Impact of AI-Driven Solutions in Financial Technology on Service Delivery: A Study of Fraud Detection, Credit Risk Assessment, and Personalized Advisory Systems in Insurance Firms in Lagos State

Anchored on the Resource-Based View (RBV), this study examined the impact of AI-driven solutions in financial technology on service delivery, focusing on fraud detection, credit risk assessment, and personalized advisory systems in seven insurance firms in Lagos State. Using a quantitative approach, data were collected from 304 respondents selected through stratified random sampling. Descriptive statistics and regression analysis were employed to test the hypotheses.
Findings revealed that AI-driven fraud detection (β = 0.352, p < 0.01), AI-powered credit risk assessment (β = 0.294, p < 0.01), and AI-enabled personalized advisory systems (β = 0.301, p < 0.01) each exerted significant positive effects on service delivery. Descriptive results showed high mean scores across variables (≥ 4.0), indicating strong consensus on AI’s operational benefits.
Theoretically, the study establishes AI-driven technologies as strategic resources that create competitive advantage in service performance, consistent with RBV. Practically, it underscores the importance of investing in data infrastructure, staff capacity development, and regulatory alignment to ensure ethical and effective AI adoption.

AI-driven solutions, Resource-Based View (RBV), FinTech, Service delivery

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