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Polygence Scholar2024
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Nihaal Oberoi

Class of 2025Redmond, Washington

About

Hello, my name is Nihaal Oberoi, I am a junior at Eastside Prep (located in Kirkland, Washington). I enjoy playing sports such as golf, basketball, and soccer, and I love working with other people on projects whether its in academic or athletic pursuit.

Projects

  • "How does the integration of AI in banking affect customer trust and the traditional relationship-based nature of banking?" with mentor Oderachukwu (Nov. 2, 2024)

Project Portfolio

How does the integration of AI in banking affect customer trust and the traditional relationship-based nature of banking?

Started July 1, 2024

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Abstract or project description

Background:

Traditional banking has historically been based on personal relationships and face-to-face interactions. Bankers and clients often built relationships over time, which facilitated trust and personalized service. With the advent of AI, these dynamics are shifting as more interactions become automated and data driven.

Key Areas of Impact

  1. Shift from Personal to Automated Interactions

Analysis: Investigate how AI tools like chatbots and virtual assistants, changes the interaction model between banks and their customers. For many customers, especially younger demographics, these tools can offer convenience and immediacy that enhance their banking experience. However, for other segments, particularly older customers or those accustomed to traditional banking, this shift might result in a perceived loss of personal touch and diminished trust.

Research Focus: Surveys and case studies on customer satisfaction and trust levels before and after the implementation of AI services in banking.

  1. Transparency and Trust in AI Decisions

Analysis: How the opacity of some AI systems can affect trust. Decisions made by AI, such as credit scoring or fraud detection, can sometimes lack easy-to-understand explanations, which is a change from decisions made by human bankers that could be discussed and rationalized directly with the client.

Research Focus: Examination of the explainability of AI in banking and its effects on customer trust, including regulatory and ethical considerations.

  1. Data Privacy and Security

Analysis: With AI, banks can collect and analyze vast amounts of data to enhance customer service and tailor products. However, this can also raise concerns about data privacy and security—key factors in customer trust.

Research Focus: Case studies on data breaches or privacy concerns in AI-integrated banking systems and their impact on customer trust.

  1. Customization vs. Standardization

Analysis: AI enables highly personalized banking services based on individual customer data. While this can improve service delivery and customer satisfaction, it also raises questions about standardization and fairness.

Research Focus: Investigate how AI-driven personalization in banking affects customer perceptions of fairness and trust.

  1. Impact on Bank Employees and Customer Relations

Analysis: Consider how the role of bank employees changes with AI integration. While AI can handle routine queries and tasks, complex issues and high-value transactions may still require human intervention.

Research Focus: Analysis of how the changing roles of bank employees influence customer relationships and trust, particularly in complex customer service scenarios.

Methodological Approaches

Surveys and Interviews: Gather data from banking customers and staff to understand their perceptions of AI in banking.

Comparative Studies: Compare customer trust and relationship metrics from before and after AI implementation within banks.

Case Studies: Research specific banks that have integrated AI extensively into their operations.