Big data plays a crucial role in financial technology (FinTech) and its impact on financial inclusion. This study explores how big data contributes to FinTech and its implications for financial inclusion. Through a comprehensive literature review, the study highlights how big data enables the development of new financial products and services, enhances risk management, and improves operational efficiency, thereby promoting financial inclusion. The ability of big data to provide insights into customer behavior is a key driver for creating inclusive financial services. However, challenges such as data privacy, security, and ethical algorithmic practices are also identified. The research provides valuable insights for policymakers, regulators, and industry practitioners, suggesting the need for balanced regulatory frameworks to ethically and responsibly harness big data's potential. The study underscores the transformative power of big data in FinTech, indicating a pathway toward a more inclusive financial ecosystem. Big data refers to the collection, storage, and analysis of large and complex datasets. It can come from various sources, including social media, sensors, and transactional systems, and can be structured, semi-structured, or unstructured. The volume, velocity, and variety of big data make it challenging to process using traditional data processing techniques. To handle these challenges, organizations use technologies like Hadoop, Spark, and NoSQL databases. Despite its benefits, big data poses challenges such as data privacy and security, the need for skilled personnel, and compliance with regulations. Big data is essential for risk management and compliance in FinTech. It enables the identification of potential risks and the development of strategies to mitigate them. By analyzing vast amounts of data, FinTech companies can detect fraudulent activities, assess creditworthiness, and improve decision-making. Big data also plays a significant role in the development of new technologies such as blockchain and artificial intelligence, which can enhance decision-making and automate operations. Big data is used to create personalized financial products and services, such as customized investment portfolios and tailored insurance policies. It allows for more accurate predictions and better risk management. Additionally, big data can help in customer segmentation, enabling FinTech companies to better understand and meet the needs of different customer groups. This leads to improved customer satisfaction and loyalty. The study also discusses the role of big data in financial inclusion, highlighting how it can help underbanked populations by providing access to financial services. It emphasizes the importance of ethical use of big data and the need for regulatory frameworks to ensure responsible and ethical use. The research concludes that big data has the potential to significantly enhance financial inclusion in the financial sector.Big data plays a crucial role in financial technology (FinTech) and its impact on financial inclusion. This study explores how big data contributes to FinTech and its implications for financial inclusion. Through a comprehensive literature review, the study highlights how big data enables the development of new financial products and services, enhances risk management, and improves operational efficiency, thereby promoting financial inclusion. The ability of big data to provide insights into customer behavior is a key driver for creating inclusive financial services. However, challenges such as data privacy, security, and ethical algorithmic practices are also identified. The research provides valuable insights for policymakers, regulators, and industry practitioners, suggesting the need for balanced regulatory frameworks to ethically and responsibly harness big data's potential. The study underscores the transformative power of big data in FinTech, indicating a pathway toward a more inclusive financial ecosystem. Big data refers to the collection, storage, and analysis of large and complex datasets. It can come from various sources, including social media, sensors, and transactional systems, and can be structured, semi-structured, or unstructured. The volume, velocity, and variety of big data make it challenging to process using traditional data processing techniques. To handle these challenges, organizations use technologies like Hadoop, Spark, and NoSQL databases. Despite its benefits, big data poses challenges such as data privacy and security, the need for skilled personnel, and compliance with regulations. Big data is essential for risk management and compliance in FinTech. It enables the identification of potential risks and the development of strategies to mitigate them. By analyzing vast amounts of data, FinTech companies can detect fraudulent activities, assess creditworthiness, and improve decision-making. Big data also plays a significant role in the development of new technologies such as blockchain and artificial intelligence, which can enhance decision-making and automate operations. Big data is used to create personalized financial products and services, such as customized investment portfolios and tailored insurance policies. It allows for more accurate predictions and better risk management. Additionally, big data can help in customer segmentation, enabling FinTech companies to better understand and meet the needs of different customer groups. This leads to improved customer satisfaction and loyalty. The study also discusses the role of big data in financial inclusion, highlighting how it can help underbanked populations by providing access to financial services. It emphasizes the importance of ethical use of big data and the need for regulatory frameworks to ensure responsible and ethical use. The research concludes that big data has the potential to significantly enhance financial inclusion in the financial sector.