the information you want and keeping the conversation flowing naturally. Creating useful prompts is challenging, especially regarding complex conversations involving specific information.
- Limits of NLP systems - Ambiguous/multi-valued questions: The user will sometimes not ask the question with the specificity that the huge amount of information poured in requires. This may lead to an incorrect answer to the question. But still, there are options to mitigate this; ultimately, the user can always be transferred to a person.
- Multilingualism: Implementing a virtual assistant in multilingual or multicultural settings requires adaptation to different languages and cultures, which can be complex.
- Efficient processing of huge amounts of information: Processing the information for use with an assistant is an important and difficult task, especially when the data is in huge amounts. We have automatic processing, but human intervention is needed to process the data further so that users always find the right information.
- Limits of “end-of-speech” detection: This is a normal challenge in virtual assistants, especially regarding a continuous conversational stream (e.g. a phone call dialogue).
- Speech-to-text problems: The critical ones so far are speaking with a dialect/accent, a noisy environment, and still a few languages to use.
Overcoming these challenges requires careful planning, monitoring, iterative improvements, and collaboration with AI and NLP experts. Successful implementation involves addressing these issues to ensure the virtual assistant delivers the intended benefits while providing a positive user experience.
The ChatBots’ Evolution - The Journey to Becoming Virtual Assistants
Sirma is an established leader in integrating audio-visual solutions, commonly known as chatbots, for front-office tasks in the banking sector. In their recent role as virtual agents or virtual assistants, they have surpassed the limitations of text-based communication. They can recognize voice, speak, and even interpret images and drawings, breaking the mould of traditional “process automation software” and taking on a more dynamic, intelligent persona. The new generation of assistants is designed by talented programmers and business experts specializing in diverse areas. The continuous evolution of virtual assistants promises a focus on heightened personalization and pushing the boundaries of what these technological marvels can achieve.
Paving the Way for Next-level Personalization
Our expertise helps Sirma clients gain a comprehensive view of the dynamic landscape of FinTech Virtual Assistants, showcasing their evolution into virtual assistants and how they become advanced solutions that deliver much more business value. Their new role unveils the industry’s commitment to next-level personalization, setting the stage for a transformative journey in the realm of personalized financial services. Here, you can learn more about Sirma’s comprehensive AI-driven conversational virtual assistant, Melinda, which is specially designed and trained to serve banks and financial institutions.
