Smart Data Emphasizes Quality, Not Quantity

March 8th, 2017

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International Data Corp. (IDC) suggests that worldwide revenues for big data and business analytics will grow from $130 billion in 2016 to more than $203 billion in 2020. The commercial interest in data comes as no surprise given the immense role it plays in facilitating innovation in the financial services industry and beyond. After all, for banks of any size, data is at the core of their vital business decisions. It enables the appropriate risk assessment of every financial operation and allows banks to accurately estimate the creditworthiness of existing and potential customers, among other things.

The value of data, however, has long been correlated with its quantity rather than quality, laying a foundation for big data analytic tools and intensive data generation in relationships between companies and consumers. While we can't deny the value of such an approach in displaying major industry trends and assessing customer groups on a general level, financial technology startups nowadays are proving that innovation in the financial services industry will likely come from a smart use of more limited, but higher quality data rather than its scale. In addition, given the diversity of sources and ever-accelerating speed of data generation, it becomes more difficult to drive meaningful insights.

Smart Data’s Value as Raw Material
Smart data represents a more sophisticated approach to data collection and analysis, focusing on meaningful pieces of information for more accurate decisions. Coupled with advanced capabilities of AI and machine learning, smart data presents an opportunity for startups to efficiently derive deeper insights from limited, but relevant data points. Professionals from Siemens and an increasing number of organizations across industries believe that smart data is more important than big data. Moreover, in the future, the most important raw material will be smart data.

For banks, smart data represents an opportunity to change the way a prospective customer’s creditworthiness is assessed, hence, a chance to expand credit to new groups of population that have previously been overlooked. In fact, financial inclusion starts with the use of smart data. While national financial institutions are looking for reasons to deny someone of access to financial services, tech companies like Smart Token Chain, BanQu and others are looking for reasons to expand connectivity and open new opportunities for those excluded from the financial system. Those companies aim to leverage a different set of records for inclusive growth and a better tomorrow.

The Anatomy of Smart Data
Mike Mondelli, senior vice president of TransUnion Alternative Data Services, listed property, tax, deed records, checking and debit account management, payday lending information, address stability and club subscriptions as some of the sources for alternative data. As he emphasized, “These alternative data sources have proven to accurately score more than 90 percent of applicants who otherwise would be returned as no-hit or thin-file by traditional models.”

Other alternative sources of data used by technology companies include web search history, phone usage, social media and more. Sources can be combined into clusters, which some professionals distinguish as traditional, social and online.


Source: Forbes, LetsTalkPayments.com

The data sources emphasized above are certainly not exhaustive and their combination can vary depending on the goal and availability. In any case, the goal is to find the most relevant, even though limited, data that corresponds with the goal of its use. Fortunately, there is a variety of fintech companies leveraging the benefits of alternative data for inclusive initiatives, credit extension and more. Such examples include ZestFinance, Affirm, LendUp—all of which use data from sources such as social media, online behavior and data brokers to determine the creditworthiness of tens of thousands of U.S. consumers who don’t have access to loans.

Companies like Lenddo, FriendlyScore and ModernLend use non-traditional data to provide credit scoring and verification along with basic financial services. Those companies are creating alternative ways to indicate creditworthiness rather than relying on traditional FICO scores. For banks, such companies open up opportunities to expand their customer base without compromising their financial returns and security, while leveraging technological advancements for adopting innovative ideas and enhancing community resilience.

emesropyan

Elena Mesropyan is a market research analyst at LetsTalkPayments.com. She is a research professional with a background in social sciences and extensive experience in consumer behavior studies and marketing analytics.