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An Investigation of Big Data in Financial Fraud Risk Mitigation: A Case Study of Fintech Startups in Kaduna State

  • Project Research
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  • Abstract : Available
  • Table of Content: Available
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  • NGN 5000

Background of the Study

The rise of financial technology (fintech) startups has transformed the financial services landscape, offering innovative solutions for transactions, lending, and investment. However, this digital shift has also increased vulnerabilities to financial fraud, posing significant risks to fintech operations and customer trust. Big data technologies offer a robust solution for fraud risk mitigation by enabling real-time detection, predictive analytics, and pattern recognition across vast datasets (Yadav et al., 2024).

In Kaduna State, the fintech sector has grown rapidly, driven by increasing internet penetration and demand for digital financial services. However, many startups face challenges in combating fraud due to limited resources and reliance on traditional methods. This study explores the application of big data in mitigating financial fraud risks among fintech startups in Kaduna State.

Statement of the Problem

Fraudulent activities in the fintech sector undermine customer confidence and lead to financial losses. Fintech startups in Kaduna State are particularly susceptible due to insufficient fraud detection mechanisms and limited adoption of big data technologies. While big data analytics provides advanced tools for identifying and mitigating fraud, its implementation remains low due to cost, technical expertise, and infrastructural constraints (Aliyu & Danjuma, 2023). This study investigates the role of big data in addressing these challenges.

Objectives of the Study

  1. To assess the adoption level of big data technologies for fraud risk mitigation in fintech startups in Kaduna State.

  2. To evaluate the impact of big data on reducing fraud incidents and financial losses.

  3. To identify challenges faced by fintech startups in implementing big data solutions for fraud detection.

Research Questions

  1. What is the adoption level of big data technologies for fraud risk mitigation in fintech startups in Kaduna State?

  2. How does big data impact the reduction of fraud incidents and financial losses?

  3. What challenges hinder the implementation of big data solutions in fintech startups?

Research Hypotheses

  1. There is no significant relationship between big data adoption and fraud risk mitigation in fintech startups.

  2. Big data does not significantly reduce financial fraud incidents and losses.

  3. Challenges to big data implementation are not significant in fintech startups in Kaduna State.

Scope and Limitations of the Study

The study focuses on fintech startups in Kaduna State, analyzing their use of big data technologies for fraud detection. Limitations include variations in technology adoption and the availability of fraud-related data for analysis.

Definitions of Terms

  • Big Data: Large and complex datasets that require advanced analytics to uncover patterns, trends, and insights.

  • Fraud Risk Mitigation: Strategies and technologies used to reduce the likelihood and impact of fraudulent activities.

  • Fintech Startups: Emerging companies leveraging technology to provide financial services.





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