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If Diversity, Equity, and Inclusion (DEI) are important to your company, this exceptional webinar with the Consumer Bankers Association and the Federal Reserve should appeal to you. Launching an effective DEI initiative starts with understanding the State of Small Businesses. In this webinar we reviewed the latest 2021 Federal Reserve Small Business Credit Survey on business owners of color and their challenges when seeking capital. In addition, you will discover lessons learned from the implementation of the PPP program in granting equitable funding access to firms of color. Hiq Lee, President of Experian Business Information Services and Brian Bond, Senior Vice President of Marketing for Experian led a discussion on financial inclusion with Janelle Williams, Senior Advisor with the Atlanta Federal Reserve. Highlights: Insights from the Fed Credit Survey results on business owners of color Lessons Learned from the PPP program. How to navigate Financial Inclusion initiatives together with Experian Understand the state of small business and the impact of the pandemic on minority business owners Learn about equitable access to funds Take steps in achieving financial inclusion initiatives.   Watch Recording

Experian dashboard of PPP program helps lenders mitigate future first-party fraud risk The last round of stimulus for the Paycheck Protection Program (PPP) ran out of funds this week. The $953 billion stimulus program, designed to help businesses, self-employed workers, sole proprietors, nonprofit organizations, and tribal businesses continue paying their workers during the COVID-19 pandemic. As a result of emergency conditions and immediate concern to serve businesses in need, lenders relaxed vetting restrictions on PPP loan applicants. Also, they rushed to digitalize services to accommodate the massive influx of new PPP loan applications. Relaxed restrictions, high demand, and time sensitivity surrounding PPP loans created potential entry points for first-party fraud, or fraud committed by known customers (individuals and entities). Lenders looking to cross-sell or up-selling PPP client's new loan products should first understand the amount of first-party fraud exposure in their PPP portfolio. Understanding potential fraud levels will help avoid unnecessary reputational risk related to the new population of PPP-related commercial clients. Experian's Commercial Data Sciences team wanted to give lenders the ability to understand the amount of first-party fraud in their PPP portfolio. To start the conversation on the scope of fraud in the PPP program, Experian evaluated the publicly available SBA PPP loan data for the first round of PPP loans; these were public-only loans originated without a private guarantor. We anonymized and scored this dataset with Experian's newly developed Commercial First-party Fraud Score. The score measures the risk probability with a machine-learned algorithm to predict first-payment or early-stage defaults within seven months from account opening. Revealing elevated levels of fraud Scoring this public data revealed segments in some PPP lender portfolios with an elevated risk of first-party fraud, in some cases 10x to 20x riskier than the baseline. First-party fraud is a type of fraud where customers intentionally default on payments, either first-time payment or a payment sometime down the line. By examining the distribution of a lender's accounts as they fall within the score bands for first-party fraud risk, lenders can understand a projected dollar amount of balances to be charged off. They can also grasp the estimated dollar amount of losses per account or loss-prevention potential for the account if it had been reviewed (assuming reviewers catch 100% of fraud.) When dealing with first-party fraud, a lender's existing identity fraud prevention tools are typically unable to detect potential fraud. If underwriting relies on a point-in-time assessment, the lender would be blind to applicants' behaviors that may change after loan origination and fraud insights gained from evaluating accounts from other lenders. As a result, first-party fraud would be hidden in charge-offs, preventing lenders from identifying it for future analysis before marketing to their PPP loan population. Experian's Commercial First-Party Fraud Score helps lenders understand the first-party fraud risk of their PPP portfolio to limit future exposure for their new PPP population. Data visualization View the PPP dataset displayed in our tableau data visualization. Suppose you are a lender and concerned about fraudulent PPP loans in your portfolio. In that case, Experian can provide you with a Lender ID so you can assess risk levels revealed by the Experian Commercial First-party Fraud Score. View PPP Dashboard

Celebrating Asian American Heritage Month at Experian One of the great things about working at Experian is experiencing how much the company promotes inclusion and diversity and bringing your whole self to work. Working with people from different backgrounds and heritage enriches the organization because our team celebrates hard work and inclusiveness. Here in Business Information Services, we have many Asian American, Pacific Islander team members and we celebrate AAPI with them. We asked colleagues working in different parts of the Experian organization to send us a video clip sharing what Asian American Pacific Islander heritage means to them and here's what they said.  

