Big data solutions are essential to the Finance Industry for the growth of businesses. It allows companies to obtain a thorough understanding of their consumers and make decisions based on real-time data.
The finance and insurance sector is an intensively data-driven industry, managing large quantities of customer data. The advent of big data in financial services provides a personalized approach to the customer experience and efficiently analyses the behavior of the customer, this, in turn, can be used for crime detection and the targeted marketing approach.
Here are some of the big data use cases in finance industry:
Customer Segment Analysis:
Financial institutions can define better customer segments (distinct categories based on customer behavior and transactions based on demographic characteristics) using big data algorithms by collecting and analyzing customer transactions, interactions, and activity data.
Fraud Detection:
Big data is a powerful tool to combat financial fraud in the credit card industry. Financial institutions can apply data analytics to significantly enhance fraud detection.
Credit Risk Assessment:
Big Data solutions enable financial institutions to analyze data collected from customer deposits, credit card purchase history, payment patterns, etc. to construct an in-depth review of the customer and thereby provide an accurate credit score.
360-Degree Customer Service:
Financial institutions need to examine the structured and unstructured data, such as customer reviews, emails, calls, social media profiles, forums, online interactions, etc. and respond accordingly with the right products and services, this is the key to customer retention.
Recommend Investment and equity options:
Through the application of big data platforms, the stock market portfolio managers and traders can gather and process a substantial volume of unstructured (company news, social media sentiment, and event data) and structured data, to identify the best investment opportunities which predict price moment, turning points of the portfolio, sentiment, etc.
Product recommendations based on customer activity:
Big Data tools and platforms can be operated to understand customer transaction activity, specifically, the behavior and usage, which is shown to recommend new products. For example, a customer who frequently travels can obtain travel rewards on credit card through banks.
DataKare Solutions has expertise in developing big data applications on financial data, which provides a foundation for advanced analytics, data mining, and integration. DataKare uses the latest big data technologies stack to build a data pipeline and an analytical engine in a distributed parallel environment.
