Alternative Data

For decades, lenders and others have relied on core credit data focused on financial borrowing and repayment behavior. Many factors go into the decision-making process, including the length of credit history, the number of open accounts, and on-time bill payments. What happens when a consumer or small business owner relies on cash for financial transactions or has never held a mortgage or a business loan? A significant portion of the U.S. adult population faces this problem. According to a 2020 report by the Federal Reserve, as many as 21 percent of U.S. consumers survive without a credit card. As a result, the traditional credit-scoring model doesn't tell the full story of their financial health, and they could be labeled “credit invisible" or “unscored" due to limited access to credit. It's both a personal and business problem. For consumers, that might mean not being able to secure a mortgage, insurance, or even be considered for a job. Start-ups and small businesses, meanwhile, may not be able to access credit to fuel their future growth and success. The recent explosion of new business filings brings the challenge of credit access to a head. Because small and emerging businesses can lack sufficient credit histories to qualify for credit on their own, they may rely on the owner's personal credit profile for lending decisions. Yet, some small businesses continue to struggle to get financing. It's especially pronounced in communities of color. For example, Black-owned businesses get turned down for bank financing at twice the rate that white-owned businesses do, according to the Federal Reserve. Technological innovations such as Experian's Experian Boost are shaking up the conventional scoring system by bringing in alternative credit factors to fill out the credit picture. For lenders, the emergence of alternative data, otherwise known as non-traditional data, helps them make informed business credit decisions among a wider number of customers and prospects. What is non-traditional data? Traditionally, lending and other credit decisions have been based on factors such as credit history and on-time payments. That can allow people and businesses that do not have a lot of cash but can demonstrate good repayment behavior to borrow. However, it's quite another story when the situation is flipped. Some consumers and businesses don't utilize financial products, though they might have healthy cash flow. As a result, they lack the necessary data to generate a credit score, making them appear to be unattractive credit risks. Non-traditional data is an important way to give consumers access to better rates and open up borrowing to more consumers and businesses. This data can include things like rent and cell phone payments, giving lenders a broader range of information to consider. According to FinRegLab, 96 percent of U.S. households have a bank account or a prepaid card and 91 percent of U.S. adults have at least one utility account in their names. Overall, including other credit data, in addition to core credit data, would bring more people into the credit system. Including non-traditional forms of data can create financial inclusion for consumers and businesses. Where does non-traditional data come from? Non-traditional data is generated by aggregators that scour utility accounts, public records and property information to understand the financial activities of consumers. It considers a wider range of financial behaviors than what just appears on a credit report. These can include: Rent payments Utility payments Employment verification Bank account information, including recurring payroll deposits, average account balances and withdrawal activity. Property records Non-traditional credit data goes one step further and supplements this data with information on consumers' use of alternative lending arrangements such as payday loans, small-dollar credit lenders, auto financiers, rent-to-own, retail financing, and others. Commercial lenders can also take advantage of technological innovations to gather non-traditional data for lending decisions, which can drive more approvals and greater profits. For businesses, non-traditional credit data can include: Social media: How many user check-ins and reviews is a business getting on social media? That can say a lot about its business. Experian Social Media Insight™ provides a social media view to help lenders better score business borrowers with thin credit profiles. Online financial activity: An uptick in PayPal or Venmo transactions can suggest healthy cash flow. Bank details: Borrowers can permit lenders to view their business banking account, which shows how much cash on hand they have. Accounting software: With direct access to QuickBooks or FreshBooks, lenders can make determinations about a potential customer's financial health in real-time. Shipping information: For businesses moving products, analyzing shipping data allows lenders to make assumptions on cash flow. How is non-traditional data currently used? Financial institutions have become receptive to other credit data sources to provide additional insights. That can improve the accuracy of credit scoring and allow lenders to find more creditworthy consumers. According to Experian's 2020 State of Alternative Credit Data report, 96 percent of lenders believe that during times of economic stress, non-traditional credit data allows them to more closely evaluate consumers' creditworthiness and reduce their credit risk exposure. By deeming more consumers creditworthy, financial institutions can increase financial inclusion, while uncovering new lending opportunities for themselves. Modern tools make that possible. For example, Experian's Clarity Services provides insights on more than 62 million U.S. consumers, helping lenders better assess and manage risk. Lenders can see consumers' utilization of alternative finance and payment behaviors for a more holistic view of their creditworthiness. How can non-traditional data be used to calculate credit risk? Non-traditional credit data can help lenders gain deeper insights into their borrowers to better assess risk. For starters, it allows them to spot creditworthiness trends in real-time, rather than a snapshot in time that traditional credit data typically provides. A deteriorating financial position among prime customers and signs of improvement among marginal customers can be spotted faster with a combination of traditional and non-traditional data. Also, some consumers may appear to be “risky" through the lens of core credit data but may prove less so when non-traditional data points are included. For example, according to FinRegLab research, cash flow data can be predictive of credit risk, not just credit utilization and history. Owner-permissioned data lets consumers decide what lenders can see when making their credit determinations. For instance, lenders who use only traditional data might see an account that has been turned over to collections. With owner-permissioned data, on the other hand, a lender can also see a record of paying rent and cell phone bills on time. As a result, lenders can evaluate both types of behaviors in their credit decision, providing them with a fuller picture. Looking at how consumers leverage alternative financial