Building financial capability and improving access to credit is essential for economic growth in our country. This is especially true for entrepreneurs, many of whom rely on their personal consumer credit standing when applying for a loan for keeping their small businesses strong or for a capital injection to expand their operations.

Ten years ago movie night at our house would usually include a run to the video store where we would pick out a selection from the New Arrivals section, some candy, perhaps some popcorn and we would have our fingers crossed the selection was a good one. Nowadays it’s not uncommon to find us binge watching streamed episodes of “House of Cards” or “Mad Men on weekends.” What’s even more gratifying is after watching “House of Cards” unprompted, Netflix now recommends “The Newsroom” and other shows we invariably like. How do they know we would like these shows? This is predictive marketing at work, driven by big data. Netflix has developed sophisticated propensity models around each member’s viewing habits, and the net result is a better viewing experience with the service. We make amazing entertainment discoveries every week. In business marketing propensity models will determine which prospects or customers are likely to respond to a particular offer. For example, the marketing department of a large financial institution seeking to expand their commercial small business loan portfolio, might want to segment and target commercial lending offers to a concentration of customers most likely to accept a particular offer. When applied in business, propensity models can unlock opportunities for increased profit, share of wallet and deeper engagement with prospects and customers. At Experian, in a typical propensity modeling engagement we will first meet with our customers to understand their goals and objectives. We talk first about pre-screen criteria that enable us to screen out prospects that would not fit into the criteria. A sporting equipment manufacturer would probably not sell to companies in the mining or agriculture industries, so we weed out the ones least likely to lead to a successful conversion. Our data scientists and statisticians get to work on large data sets and evaluate a number of factors. Experian will then develop a customized response model that will identify significant characteristics of responders vs. non responders and therefore will maximally differentiate responders from non responders. Since (holding other factors constant) a higher response rate is preferred, a response model can help lower the cost per response. The response model will generate a “score” that can be used to rank order the prospects base in terms of response likelihood. The response model can be used in two different ways to achieve maximum effectiveness. It can be used to optimize the number of responders for a given sized solicitation, or it may be used to minimize the number of solicitations in order to achieve a budgeted number of responders. A high response score will indicate someone who is likely to respond, as is shown graphically in Exhibits 1 and 2. This work results in a model of the ideal target to which an offer would most likely resonate with. This is called a lookalike. The marketing department at our large financial institution might start off with a large list of potential candidates to send the offer via direct mail, 1 million for example. But mailing an offer to that many people may be cost prohibitive. A propensity model can identify prospects most likely to accept the offer, so your direct mail campaign is more targeted, thereby increasing ROI. A highly targeted mailing to your ideal targets is a safer bet, and would make for a much more predictable outcome. The marketer can feel more confident mailing an offer to lookalike prospects because the chances of successful conversion are that much higher. That’s the case for Woodland Hills based ForwardLine, who have been providing alternative short-term financing to small businesses since 2003. Working with Experian Decision Analytics, ForwardLine did an analysis of their direct marketing program and determined that 22 percent of direct mail was generating 68 percent of their underwriting approvals, exposing a significant gap in wasted marketing funds. The Experian Decision Analytics team developed a custom model which enabled ForwardLine to algorithmically target lookalike prospects with a higher propensity to convert into a successful loan engagement. Michael Carlson, V.P Marketing, ForwardLine ForwardLine Vice President of Marketing, Michael Carlson is thrilled with the initial results. “Working with Experian we were not only able to improve performance, but we are able to reduce our marketing spend, while achieving the same results. We have taken our direct marketing effort from a small program that was profitable, but not meaningful in terms of generating significant volume, to working with Experian to achieve remarkable results. It’s largely why we enjoyed 20 percent growth this year.”     Best in Industry Credit Attributes Experian clients use our archived Biz AttributesSM along with collection specific data elements as independent variables for propensity model development. Experian’s Biz AttributesSM are a set of commercial bureau attribute definitions (includes several key demographic attributes as well) which are accurately developed off Experian’s Commercial BizSourceSM credit bureau. When used for response model development, Biz AttributesSM provides significant performance lift over other credit attributes. Biz AttributesSM are also effective in segmentation, as overlay to scores and policy rules definition, providing greater decisioning accuracy. Additionally, at Experian we are constantly monitoring our growing data warehouse looking for ways to develop new attributes. We live in an ever changing market place which requires us to develop new credit and demographic attributes as well as making enhancements to existing attributes. This process takes a disciplined, rigorous, and comprehensive approach based on experience guided by data intelligence. Our goal is to provide world-class service and the industry’s best practices for modeling attributes. To keep pace with market changes, new attributes are developed as new data elements become available, while raw data elements and existing attributes are monitored and managed following rigorous and comprehensive attribute governance protocols to ensure continued integrity of attributes. If you would like to learn more about propensity models, contact your Experian representative today.

