Big Data In Financial Services: What You Need To Know

Big Data In Financial Services What You Need To Know
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Big data is a collection of data from multiple sources, gathered for analysis and developing insights. Financial services can utilize big data to gain knowledge about the market and customers at the same time. The jumble of data can be reduced for analysis based on filters that suit the demand.

Big data is defined with six Vs in the industry. They are volume, velocity, variety, veracity, value, and variability. Big data provides abundant data for the financial industry that can boost business revenue and growth. It helps financial institutions to:

  • Forecast financial trends
  • Analyze risks
  • Automate tasks
  • Foster inclusivity

When it comes to business applications, big data offer a range of services and capabilities to financial institutions. Some of them are:

  1. Consumer analytics and insights for insurance companies
  2. Real-time analytics and marketing
  3. Risk assessment and management
  4. Fraud detection and prevention
  5. Customer segmentation and targeted marketing

Let us learn more about the application of big data in the financial industry.

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Consumer analytics and insights

Data analytics based on big data can map the financial journey of consumers without missing anything. Each consumer leaves a digital trail that can be collected into data and stored. The insights gained from such information helps the finance companies to determine their capabilities for loans, mortgage, buying, selling, investment, or insurance; avoids risks in return.

Real-time analytics and marketing

Data science is capable of real-time analysis of data. It enables the companies to respond quickly to any financial changes in the market. It enables the industry leaders to understand the consumer mentality and trends, responding with the corresponding marketing materials. Geofencing, geotargeting, and beaconing can assess this data and help the marketing teams to win customers.

Risk assessment and management

The more varied the customer base is, the more risks a finance company faces. Risk assessment can’t be completed with one time data analysis. Machine learning algorithms and artificial intelligence work together with big data to gain insights. The proper utilization of technology can help in better risk assessment and management of risks.

Fraud detection and prevention

Financial frauds are unavoidable in the finance sector. Big data gathers information on customers and users of the service and track or monitor the activity patterns with algorithms. Filtered data on behavioral patterns can determine if there are any abnormal behaviors that can lead to frauds or are fraudulent.

Customer segmentation and targeted marketing

Each company has their own selection of preferred customers. Big data can help the companies select a set of leads based on the selection criterions of the company from the target audience. It allows the firm to carry out customer segmentation and promote productive targeted marketing.

What the future holds?

The usage of big data in the finance sector does not end here. Other use cases include:

  • Predictive analytics
  • Future planning
  • Financial market analysis
  • Investment analysis

As technology keeps advancing more and more human analytics part will be replaced by machine. We have yet to see a system that can analyze the big data as a whole for any purposes. 

About the author

Melwin Joy

Passionate and professional writer with lots of writing experience in handling articles in multiple industries and verticals. I like photography and writing.