products to manage debt can also reveal responsible credit-management behaviors. Consumers who appear to be low-risk in the eyes of traditional credit data may actually be riskier if they do not manage their alternative finance products well – an activity that doesn't appear on most credit reports. The challenges of non-traditional credit data Non-traditional credit data has the potential to open the world of credit to underserved communities. For lenders, it can unlock opportunities by bringing in a wider range of potential customers. But it's important to recognize that there are challenges too. For starters, lenders are still figuring out how to incorporate it into their lending decisions. While non-traditional credit data has always been available, big data collection now makes it easier to access. As lenders and regulators become more comfortable with its use, they will begin to incorporate it into credit decisions, while also being aware of its limitations. Consumers, meanwhile, may have data security and privacy concerns about how their information will be used and who may have access to it. The Consumer Financial Protection Bureau is working on guidelines that ensure that lenders are using data appropriately and fairly. Related Posts

In the wake of the Coronavirus Pandemic, thousands of companies were forced to go digital, transforming brick and mortar experiences to mobile-enabled, touchless digital experiences.  Whether you were a small grocery chain or a family restaurant getting plugged into a myriad of takeout ordering platforms, the choice was simple, upgrade to a fully digital experience or go extinct. When the $2.2 trillion CARES act passed in March of 2020, and with it the $350 billion Paycheck Protection Program, many banks had to work quickly to transform their SMB lending process to be more data-driven, risk-proof, scalable, and ready to deploy in a matter of weeks, rather than months. The Unqork no-code solution offers a flexible alternative. There’s a new breed of solutions that make it possible for banks to build robust, mission-critical applications without using a single line of code. Unqork is the leading no-code enterprise application development platform. With Unqork, you can manage no-code application development throughout the entire Software Development Lifecycle without having to implement traditional coding efforts, so you can move faster at a lower cost with fewer errors to future-proof your business. The Unqork platform makes it easy to power applications with Experian data using API’s. You can build powerful digital experiences without the scripting and coding you would normally expect. Curious? Watch our recent Business Chat interview with Unqork below. Digital Transformation with No-Code & API's | Business Chat Interview Transcription We interviewed Ben Smith, Head of Banking with Unqork and Carl Stronach, Senior Product Manager with Experian met during a recent Business Chat about No-Code for Enterprise Financial Services. What follows is a lightly edited transcription of their talk. [Gary]: Hello and welcome to Business Chat. So happy you could join us today. I'm Gary Stockton with Experian; I'm with Business Information Services here in North America.  We would love to know where you're joining us from. We're streaming here from Costa Mesa, California; we're live on LinkedIn and other channels via Restream. Be sure to drop us a comment and hashtag #teamlive if you're watching us live, hashtag #teamreplay, if you're catching this on the replay, and remember sharing, is caring. We would love it if you can share this chat. If you could let your colleagues know that we're talking about APIs and No-Code by sharing this live stream, that would help us expand our audience. So they were going to be talking about no-code technology and Experian API's with two great experts. Joining us from Unqork is Ben Smith. He's the head of banking, and from Experian is Carl Stronach. He's a Senior Product Manager here at Experian, and he works on API's. Welcome gentlemen. Ben, if you could take a moment, please tell us a bit about Unqork and your mission, where you're based, and how you got started. [Ben]: So we were founded in 2017 by Gary Hoberman. Gary was the CIO of MetLife, and Gary had a mission to redefine software development and focus on delivering software at the enterprise-grade faster with a lower total cost of ownership and something that could be delivered by a number of different people, not necessarily people who had a significant development talent and experience. So Gary set out in 2017 to redefine how we do it. We are a no-code platform. We are totally cloud-based and agnostic. We are deployed in over ten countries with over 70 different clients. And the other thing, part of the mission that we have here around the development is we've trained over 10,000 experts globally who can develop on the platform because we believe that the no-code environment allows for rapid adoption, and we want that adoption to be significant. [Ben]: So, what it says here is we have three major investors; we have a number of other ones. Obviously, BlackRock, Google, and Goldman Sachs are all major investors. And then, as I alluded to earlier, the mission of the firm is to develop enterprise-grade no-code solutions. So you can see at the bottom of this slide some of our major customers as well. [Gary]: Carl, could you share a little bit about your role here at Experian you've been at Experian quite a while, and how you work with companies like Unqork? [Carl]: So I've been with Experian for almost seven years, I'm focused on new product development. For the last four years, I have been focused on our APIs and bringing Experian business information into our global developer portal. In that time I've worked with a countless number of banks and FI's, and many of our clients across our verticals in their integration with Experian. In terms of how they are going to get our data in the most efficient way. I've supported a lot of them from the business side and the IT side and kind of sat in on both. And I've seen many of our clients really succeed with their integrations with us. That's just a direct integration to our rest API, and others, you know, take a long time. [Carl]: So I'm sensitive to the fact that coding to APIs as easy as we can try to make them with a rest API, and as easy as we can try to make them by adding SDKs or, or other supporting information on top, it's still difficult and time-consuming. A lot of the time to code to APIs certainly gets much more complex as we get into regulated data.  So it's definitely something that we want to narrow the timeline strategically.  How do we get access to data and query it faster than ever before?  Strategically it's something we're interested in and excited to be a part of, and working with providers like Unqork allows us to unlock some of those technologies. [Gary]: So Ben, what's the distinction between low-code and no-code, and what drives the adoption of no-code technology? [Ben]: The main difference is that everything that we develop on Unqork does not have any native code to it.  