TRANSFORMING CUSTOMER RETENTION IN FINTECH INDUSTRY THROUGH PREDICTIVE ANALYTICS AND MACHINE LEARNING

Аннотация

INTRODUCTION with financial services, fintech encompasses a In recent years, the fintech industry has wide array of offerings, including digital banking, experienced rapid growth, driven by technological peer-to-peer lending, robo-advisory services, and advancements and evolving consumer payment processing. As of 2023, the global fintech expectations. Fintech companies offer innovative market was valued at approximately $309 billion financial services, such as digital banking, and is projected to reach around $1.5 trillion by investment platforms, and payment solutions, 2030, according to a report by Fortune Business catering to the needs of a tech-savvy customer Insights. This remarkable growth is largely base. However, as competition intensifies, attributed to advancements in digital technology, customer retention has emerged as a critical increasing smartphone penetration, and a growing challenge for these companies. According to a consumer preference for online financial solutions. study by Ransom (2021), acquiring a new Moreover, the COVID-19 pandemic accelerated the customer can cost five times more than retaining adoption of digital financial services, as consumers an existing one, making it imperative for fintech sought contactless transactions and remote organizations to focus on strategies that enhance banking options. customer loyalty. The financial technology (fintech) sector has experienced unprecedented Customer churn, defined as the rate at which growth in recent years, fundamentally customers discontinue their relationship with a transforming how individuals and businesses company, poses significant threats to profitability access and manage financial services. and growth in the fintech sector. The annual churn Characterized by the integration of technology rate for fintech companies can be as high as 20- https://www.theamericanjournals.com/index.php/tajet 151 THE USA JOURNALS THE AMERICAN JOURNAL OF ENGINEERING AND TECHNOLOGY (ISSN – 2689-0984) VOLUME 06 ISSUE10 30%, according to the 2022 report by Accenture. communication and tailored product offerings, Understanding the factors influencing customer significantly enhance customer satisfaction and retention is essential for developing effective retention rates. Additionally, the importance of strategies to mitigate churn and foster long-term understanding customer behavior cannot be relationships with clients. In this context, machine overstated. Insights derived from customer learning has emerged as a powerful tool for interactions and preferences allow fintech analyzing customer behavior and predicting churn, companies to customize their services and respond enabling organizations to implement proactive proactively to customer needs. measures to retain valuable customers (Bashir et In this context, machine learning has emerged as a al., 2021). powerful tool for predicting customer behavior Despite the promising landscape, fintech and enhancing retention strategies. By analyzing companies face significant challenges, particularly vast amounts of customer data, machine learning concerning customer retention. With the algorithms can identify patterns that signal burgeoning number of competitors in the market, potential churn, enabling organizations to retaining customers has become a daunting task intervene before customers decide to leave. for fintech firms. The competitive nature of the Numerous studies have highlighted the industry means that customers have numerous effectiveness of machine learning techniques in alternatives at their disposal, leading to a predicting churn across various industries, phenomenon known as customer churn, which including banking and telecommunications. For refers to the loss of clients or customers over a instance, Bashir et al. (2021) demonstrated the specified period. According to research by utility of random forest models in predicting Accenture, the average churn rate in the fintech customer churn in a mobile banking app, achieving sector can be as high as 20-30% annually, a impressive accuracy rates. These findings suggest statistic that underscores the critical need for that leveraging machine learning can provide effective retention strategies. Furthermore, the fintech companies with actionable insights to cost of acquiring a new customer can be five times refine their retention strategies. greater than that of retaining an existing one The application of machine learning in churn (Ransom, 2021). As such, understanding the prediction goes beyond merely identifying at-risk factors that drive customer loyalty and customers; it also helps in understanding the implementing strategies to enhance customer underlying factors that contribute to churn. retention is essential for the long-term success of Feature importance analysis can reveal which fintech companies. customer attributes—such as transaction Customer retention is influenced by various frequency, account balance, and engagement factors, including