Banking, Financial Services, Lending, and Data Science: Some of Our Clients and How We Can Help
The banking and finance industry is turning to data science to better understand their customers, build predictive models and simulate market events, and fight fraud. Using data science in the banking industry is a necessity to keep up with the fierce market competition, while ensuring that predictive and prescriptive models do not unfairly marginalize consumers.
Banking and finance companies have come to realize that big data analytics can help them use resources efficiently, improve performance, and make smart decisions. Data analytics, predictive modeling, and tailored algorithms offer the chance to develop customized products, run relevant campaigns and build products to suit customer segments, track trends, monitor product launches and enhance brand perception, understand real time analytics, and predict supply and demand of financial service products and services.
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Banking & Financial Services: Questions Data Science and Consumer Research Can Answer
Can we build predictive models to accurately predict loan volume by location and market segment?
Can predictive analytics effectively detect and prevent credit card fraud?
What can we learn about our customer behaviors, interactions, and preferences from our big data we have collected from our customers?
How can we effectively manage risk?
Can we use the behavioral, demographic, and historical purchase data to predict how customers will respond to a promotion, product or an offer?