So for you, as a developer, it's a complete visual system. And the most important thing is there's no need to maintain the code once you've written it. So even in low code environments, there is, of course, the upkeep of the code, and ultimately it becomes legacy. Whereas in our system, all of our customers are on the same platform using the same environment, or sorry, using the same software to develop their solutions. And they're always up to date. That's a big difference, there's no need to develop that last bit, and there's no need to maintain it once it's out because as soon as you write a bit of code, you've got to maintain that code going forward. [Ben]: To the second point, how are people adopting it?  We see it adopted across a number of use cases. So, for exactly that reason. Many in my world as Head of Banks, many of our customers in the banking sector are looking for ways to develop both customer-facing as well as internal-facing software that digitizes their workflows, whether that be onboarding, operations. It just depends on the needs of that particular bank. But again, the rapid development, the ability to get to market faster and the ability to not have to maintain that codebase once it's up and running have been a really powerful part of our value statement. [Gary]: Carl, switching to data and API's. You work with a lot of clients in the banking industry. Can you tell me where in the customer life cycle does Experian API's fall? [Carl]: It's really across the lifecycle. From campaign targeting and finding new customers to underwriting and account acquisition and customer management, even collections. It's really across the full spectrum. To take a step back.  Everyone thinks of Experian as the consumer credit bureau. And, I am a very big fan of John Sina. So I think that's how Experian is generally known. But Experian's business goes well beyond just consumer credit. Obviously, we have business credit, and that's our focus here. But when it comes to our APIs, we bring everything together into a single global developer portal. So, what you can do through a single developer account is an interface with all Experian information, and we source data internally. So we've got our North America Business Information, Consumer Information, Automotive, Data, Quality, Decisioning, you name it, it's all available in one place. Also, we have an International focus too. So if you go there, you'll see API's from the UK, India, Singapore, all across the globe. We really try to be that shop for Experian data, making it much easier to code to us and eliminate those silos that used to exist in our own internal legacy systems. [Carl]: Now, I'm really excited by some of the things that Unqork can do. When we talk about setting up one workflow that can be shared many times and doesn't have to be re-coded over and over and over again, we see the same in working with our customers. When we work with our banking customers, a lot of them execute the same exact workflows to get to Experian data. Maybe the data they need is different. Maybe the data they find predictive is different, but it's really a lot of the same workflows. And so, as we work with Unqork we can define more of these workflows, make them predefined and hopefully just speed time to market. Really eliminate a lot of the burdens with a new integration or basically offer a new product and get it out. [Gary]: So you're finding that customers are applying these new technologies to get to market faster. I have to imagine that that was fairly active during COVID. A lot of people spinning up shopping carts and people that have brick-and-mortar stores had to innovate faster. And would you agree that platforms like Unqork are helping make that possible with API's? [Carl]: Absolutely, so that's even a part of what we're trying to do as well. As small businesses have had to transform due to COVID, they've had to adopt more digital experiences and maybe they had to. It's a restaurant and they had to change their storefront from having tables and chairs to having just a counter and offering delivery, opening up the restaurant to more kitchen space, to handle a greater number of orders coming in. I think we are also trying to capture new data assets that can tap into that business's digital transformation. So, we've done a lot to acquire more online data on businesses, more social media data on businesses, to tap into understanding what that business activity is. Are they open? Are they closed due to COVID? And so, as we start to adopt those new data sources, our clients also face the challenge of discovering them, integrating them into their services. [Gary]: Excellent. So, a two-part question for you Ben.  How are banks deploying no code and, and are there any security considerations when using a no-code platform? [Ben]: I think you know what we do here at Unqork for some of our customers, and what Unqork provides is the capability to both design a bank-specific user experience, but in a rapid way to deploy digitally. To solve problems that are rising quickly. PPP is a good example of that and other ones. Going forward, the ability to integrate with places like Experian on different data types such as social and some of the other ones that Carl spoke of. I think will be very important in terms of how banks redefine their small business and business offerings because post-COVID we're all going to be trying to figure out how to serve that segment in a way that makes sense from both a credit and a service point of view. [Gary]: Excellent. So, Carl what challenges are you seeing with lenders adopting and integrating bureau and non-traditional data? I mean, non-traditional is a hot space right now. [Carl]: Yeah. So, I think one of the challenges is just discovering the data and defining it, and being able to start working with it.  I think we experienced that, even internally, so there are just so many different data sources out there. How do you really prioritize what to go after? Having it available in a single place is really key.  If you had to continually define data and bring it into your database in order to work with it, it just becomes very challenging.  We need to find and adopt technologies that take that burden away from our customers. Gary, we can't expect every customer to define the data source. We need to do it for them and technologies like Unqork, give us the ability to do that. And so, I'm excited by that part. If we can lower the burden there, it can unleash data analysts and data scientists to really find out which data might be predictive.  So a lot of our customers want to find data that's going to be predictive of credit risk, predictive of delinquency. We need to find ways that allow them to really focus their time on finding the data, what data is actually going to be predictive. I don't want to spend all my time just defining the data just so I can test the top, a couple of fields that I have a hunch on. I want to go deeper and really find that marginal value. And technology is the key enabler that lets us do that. So go into the data. [Gary]: Thank you, Carl. So, Ben, based on what we just heard from Carl, can you share some examples of how SMB lenders can fast-track lending applications? [Ben]: Sure. We're working with banks around both customer onboarding and also around, the product development, into the origination cycle.  