In many cases, business lenders often rely on the commercial credit of the enterprise coupled with the personal credit of the business’s owner when making lending decisions. This is especially true for sole proprietorships and partnerships. To that end, regulatory action and public policy initiatives aimed at consumer credit often times can have a direct impact on commercial lenders. This blog takes a look at some of the top regulatory priorities for business lenders within the credit ecosystem.

At the recent “Future of Data-Driven Innovation” conference, Emery Simon of the Business Software Alliance noted that each day 2.5 quintillion bytes of data is gathered. How much data is that exactly? To put it into tangible terms, if this data was placed on DVD’s, 2.5 quintillion bytes would create a stack tall enough to go from Earth to the Moon.

Hello, I’m Hiq Lee, president of Experian’s Business Information Services, and I’d like to talk to you about how we are using data for good to help companies, large and small, succeed in the marketplace. At Experian, our group plays a crucial role in the big data ecosystem as an enabler of commerce and insights for the business community at large. We deliver unbiased information on more than 25 million active U.S. businesses, plus our international data capabilities, enable our customers to make more confident decisions on companies overseas. In 2012, along with Moody’s Analytics, we developed the Small Business Credit Index, which provides a unique perspective on the health of small businesses in the United States. The report contains important trends on bankruptcy rates, delinquencies, and overall payment behavior, as well as macro-economic information. This deeper look at the business landscape helps financial institutions and businesses every day to make sound lending decisions, gain key insights on business credit health and prospect for the right customer. At Experian, we are committed to delivering quality data and are strategically focused on the innovation of new and advanced products and services that enable businesses to thrive. Whether it’s analyzing millions of business credit transactions to generate industry-leading commercial credit scores and business credit reports, or safeguarding and securing millions of records to protect businesses and their customers from fraud, Experian is at the forefront of big data, driving value for our customers the world over. For Experian’s Business Information Services, using our data for good means constantly innovating and looking for ways to benefit businesses, as well as consumers and the overall economy. Related Data Is Good – Analytics Make It Great – Craig Boundy, CEO  

According to a recent United States Department of Commerce Economic Statistics and Administration report, world trade volume for goods and services is expected to increase 5.3 percent in 2015, up from 3 percent in 2013. Working with companies overseas can have a lucrative impact on your business, however, the opportunity does not come without risk. There are many potential pitfalls to expanding overseas that must be addressed in order to mitigate risk and improve profitability. Three of the major information-based hurdles that should be considered are: 1 – Availability – International data often is unavailable to credit professionals or it takes them too long to acquire. 2 – Freshness – International data is often out-of-date, increasing the chance of making inaccurate risk assessments. 3 – Consistency – Credit professionals can’t use the same analytical models across multiple geographies due to data differences. Experian makes it easy for our customers to expand into new territories through our enhanced international capabilities. We provide comprehensive insight into your international customers and vendors — both prospects and existing — that is accurate, up-to-date, easily accessible and highly actionable. This data helps you assess risk, reduce exposure to late payments and defaults, and be more competitive overall. In the below video Experian product manager, Greg Carmean discusses some of the challenges in international business engagements. Experian’s International Developed Profiles help Rubicon Project safely expand into untapped markets Rubicon Project is a technology company that automates the buying and selling of digital advertising. Their trading platform reaches a global audience of 200 million U.S. and 646 million global monthly visitors. Before they began using Experian, the company was hesitant to grant credit internationally due to the limitations of its previous sources. Rubicon Project is focused on rapidly expanding into new territories while providing world-class service and minimizing risk. In some geographic regions, online ad trading is a new concept that is generating considerable excitement, but this poses the challenge of being able to adequately navigate risk in uncharted waters. "With Experian's Business Information Services, we have access to comprehensive information that helps us uncover new growth opportunities," said Lorraine Moses Rubicon Project’s director of credit and collections. Most recently, Rubicon Project has been challenged with monitoring customers located in high-risk countries affected by recent economic challenges in the Eurozone and Latin America. “Experian simply has updated information on many of the customers of concern,” Moses, continued. “We have been able to grant credit to a large number of international customers that would have been declined because we were unable to determine credit worthiness due to limited information.”