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How to Benefit from Big Data in the Financial Industry

October 01, 2017

How to Benefit from Big Data in the Financial Industry

The financial services industry thrives on market intelligence. Any insight that can provide a competitive advantage is gold to financial professionals. If you can demonstrate to financial professionals how to benefit from big data you will be able to make a lasting impression, and land an ongoing customer contract.

Technology is driving financial service firms to improve in multiple areas – customer data, risk measurement, market expectations, and operating efficiency. Showing financial firms how to benefit from big data in each of these areas will make your services invaluable.

As reported by Price Waterhouse Coopers, the big data market is currently $5.12 billion and growing. The market is expected to hit $32.1 billion by 2015 and $53.4 billion by 2017. There are 2.5 quintillion bytes of data produced daily, and 62 percent of companies believe that data can give them a competitive edge.

However, according to Deloitte 75 percent of executives polled from 500 companies say they are wasting more than half of the data they have stored. Put another way, 80 percent of their market insight is being generated by 20 percent of the data available. One immediate way to show financial customers how to benefit from big data is to demonstrate how to get more value from the data they already have.

Before you start demonstrating how to benefit from big data, be sure your financial prospects understand what big data is and the role it can play in their business.

The Role of Big Data in Financial Services

There is a lot of confusion about what big data truly is. Financial institutions often see big data as a technological hurdle rather than a valuable business tool. Their business generates more data than they can process but senior management can’t yet grasp how to benefit from big data. Financial professionals also have differing views of how to benefit from big data; some see it only as a means to improve operations ignoring its potential to deliver market insight.

Your first task is to educate the financial customer about how to benefit from big data. Big data can play a valuable role in three specific areas:

  1. Monetizing customer data.
  2. Developing predictive models for transactions and operations.
  3. Optimizing risk management and regulatory reporting.

Creating More Customer Value

The IBM Institute of Business Value reports that 55 percent of banking and financial market executives say their top big data objectives focus on customer-centric objectives (as opposed to product-centric). The customer is the focal point for big data insights, operations, technology, and systems.

Institutions are using big data to create a single view of the customer, enhancing the customer experience, which in turn improves brand value and increases revenues. Customer information is already stored in the institution’s servers. Using big data analytics reveals more about customer needs and how to create better services and products.

Big data analytics also are valuable for developing customer risk analyses. Big data can analyze individual profiles, spending habits, and other metrics to develop a risk management profile.

Big data also keeps financial institutions on track with customer satisfaction. By adding unstructured data sources such as customer service calls and social media activity, financial institutions can gauge customer satisfaction and address problems before they lose business.

Improving Transactions and Operations

Big data analytics also can reveal what products and services appeal most to customers. Social media data, for example, can be analyzed to reveal sentiment about new services or financial products. Many financial institutions try out new products on social media to determine pre-launch attitudes and refine their marketing programs.

To improve transactions, trading institutions are using historical market data to develop predictive models, using big data to develop market forecasts. Combining market and transaction data and reference information from multiple sources also can inform trading for complex securities.

Facilitating Risk Management and Regulations

Increased regulatory scrutiny has changed the manner in which financial institutions approach risk. Now institutions have to manage risk across multiple risk dimensions. Big data analytics makes it possible to assess real-time data streams, such as news, research, social media, audio, and video, to track market events and more closely manage risk.

For regulatory reporting, big data also makes it possible to combine regulatory data with documents, contracts, and supporting materials for better regulatory risk management.

These are some of the most common use cases you can use to demonstrate to financial services firms how to benefit from big data. Each financial prospect will have a different understanding of what big data is, and different points of pain. If you can demonstrate how big data can meet their needs you’ll be well on your way to landing a new and long-lasting customer.