I think what Carl's saying is right. To the extent that we can discover this data and get it at a deeper level, get it into the risk modeling infrastructure,  through the integrations that we, as a platform can build, allows for more rapid adoption of alternative data sources. But also, better credit decisioning, you know, particularly as I sort of feel passionately about a post-COVID world and the need to take a different view as to how that credit risk moves or how credit risk is assessed. [Gary]: Well this has been very interesting guys. And folks, if you would like to learn more about no-code and how to fast track applications and integrate with Experian API's, Unqork is hosting a webinar March 24th at 12 Eastern. Experian is going to be participating in that, we're very excited to participate.  If you would like to register, you can just point your phone at the QR code or go to the link that we have there. We'll leave that in the description for this video, if you want to come back to this later. And, by all means, if you have any questions drop them in the comments. We'll be monitoring the comments in the next few days and replying to those. I want to thank both of you guys for taking time out today. I know you're both extremely busy, and looking forward to chatting with you again soon and looking forward to the webinar on the 24th. Watch Webinar Unqork + Experian: Smarter Small Business Lending  

When insurance underwriters make mistakes, bad policies can cost billions. Alternative forms of data is helping change those outcomes, particularly for insurance providers in helping them identify blind spots and accurately underwrite policies. Watch our special Insurance-focused webinar titled "Beyond Credit Risk - Understanding Alternative Data" with HazardHub. Heath Foley and Carl Stronach from Experian is joined by Bob Frady from HazardHub during this lively discussion. Alternative sources of data are growing in importance in the market. The key to our data platform is constantly investing and sourcing a wider variety of data such as geographic hazards, social media, and OSHA data in order to represent a fuller picture of the health of the business.  In this one hour talk, we walk through: Utilizing property-level hazard risk assessments The growing importance of alternative sources of data How to bring superior data to power comprehensive insights Related information What is alternative and non-traditional data/

A gastropub restaurant applies for business insurance and is approved. However, social media insights show the restaurant is declining. Even though underwriters usually take a quick look at social media postings, evaluating the trends of the business is not part of the decision process. Costly mistakes: Underwriting using only business supplied information How could something as basic as a business in decline be overlooked in the insurance underwriting process? Think about the process when reviewing a new business insurance application. The underwriter reviews the application and looks at traditional credit and public filing information. Although the underwriter checks out the company website, he doesn’t meet or interact with the company. He then must make a potentially costly business decision about its risk level. Even though the process appears thorough, it does not use the new wealth of information available. How social media provides information about business health If the insurance company had used unique and new sources of social media data, the underwriter would have seen a different picture of the restaurant. The trends in the number of reviews point to a declining business due to poor service, bland food, or increased competition.  Traditional data sources miss these subtle signs that point to a higher risk of going out of business. While one poor review shouldn’t result in a denial, a pattern of a declining business is important. This can be spotted using tools that analyze the trends in reviews and ratings for the business line. After all you cannot compare restaurants, with high volumes of social media postings, with say a dry cleaner. By correctly using social media data during the underwriting process, insurers can give an additional lift on the model to determine the risk. Social media data can also help determine more information about the business. For example, an exercise gym may have treadmills and weight machines, or it might actually be a kickboxing studio, which has a much higher level of risk and premiums. Underwriters also get a much more granular view than a typical application, such as the parking situation and the hours. Because risk is higher for businesses with a liquor license, insurers can often learn if a bar didn’t disclose this on their application. Customer photos also often tell a story not detectable on the application, such as broken stairs or a fireplace without proper screens. Using artificial intelligence to analyze social media data Looking through social media for each application takes large amounts of time. Even more importantly, humans may be subject to bias and miss word patterns in reviews. By using an artificial intelligence tool with machine learning capability to analyze social media data for business insurance applications, underwriters can gain a much more accurate picture of the risk they are assuming by insuring a business. Additionally, an AI tool can analyze business health much more quickly than an underwriter could doing the social media check manually. Insurance companies that use artificial intelligence tools to analyze social media data during the underwriting process can more accurately predict the risk of a business. Because the processing speed, adding this additional step does not slow the process down. By reviewing what other people are saying about the business, your insurance company can decrease risk and save money on claims.

For lenders, alternative data can be the factor in edging out your competitors, especially when better decisions are needed to compete for emerging businesses and startups. Both startups and emerging businesses may represent a good growth opportunity, but they may also be high risk. The challenge? Businesses with thin credit profiles can be difficult to score. Social Media Insight TM provides lenders with another layer of data that can help you better assess the direction of these businesses, score them more accurately and open new growth opportunities. After all, nobody likes to leave money on the table. For emerging businesses who have a thin credit profile but have a strong social media reputation, Social Media Insight can be a factor in gaining access to credit and resources they deserve. Social Media Insight enables you to see the activity, trends and sentiment on a business, over time. In our Experian DataLab tests, we improved overall model performance by 12 percent and new and emerging businesses by 91 percent, boosting predictive performance over traditional data sets. Social Media Insight is directly sourced data providing you with over 70 attributes including trends and sentiment along with descriptive attributes. This powerful data enables you to more accurately score or assess new and emerging business as well as long established accounts. Want to learn more? Watch our on-demand webinar or contact your Experian representative today.    

