The
emergence of online lending platforms (online loans) has revolutionized the
credit landscape by providing easy access to loans. However, concerns about
unethical practices, data privacy, and high interest rates have sparked mixed
reactions from the public. This study explores public sentiment towards online
lending platforms using a data-driven sentiment analysis approach. This
research conducts sentiment analysis using RoBERTa and VADER base sentiment
model to classify consumer sentiment into positive, neutral, and negative
categories. Data collected from fintech lending application reviews and online
forums highlights key consumer concerns and drivers of satisfaction. The study
aims to provide actionable insights for regulators and online lending providers
to inform prioritization of interventions and enhance customer trust.
