An explosion of information has transformed the world around us. Big data has evolved as an industry in its own right and has had a tremendous impact on many vertical industries, including consumer lending.
As the timeless saying goes, “Money never sleeps.” And, consequently, neither does the massive amount of data that forms the basis of consumer credit performance. Data is at the heart of all lending decisions, and in 2016 the river of credit information runs deeper and wider as computing and cloud platforms have managed to gather and store massive volumes of data.
With new players entering the lending marketplace and applications driving engagement, the market is dynamic and evolving. Likewise, so are consumer behaviors and preferences. Today, people are more mobile, have the luxury of expanded choices in financial institutions, and can research many more financing services and products.
Traditionally, a record of historical credit data has enabled financial institutions to better understand the market and the changing trends in consumer behavior, preferences, and payment patterns. These insights allow institutions to have higher confidence in their decision making, giving them the ability to better satisfy consumer needs both profitably and sustainably. In general, the greater depth of historical data that a lender has, the better insights it has regarding anticipated risks. These insights are key to making daily business decisions.
Today, big data has provided the financial industry with what it never had before: context. With big data, lenders are able to get a much better and more precise understanding of the most current consumer behavior. And the industry is noticing. According to a recent IDC report, worldwide revenues for big data and business analytics will grow from nearly $122 billion in 2015 to more than $187 billion in 2019, with $22.1 billion of that going toward the banking industry.
One of the biggest benefits that big data provides lenders is the ability to aggregate data, which reduces the time it takes to query large sets of data. This subset of data provides lenders with the opportunity to track consumer actions to help identify important factors, such as overall risk levels, and to mitigate losses through early intervention.
Traditionally, lenders have considered past payment behavior a key indicator to predict future likelihood to pay. However, the depth and breadth of the consumer credit file (e.g., credit history and utilization across products ) and the incorporation of alternative data sources such as utility payments, payday loan, and checking account performance have significantly increased the ability to accurately predict payment behavior.
Moving Forward with Big Data
One of the biggest data challenges that financial institutions face is plowing through the massive amount of data that already exists without having to have specialized teams in place that can extract the value in a timely fashion. The inability to get to the heart of the data quickly and easily means leaving volumes of data untouched and, more importantly, leaving valuable insights behind.
Financial institutions increasingly are demanding more advanced analytics tools to better understand customer needs and foster sustainable growth. So much so that Aite Group estimates that 77 percent of bank executives plan near-term investment in big data analysis tools. Several forces are increasing market pressure and driving this demand, including changing consumer preferences, new market entrants, and heightened regulatory oversight. Financial institutions now require data, perspective, and greater control to take action in their respective businesses.
And these changes come with their own challenges. Financial organizations face the same types of problems that hinder success in their business intelligence investments: challenges in accessing needed data, inability to gain valuable insights and perspective from data, and the governance process.
But new financial tools are being introduced in the market and are positioned to solve these challenges. These tools combine data, knowledge, and technology, and are designed to help break the barriers for big data and analytical capabilities so that customers can better define, deploy, and monitor strategies.
These new solutions are delivering unique value propositions that provide lenders with the context, flexibility, and speed they need to make better and more-informed decisions. From the context perspective, lenders can now do the following:
- Conduct analysis based on a full file of anonymized national consumer credit data versus sample data
- Access seven years’ worth of historical, anonymized data to help better understand market trends and consumers behavior
- Look across all lines of business in one solution to have a more holistic and integrated market understanding versus a siloed approach
- See a more comprehensive view of consumer behavior versus just product performance
- Compare performance against peer and industry benchmarks.
When it comes to greater flexibility, new advances in technology empower users to access information 24/7 with any device (computer, tablet, or mobile), integrate additional third-party data to enrich the power of their big data, and interact with a user interface that helps them get answers to their key business questions.
One of the biggest benefits being delivered today to help lenders make good use of the massive volumes of data they have is advancements in speed. Lenders now can query data results and access desired business insights within seconds – a process that took months previously – and drive decisions based on the most up-to-date information, as data is updated monthly and automatically.
Competing in an increasingly dynamic market requires better insights within and outside of an organization’s walls to better understand credit performance and competitive trends. With so much data for institutions to both manage and measure, the industry must better meet the needs of lenders that are seeking to pull actionable insights from their data. And as big data becomes more manageable, available, and powerful, the strategies and tools that mine these insights must be equal to the task.
Paul Siegfried is the senior vice president and credit card business leader for TransUnion. He leads the financial services card vertical and is charged with product development, business development, and market strategy.
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