The Consumer Financial Protection Bureau (CFPB) is engaged in increasing its understanding of the opportunities and potential challenges associated with consumer permissioned account data. The agency launched a request for information on the topic in November 2016 and is currently analyzing information it received prior to the February 2017 comment deadline. In remarksat a field hearing in conjunction with the launch of the RFI, CFPB Director Cordray stated, that "access to digital financial records is critical. As with your student records or medical records, your financial records tell an important story about you. With health care, for example, if you can see your records, it is easier to participate.” Demand for financial account data goes beyond consumer loans and its use in the small business credit-granting process has been increasing. Experian recently entered a partnership with Finicity to develop new tools that will make it easier for small businesses to apply for a loan and to accelerate loan underwriting. These tools are used for authentication, verification of income and assets, and cash flow analysis. These tools improve accuracy and reduce fraud risk for lenders, thereby broadening access to loans. Experian's new Digital Verification Solutions leverage Finicity's data aggregation and insight platform. Experian is the first credit bureau to implement this technology, which gives small businesses the opportunity to secure loans with less paperwork and hassle by connecting with financial institutions digitally. While this information is currently limited in use for credit risk analyses for small business lending, Experian believes that user-permissioned account aggregation platforms will increasingly provide an opportunity to collect and analyze cash flow and recurring payment information relevant to lenders in making credit decisions. For example, user-permissioned data from a businesses’ bank account could demonstrate the entity’s payment history for utilities and telecommunications services, as well as for monthly rent. With respect to the collection and use of data obtained through account data aggregation platforms, it is important that a borrower grant permission pursuant to clear statements about how the consumer's information will be accessed and how the data will be used. Such statements should include whether the data will be shared with third-parties, and for what purposes. It is vital for market participants — both financial institutions and account aggregators — to continue to work together to develop cooperative agreements that allow data to be accessed, analyzed and shared in an efficient and secure environment. Recently, several account aggregators have formed direct agreements with financial institutions and there is ongoing work to develop best practices and industry standards for secure consumer and business access to financial data. In the past, the CFPB has promoted this ecosystem. As with other commercial credit data, financial account data can be used to make decisions throughout the credit lifecycle. This includes supporting pre-qualification when a business is prospecting for new customers; conducting credit risk analysis and verifications; managing portfolio risk; and if necessary, collecting on unpaid or overdue debts.

This week for Business Chat | Live we interviewed Peter Bolin about business owner wealth, and how lenders are finding new ways to evaluate entrepreneurs in the underwriting process. Gary: Today we're going to have a discussion on business owner wealth and evaluating business owner wealth in risk models. Joining me today is Mr. Peter Bolin. He's the Director of Analytics and Consulting for Experian. Good morning Peter. Peter: Good morning Gary. Good morning everyone. Gary: Let's just kick off this discussion. Business owner wealth and small business owners and evaluating risk. What's it all about? Peter: Yeah, thanks Gary, thanks everyone. As I travel around talking to a hundred clients a year, one theme that always comes back is, "Hey Pete, can you and Experian help us get to yes?" We know that there is a pool of small businesses, a pool of small business owners out there that are small, that are emerging, that are cutting edge, maybe not solid yet, but they don't have a credit file, what we typically call maybe credit invisibles or maybe thin files, but we know that they have a good idea, we know that they've good product and services, but we can't approve them. Is there anything you can do to help us get to yes? At Experian we got to thinking about that. We have a tremendous amount of data assets as everyone know. We looked around and we said, "Hey, there is this new product that we have called the Wealth Opportunity Score," and that estimates, based on our proprietary database, the wealth of an individual. We got to thinking, does wealth of a business owner affect the opportunity to be approved? That's what we're here to talk about today, Gary. Can we use the Wealth Opportunity Score on a business owner based on a sample of our data, we have some great results, and we definitely feel that we can help lenders, wholesalers, target marketers, get to yes. Gary: Okay. So you mentioned getting to yes. What does that mean in terms of say, a new business or a business that has say, a very thin credit file? How does that work? Peter: The first thing that we do when we're evaluating any new data source, and while wealth insights have been at Experian for a year or two, it's new, we're introducing it for the first time to the commercial space for the business owner, the first thing we do is say, "Okay, can we get a predictive lift by using this data?" The answer is yes. In particular, can we use this in the thin file, in the very, very small, emerging businesses that maybe we could refer to as the credit invisibles. It's kind of an overused term. Invisible to who? So, we're using this in this example as credit invisible are a very thin file or maybe have no file on the commercial credit report. We took a sample of business owners in that population and we added this Wealth Opportunity Score as an attribute within our demographic only segment, and we said, "Yes, indeed, this does help the predictive power of that segment." Going from a KS of a 16 to a 23. A KS for those of you who might not know, that's the Kolmogorov-Smirnov statistic, that's the industry standard for measuring the predictiveness of the model, the higher the KS the better the separation between the goods and the bad. We're seeing that yes, by just including this data, on the credit invisible/thin file, that segment was able to improve the predictive power by 43%. Gary: Wow, that's incredible. So, we discussed the better prediction of risk using the owner wealth. What does rank ordering have to do with that, and why is that such a big deal? Peter: As quant jocks sometimes we get overly, overemphasize the KS, the rock, the Genie, area under curve and those are all important statistics, but we can't forget about another critical part, which is the stability of the model. That's where we look at how well it rank orders. We'd like to see a nice, smooth monotonic progression in the rank ordering of the bads throughout the decile. We would like to see a large number of bads pushed down to the riskiest scoring, and fewer