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Development of a Friendly Voice Assistant for Financial Service Mobile Application
  1. case
  2. Development of a Friendly Voice Assistant for Financial Service Mobile Application

Development of a Friendly Voice Assistant for Financial Service Mobile Application

e-point.com
Financial services
Other industries

Identifying Customer Interaction Challenges in Digital Banking

The client seeks to improve customer engagement by reducing dependence on traditional support channels, streamline routine transactions, and increase accessibility for all users, including those with visual impairments. The current mobile application lacks intuitive voice-driven interaction, limiting user experience and operational efficiency.

About the Client

A large, market-leading bank aiming to enhance customer self-service and accessibility through innovative digital solutions.

Objectives for Enhancing User Engagement via Voice Technology

  • Design and implement a friendly, easy-to-use voice assistant to facilitate banking transactions and information retrieval.
  • Enable the voice assistant to handle a comprehensive set of user requests, including balance inquiries, transfer instructions, and content navigation.
  • Develop onboarding processes and communication guidelines to ensure seamless adoption and consistent user experience.
  • Achieve high user engagement with the voice assistant, aiming for substantial interaction volume shortly after launch.
  • Expand the voice assistant's capabilities and improve assistance for visually impaired customers, with targeted performance metrics.

Core Functional Specifications for the Voice Assistant System

  • Natural language processing for understanding and responding to user queries.
  • Predefined dialogue models for common banking tasks such as balance checking, transfer execution, and account history retrieval.
  • Voice onboarding process including assistant presentation, activation, and user guidance.
  • Visual branding elements, including iconography and interface design components.
  • User interaction analytics and model refinement based on conversation data.
  • Accessibility support features for visually impaired users, including speech synthesis and recognition.

Preferred Technologies and Architectural Approaches

Advanced speech recognition and synthesis platforms
Natural language understanding (NLU) engines
Agile development methodology with iterative design and testing
Integration APIs for seamless backend communication

Essential System Integrations

  • Banking information systems for real-time data access (account balances, transaction history)
  • Transaction processing systems for executing transfers and payments
  • Content management systems for helpful content suggestions
  • Accessibility services for visually impaired user support

Critical Non-Functional System Characteristics

  • High scalability to support growing user interactions (targeting hundreds of thousands of conversations per month)
  • Robust performance with real-time response latency under 1 second
  • Strong security measures to protect sensitive financial data
  • High availability with 99.9% uptime
  • Compliance with accessibility standards to aid visually impaired users

Projected Business Benefits and Success Metrics

The implementation of the voice assistant is expected to significantly increase customer engagement and self-service efficiency, evidenced by over 360,000 interactions within the initial months. It will improve transaction speed, reduce support workload, and enhance accessibility, especially for visually impaired users, ultimately strengthening customer satisfaction and operational cost savings.

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