Is Big Data Helping Improve Consumer Finance?

Big data analytics is a new technology that makes it possible for businesses to collect, process, analyze and store vast amounts of varied data at ultrafast speeds.

Additionally, it can deliver valuable insights that can help improve decision-making, which make it especially useful to consumer finance companies.

Consumer lenders are required to take risks on a consistent basis, and they can use big data analytics to make better lending judgments and keep losses to a minimum.

Here is a look at how big data can help improve consumer finance.

Why Consumer Finance Companies Should Adopt Big Data Analytics

Save Time and Effort

Consumer finance companies that are still using traditional data management solutions have to spend a lot of time to perform certain data-related tasks.

For instance, it may take more than a month for them to post credit reporting updates, which include data updates, data corrections and additions of new credit references.

A big data system can help them streamline their data processes and make data easily available to their credit reporting teams, allowing them to complete their tasks much faster.

Additionally, it enables them to improve underwriting, offer paperless loan applications and speed up their lending processes.

Reduce Risks

One of the main reasons why big data analytics is seeing rapid adoption in the consumer finance industry is because of its ability to facilitate greater accuracy in the evaluation of loan applicants' creditworthiness, which can result in significantly lower lending risks.

According to an article entitled "How Big Data Can Transform Consumer Finance", lenders traditionally use 10 to 15 data points in FICO scores to determine their customers' creditworthiness, but these data points may not be sufficient to enable them to assess credit risks accurately.

Big data makes it possible for them to collect consumer data from many sources and discover hidden patterns and insights that give them a better idea of their customers' tendency or ability to repay their loans.

With big data analytics, consumer finance companies can perform a more detailed analysis of their customers' credit risk based on their behaviors and lifestyles.

For instance, two consumer finance companies, Earnest and Affirm, used big data to find out that people who keep the same mobile phone number a long time are more likely to repay their loans, and people who fill out a form using all capital letters are probably higher-risk borrowers.

Other Benefits

Big data analytics can be useful to consumer finance companies in many other ways:

• Spread risk more broadly across industries and geographical locations.

• Reduce costs of acquisitions while expanding geographical footprints.

• Develop better products and strategies by gaining a better understanding of consumer needs and preferences.

• Provide personalized customer service.

Many experts believe that big data analytics is the future of credit risk evaluation.

Consumer finance companies can take advantage of this technology to expand their customer bases, offer a wider variety of products and boost their profits, while minimizing their risks.