number of bads pushed up to the least risky. As you can see, when we added the Wealth Opportunity Score to our demographic only file, we got a nice, more smooth monotonic progression, which says not only do we get lift like we talked about in the first slide, but we're also improving the stability of the model, which is very, very important. As you can see, it's still a little bit choppy. Some of you might say, the skeptics out there might say, "Gee, Pete, this is all pretty choppy." However, keep in mind this is a demographic thin file, not much to go on other than some key demographic items, but by adding the Wealth Opportunity Score we're able to increase the predictiveness and the stability of the model. Gary: Wow. Okay, so there's been a lot of talk about women-owned businesses, minority-owned businesses lately. How does wealth play in the role in accessing credit for minorities, and in particular women-owned businesses? Peter: Absolutely. Gary, that's a huge topic right now, access to credit. Do minority-owned businesses and especially women-owned businesses have access to credit? We're also looking at data to help evaluate that. The next thing we did was, we were curious. Okay, is there a difference between a male-owned business and a female-owned business when it comes to wealth? Really, if you look at the bottom two lines on the curve, you see that there's really not. They're pretty similar. They are fairly similar. There is some blips on the lower side, so if you're looking at the left side of the graph, you do see where that pink line is the female owner, they do tend to have slightly lower wealth, and that's measured on the first Y axis. What we're saying is that there's really no difference. If you're looking at wealth, there isn't much difference between a woman-owned business and a male-owned business, so that should not be a prohibitor in access to credit. The other thing that we looked at on the other, secondary X axis, is the whole concept around annual spend. This is annual spend on the business owner personally, not the business, so I just want to make that clear. We looked at that, and we saw similar trends, that there really wasn't much difference in spending except in the very, very high quadrant up there, there was a little bit of difference in the extremely wealthy. Actually, it says that male owners, male business owners, had much more annual spend. So, not only were we introducing the Wealth Opportunity Score, which is a new concept in commercial lending, we're also looking at the total plastic spend on the business owner personally, which we found is a very powerful indicator, especially when you're trying to target market. Gary: Excellent. Okay, changing gears a little now, to target marketing and how does wealth help with those that are maybe in the market for credit? Peter:  Well, it's very interesting Gary, because what we find is that there's an inverse relationship between wealth and in the market, so very, very wealthy owners are not as in the market based on our in the market score. We have a business credit seeker model, which predicts the likelihood that someone's going to open up a new trade, so, that they're in the market. They're really serious about it. We threw these attributes and this scores into that model, and what we found is that intuitively I think that it makes a lot of sense as well. What we see is that lower wealthy business owners are more in the market, right? They don't have any personal wealth. They need capital. They need access to capital. They're anxious to get capital. There's a higher percentage of the lower wealth spectrum that are looking for credit. However, however, that's not to say that the high end, so if you look at the very high end, three million or more in wealth, there's also a percentage, 9.5% of the population that are also looking for credit. They could be a small business, they could have two employees or less, they could be around for two years or less, but they have high net worth. They might be invisible on the commercial side and this Wealth Opportunity Score will definitely help them, help lenders and wholesalers get to yes. Gary: Are there other particular industries that you recommend targeting with the new business credit seeker model? Peter: Sure, that was the other kind of thing that was surprising to me, I'll be very frank. This surprised me, because when we looked at the industries and then we plotted the risk scores, and then we plotted the bad rates, and then we looked at the wealth of the individual, or sorry, not the wealth at this particular point. What we're looking at here is the actual in the market. What we found is that the industries that have the highest in the market percentage, which is measured on the blue bar, and then we look at their average IPV2 score, that's Experian's commercial risk score predict a likelihood of a trade going 91-plus, we see a convergence that the agricultural, wholesale trade and mining industry, which surprised the heck out of me, were the three industries that have the highest percentage and likelihood to be in the market, and also had the highest IP score, which means they have the lowest risk. The mining industry in particular, Gary, is shocking, because over the last eight years, without me getting too politically sensitive, that industry has taken a battering in the last nine years. Big cuts, big cutbacks, in traditional coal mining, and what we're seeing now, with some of the new administration's outlook on mining, the regulations are coming off and we're predicting that this could be a very big growth opportunity for our clients in terms of marketing, in terms of wholesale credit, traditional lines of credit, and traditional term-type credit. The mining industry in the market and a very high IPV2 score, and later on we'll see also some interesting wealth information about that as well. Gary: Excellent. You talked about credit scores. What about bad debt rates and industry targeting? Can you talk a little bit about that? Peter: Yep, very similar results. We also wanted to look and see what the bad rates were for each of these industries to give the viewers an opportunity to see this trend. This is also the exact same thing as you saw with the score, relatively low risk. Agricultural, wholesale trade, mining again, when you look at their bad rates as measured on that secondary axis, but high in the market. Very, very surprising to me, once again, I did not expect to see especially the mining, given the fact that they've been hammered the last nine months, so again, if you're looking about low-risk industries to target, those are the three that I would recommend. Gary: Does owner wealth matter in these industries in particular? Peter: It does, it does, especially again in the mining industry. You see some interesting wealth statistics. If you look at the distribution of the Wealth Opportunity Score, which once again, predicts the wealth of the business owner, or the individual but in this case we scored it with business owners, you see some blips. Those yellow bars, some blips, and as you can see, there's also a tremendous opportunity really up there in that big, look at up there, there's a significant percentage in all three of these industries, but particular mining industry that have extremely high