The Role of Big Data in Financing Projects

The Role of Big Data in Financing Projects

Big Data is a new information technology concept that refers to collection and analysis of large amounts of data. Due to increased computing power and low cost of computing, Big Data has become more economical and feasible. Here is the role of Big Data in financing projects:

1. Auto Insurance

Since the 1980s, the Progressive Insurance founder envisioned a day when hard data regarding individual holders of car insurance policies, such as their driving habits could be collected for analysis. This could result in precise risk assessment and risk measurement, and hence more accurate premium setting. By 2010, the requisite technology for collecting data had been made available, and more than the million clients have given their consent for installation of black boxes to track their driving habits such as how suddenly they normally break and how fast they

usually drive.

2. Consumer Credit

LendUp uses social network analysis drawn from numerous sources to add to native FICO credit ratings to make lending decisions. For instance, LendUp wants to know if a prospective borrower has changed phone numbers often, which may show a bad risk. The firm also believes that people’s online interactions with their friends provide powerful clues regarding their riskiness as borrowers. Those who provide the most active and strongest community ties and social connections seem to be the best risks. Hence, prospective borrowers are asked to avail their Facebook accounts to the company for analysis. Whether you want an education loan or pool financing, banks will use Big Data to determine your legibility.

CapitalOne, a credit card giant, became a big finance firm in the 1990s typically through the use of advanced data collection and techniques for analysis to get prospects for its credit cards.

3. MortgaLendingge

JPMorgan Chase is utilizing Big Data analysis to obtain acceptable sales prices for commercial properties and homes that have been repossessed due to default mortgages. The idea is to evaluate local property markets and economic conditions to determine sales prices that are reasonable before the default of the mortgage loans. Accurate setting of these mortgage prices could minimize the local property market’s disruption from default, repossession and sale by the financial institution. Moreover, the period which the financial institution has to hold the property before making a sale reduces.

Additionally, Quantfind is a firm that has offered technical expertise to the CIA with the aim of uncovering false identities used by terrorist suspects. The same firm has been in meetings with JPMorgan Chase to discuss how its technology can be applied in credit business in areas like marketing and credit evaluation.

4. Customer Segmentation

Big Data offer banks comprehensive insights into the spending patterns and habits of the clients, making the task of ascertaining their wants and needs simple. The ability to trace and track each customer transaction enables the banks to segment their customers based on various parameters such as net worth, regularly accessed services, and preferred credit card expenditures. Customer segmentation will then benefit the bank by aiding them to target their

customers with relatable marketing promotions that are designed to meet their requirements.

5. Personalized Product Offerings

Customer segmentation is used to form and deliver new plans and schemes, aimed directly at the particular requirements of the clients. By analyzing present and past costs and transactions, a financial institution can better understand how to obtain the highest rate of response from their customers. Creation of customized product offerings will cater to an untapped gap of personalized services that enable financial institutions to establish more meaningful customer relationships.

6. Fraud Detection

Fraud is one of the most significant problems in the financial industry. However, Big Data enables banks to ensure that there are no unauthorized transactions, offering a level of security and safety that improves the industry’s security standard.

7. Crop Insurance

Various financial institutions underwrite crop insurance for farmers. The firms use Big Data to run massive simulations in predicting weather patterns in the long-run and set premiums.


Banks, insurance firms, credit firms, and other financial institutions are enjoying multiple benefits, thanks to Big Data.