The finance industry has seen significant losses due to fraud, with nearly $7.7 billion lost by US consumers in 2024. Financial data analytics can help prevent such losses by detecting fraud in real-time, predicting market trends, and offering personalized services. Banks and other financial institutions are leveraging advanced analytics to revolutionize their operations and customer experiences, including applications like fraud detection, customer experience personalization, credit risk modeling, predictive maintenance, parametric insurance, claims management, investment decision-making, and predictive financial modeling. Data analytics has become a cornerstone for driving innovation and efficiency in the finance industry, enabling financial institutions to innovate, stay competitive, and deliver superior value to their stakeholders. Building a robust and secure financial data analytics setup requires a strategic approach that encompasses technology, processes, and people, including defining goals, identifying data sources, establishing data governance, choosing tools, building a skilled team, implementing security measures, and fostering a data-driven culture. Data quality is also critical in the success of financial data analytics, with aspects like accuracy, completeness, timeliness, consistency, and relevance to consider. Acceldata is a leading provider of data observability solutions that help financial institutions ensure data quality and reliability for their analytics initiatives.