net worth. We already know from previous slides that they have low risk, low bad rates, so again, the mining industry, high wealth, high scores, low bad rates, again, another indication that using this data can help you get to yes. Gary: What about micropreneurs, you know, these businesses that are just emerging, just getting started, they're credit invisible, right? Does the business owner wealth factor come into lending and risk models? Peter: Certainly, and the whole concept of a micropreneur, that's kind of a new term, I'm not even sure it is a word, but maybe we invented it, the micropreneur, a great concept, very, very small businesses. It's not uncommon, Gary, that I get the following statement made to me when I'm talking to clients: "Pete, we don't approve anyone that's been in business for two years or less. We don't approve anyone that has two employees or less. We don't approve anyone who's a sole proprietor. We want to avoid those type of businesses," and I would urge all of the listeners and all of the viewers to think a second time about that, because even if you look at the far right-hand side bar, there are 28% of the population with three million or more in estimated wealth, 28% of that population have been in business or have one or two employees or less. That wealth could be used in your personal guarantee situation, that could be used as collateral. The other nice thing about the Wealth Opportunity Score before I forget is actually evaluating the net worth of an individual. It gives you the opportunity to verify that. It's very common in these situations that if a small business, one or two employees or less, goes in for an application, applies and they have to have a personal guarantee, and they say, "I'm worth $3 million," well, how do you know? Well, with this system you can come to Experian and at least get an estimate that that wealth is right, that you've verified that wealth and that you can set your credit limits, you can set your approval accordingly. So again, what does it mean for the micropreneur? It means that if they have wealth, it's another data point that can help you. Gary: It's helping them get their businesses started. It's helping to drive the economy, which is, at the same time this is good for everybody. It's a win-win situation of, it sounds like to me anyway. Peter:  Absolutely. You know Gary, the whole concept of what we're talking about today comes from my personal passion, and I know Experian Business Information Services as an entity's passion, to be an advocate for the small business owners. What we talk about frequently. Through this passion, we're looking at all of our data assets. Can we use our data assets for good? And the good is, as small businesses goes, so goes the United States, and I'm really passionate, and I know Experian Business Information Services is passionate about turning over every leaf, every piece to data, that will fuel small business growth and fuel our economy. Gary: That's awesome. Okay, well this has been excellent Peter. I think if folks are interested in this, we just invite them to drop a comment on the video here if you find this on YouTube, or come to our website, experian.com/b2b. I'm sure we can connect you to Pete and his experts in business information if you want to talk about business owner wealth models. Pete I want to thank you so much for taking time out this morning to come on and talk to us about this topic. I really enjoyed our chat, and we'd love to have you back again in the future. Peter: Thank you Gary. I had a lot of fun. My first live TV spot. Gary: All right, thank you Pete. Have a good day, and- Peter: Thank you. Gary: And have a good day everybody. Thank you so much for coming to our live video. As I said, we're just wading into this. We'd love to have more of these live shows. If you've got ideas for live shows, if there's things about business information, things that would help you be more successful in business or evaluating risk, just send us a note on our YouTube channel. We'd be happy to consider that, and maybe put a show together. Maybe even invite you on as a guest. That's it for today, so thank you everyone and have a good day.    

This year’s Marketplace Lending and Investing Conference explored issues of transparency, partnership, consistency and sustainability.  There was healthy debate on each of these topics and the audience, presenters and panelists frequently returned to the theme of the relationship between Marketplace Lenders, Fintech, Banks and Investors.  As the conference unfolded I thought about the role of small businesses in the relationship between these stakeholders.  How do mom and pop small businesses fit into these complex, rapidly evolving relationships? In mid-2015 The Federal Reserve of Cleveland published a report.  The title was “Alternative Lending Through The Eyes of ‘Mom & Pop’ Small-Business Owners: Findings from Online Focus Groups”.  The report found that the small business owners participating in the online focus groups had a number of common concerns: Marketplace Lenders’ sites are attractive … but how secure? How private is the information the small business provides? It is difficult to compare product offerings, features and pricing The small business owners bank is a source of advice but is not necessarily considered as an option for funding There are some clear parallels with the conference’s focus on transparency, partnership and sustainability.  See if any of these sound familiar: Regulators at the federal and state level are researching the Marketplace Lending industry and exploring ways and means of regulating the space. They are particularly focusing on issues of disclosure, fairness, privacy and governance.  The CFPB – Consumer Financial Protection Bureau has been particularly active.  There are two recent examples that illustrate increasing protection for small businesses. Dwolla was hit with a $100,000 fine in March of 2016, directly related to data security practices.  Then, in late September LendUp was fined $3.5 million for deceiving its customers.  The list of lenders who have strayed from fair and transparent business practices is long and growing.  Fortunately, regulatory supervision of the online marketplace is here to stay. Banks largely abandoned the small business segment post 2008. Lack of profitability is most often cited as the reason for the exodus.  Marketplace Lenders entered the space, delivered a wide range of product offerings, high levels of responsiveness and a relatively painless customer experience.   Now, eight years later, banks and Marketplace Lenders are partnering to make the most of their relative strengths – deep customer relationships and the capability to deliver exceptional customer choice and experience, through technology. Leaders in the various stakeholder organizations are still focused on surviving, meeting goals for growth, managing risk and optimizing returns.  In the past these may have conflicted with the small business owners interests.    In late 2016, they are in alignment … and that is good news for small business owners throughout the US economy. If you would like to hear more of what I learned at Marketplace Lending and Investing, check out the Live Marketplace Lending & Investing Q&A I recorded from the conference.          

Simply put, online marketplace lending is here to stay. Virtually unheard of just 10 years ago, Web-based companies that offer funding options beyond traditional bank loans have grown considerably. Small businesses — drawn by the easy application process and flexible repayment terms, have become increasingly comfortable working with online lenders, which offer rapid access to capital, a wide array of niche products, and a low-friction customer experience.  The lack of regulation and higher-than-market interest rates that often accompany these “alternative” loans have not deterred borrowers from trying this new source of business financing. Despite their growth, however, online lenders still make up only a small segment of the overall small-business loan market. While that paints a clear picture of the current online marketplace lending environment, what does the future hold? How is the industry, still in its infancy, likely to change as it responds to pressures from competitors, borrowers and regulators? Here are some trends we can expect to see over the next several years: Growth — As online lending becomes more mainstream, look for the industry to expand exponentially. In 2014, online lenders combined to issue loans totaling about $12 billion in the United States. In a recent report, Morgan Stanley said it expects the U.S. number to grow to $122 billion by 2020 and the global number to surpass $280 billion in the same time period. "Online marketplace lenders are still very small players relative to the overall market, but they’re growing fast. They could be very disruptive or an entirely new [source] of capital for both small businesses and consumers that aren’t necessarily serviced by larger banks.” James Francis Executive Vice President, Consumer Lending Group MUFG Union Bank N.A Participation — Exponential growth likely will be fueled by the growing acceptance of online lending by small businesses, especially those run by millennials comfortable with virtual transactions. As the customer base grows, look for competition to increase as both new and established lenders fight for the attention of this attractive market segment. "Small-business owners in general are increasingly turning to online options to seek capital. According to a recent study by the Fed, 20 percent of small-business owners sought a business loan online during the first half of 2014. Small businesses are using new technologies to manage their customers, process payments, handle point-of-sale — it makes sense they’d turn online for capital as well.” James Hobson Chief Operating Officer OnDeck   Innovation — New, even more, efficient ways for borrowers to secure business loans — not to mention the nature of the financial products themselves — will continue to appear as competition drives innovation. Look for lenders to develop: Faster, more user-friendly interfaces along with algorithms that further accelerate the review and approval process Frictionless access Improved customer engagement and experience Platform and product innovation "Certainly there are more players in the space today, which is great because it pushes not only us but the category as a whole to generate more awareness, more credibility and better platforms to help small businesses. The category as a whole has been built on this idea of making things a little bit more simple and easy. We’re always asking, ‘How can we provide our offerings in a frictionless way and time-sensitive manner?” Jason Rockman Vice President, Brand Marketing CAN Capital   "There are a lot of lenders offering similar products to the same customers. There will be more competition to offer more products, which is better for borrowers.” Meredith Wood Editor-in-Chief Fundera   Consolidation — Industries often go through a period of hyper expansion followed by a period of consolidation as larger, better-financed players acquire smaller competitors and underperformers go out of business. One hundred years ago, more than 100 companies were making automobiles in the United States alone. Today, there are fewer than a half dozen. Twenty-five years ago, scores of companies were making personal computers. Today, a handful of brands dominate 90 percent of the market. We can expect the online marketplace lending sector to experience similar consolidation. Spillover — As online lending becomes increasingly mainstream, look for traditional lenders — particularly commercial banks — to enter the fray. Some forward-looking banks already are working directly with online marketplace lenders, referring customers based on their needs and qualifications or re-creating the frictionless look and feel of online lenders. Look for the dramatic differences between “traditional” and “alternative” lenders to blur in the coming years. "There are several key reasons why banks would want to partner with online lenders. The first is to drive customer retention. A bank says yes to small-business borrowers roughly 20 percent of the time based on their lending criteria. What happens to the other 80 percent? Banks don’t want to lose those customers. Partnering with marketplace lenders is one way to retain those customers and create a good user experience. “Customer loyalty is another driver. Access to capital does more to build loyalty than any other product or service. Finally, the biggest motivator is access to new technology and data, especially for institutions forward-thinking enough to recognize that there are opportunities for them to monetize their existing data as well as learn from the data analysis and data science that some of the more sophisticated marketplace players are executing.” Glenn Goldman CEO, Credibly Regulation — Regulation is on the horizon for the online lending industry. While the absence of regulation has facilitated rapid growth and innovation, this lack of oversight also has led to an environment in which some borrowers have complained of unfair lending practices and a lack of transparency. Most leading online lenders believe some kind of regulation is good for the industry. A set of rules and standards defines the playing field and provides the confidence and consistency the industry needs to grow sustainably. “Some government oversight is going to happen. It’s just a matter of time,” said Levi King, Founder and CEO of Nav (formerly Creditera), which was founded in 2012. “Small businesses are not sophisticated. There’s a lot of predatory lending extended to small-business owners, who are, as a rule, not sophisticated enough to know what’s happening.” “We believe it’s important to foster greater transparency in business lending marketing,” said Rebecca Shapiro, Director, Brand & Strategy, Funding Circle. Along with Fundera, Lending Club, Opportunity Fund and Accion, Funding Circle recently helped craft the Online Borrowers Bill of Rights, which attempts to establish ethical standards the industry can use to police itself. “We don’t assume the bill can replace government regulations. We do believe that, by encouraging responsible regulations, we’ll have a model for what the government should do,” said Shapiro. The Future Is Bright Customer engagement, access, frictionless applications, and a wide range of product choices are at the heart of the online marketplace lending industry. The mainstream banking industry is starting to take note, looking externally at possibilities for collaboration and internally at ways of updating systems and processes to improve the customer experience. Ethical standards and regulations will increase transparency, accountability, and consistency. If these trends continue, both the small-business owner and the economy will reap the benefits. The State of Marketplace Lending In 2008, a short two years after the first online marketplace lenders opened for business, the Great Recession began to wreak havoc on worldwide financial markets. Small businesses struggled to survive, banks failed and access to capital was limited. More online lenders saw an opportunity and opend for business. These technology-driven newcomers hired an army of data scientists, coders and digital marketers. In the fall of 2015 the innovation, industry disruption and regulatory uncertainty that characterize this dynamic sector led Experian to produce a series of articles focusing on different aspects of online marketplace lending. This report contains those articles.   Download eBook Related articles Just how alternative are today’s online marketplace lenders? How online marketplace lenders are changing the rules of small-business finance Self-Regulatory Program for Nonbank Small Business Lenders Top regulatory priorities for commercial lenders Playing to Your Strength - Opportunities for Regional Banks to Build Better Lending Portfolios Game Changer - How Marketplace Platforms Are Bringing Financial Institutions Back to Small-Business Lending Marketplace Matchmakers - How Loan Aggregators Bring Borrowers and Lenders Together New Frontiers - What's Next For Marketplace Lending?