Identity Fraud in Commercial Applications We recently sat down with two Experian experts to talk about commercial fraud trends and gain an understanding of why commercial fraud is on the rise, and what organizations can do to combat the problem while at the same time grant credit to growing businesses.  What follows is a lightly edited transcript of our interview. [Gary]: Hello and welcome to Business Chat I'm Gary Stockton with Experian Business Information Services, and today we're going to talk about Commercial Entity Fraud with two of our experts. [Gary]: Patricio HernandezBarron is a Product Marketing Manager here in Business Information Services, and he covers the commercial fraud space. Chris Gerding is a Consultant and he also focuses on commercial fraud. Welcome to business chat guys. [Gary]: The two of you recently collaborated on a perspective paper called Identity Fraud in Commercial Applications, and the piece asserts that there's been rapid growth in commercial fraud in the past few years. So, Patricio, if I could ask you, how are B2B companies affected compared to business to consumer companies in battling fraud? [Patricio]: Let me start by saying that both commercial and consumer or B2B or B2C companies are both affected by fraud, whether this is first-party fraud, third-party fraud, or synthetic fraud. They're both affected. Now, where it becomes different is the type of solutions that are out there in the market for them to solve it. There have been a lot more advancements on the consumer front, and it makes sense, consumer trends move a lot quicker compared to the commercial side of things. [Patricio]: But, in 2020, it's been considerably harder for fraudsters to get through the filters on the consumer side. So (fraudsters) being smart, they've started to focus on the commercial lines of business, which they already know that they're a little behind in terms of the sophistication of consumer lines. So, it's opened a potential opportunity gap for fraudsters to get through and businesses can't wait any longer. They need to raise their game and make that parity between consumer and commercial lines of business in terms of the fraud mitigation strategies. [Gary]: What's the scale and size of the problem of commercial fraud? [Patricio]: It's a big problem. A recent report published by the Association of Certified Fraud Examiners stated that 5% of business revenue was lost to fraud. 55% of respondents we asked said that as of 2019 fraud attacks have increased. So there's a clear problem right now, whether these businesses are recognizing these losses as bad credit or as fraud losses, that is the first thing that they need to focus on. [Patricio]: And the thing is, many of our customers would tell us, “we don't have a fraud problem”, but it was because they weren't recognizing and discerning between credit losses and fraud attacks. So that is the first thing that they need to focus on, start differentiating and categorizing those losses differently so they can start looking into it. The other thing that I'm sharing around this topic is many times businesses tighten their credit decisioning in hopes to reduce those losses. But that was counter-intuitive because they were making it harder for potentially genuine customers to make it through the application process. And yes, the fraudsters were passing this filter or no filters but were passing this credit scoring with no problem because they knew the data that would be required, and there were again, no fraud filters in place to stop them. [Gary]: So, Chris, can you talk about some typical scenarios in which businesses, especially small businesses are typically attacked by fraudsters? [Chris]: Small businesses and any business have a lot in common with consumers. There are modes and fraud scenarios where both are vulnerable. And businesses typically have both financial assets and competitive information at risk. They could be phished; they could be socially engineered, and this is exactly what we read on a consumer basis when we hear about how to avoid fraud. [Chris]: Second, leakage of sensitive information over the other channels can result in direct fraud, like account numbers, pins, obvious targets. However, they need to misrepresent their identity in many cases. And the contact information such as the firm name, the address, the owners, or officer's personal details, this kind of information when compromised leads to potentially bigger and harder to detect, harder to stop fraud schemes. Consumers can be defrauded like businesses, but these are the more big-ticket business-specific categories that you're seeing here on this slide. [Chris]: These three represent a good slice of the many ways businesses are defrauded and small businesses with some vulnerabilities associated with not having millions and millions to spend on fraud defenses would be vulnerable to some extent. The equipment financing and leasing firms can be defrauded either out of funds or especially vehicles and heavy equipment. We see cases not many in the news, but you do hear about these, where, if you pass the finance companies fraud screen, fraudsters can successfully apply for financing and potentially come away with, I mean, a car would be on the low end of this, construction equipment for or combined for major capital items. Then they disappear. [Chris]: Number two, fake invoices are a very easy way comparably to collect perhaps smaller amounts, but these can be forged documents sent in under the wire and they are paid sometimes by very busy accounts payable people with very few defenses in place, and something that we're going to talk about later,  fraud payments figure very largely in commercial fraud. Payments that are not backed up by good funds and intentionally sent it to cover a balance on an account are a very big part of commercial fraud.  Fraudsters may actually make multiple payments, playing the timing game so they keep the account and the account balance alive and growing, or the credit balance on the account so that they can perhaps get more from the fraudulent credit relationship that they've built than the intended credit line by this timing and submission of payments.  They can do this for several industries. They can do this for all different kinds of payment items themselves. They could be done with forged paper checks, electronic payments, and sometimes counterfeit payments themselves. [Gary]: Patricio, turning to you, would profit be impacted by implementing fraud prevention filters? I would imagine that would hinder some profitable growth? [Patricio]: It's a tricky one because, you know, there's this big misconception that by applying fraud filters, that's going to affect your profit or affect your number of applications going through. And it is true to an extent by applying fraud filters, you will see fewer applications going through. But affecting your profit, it's the complete opposite. It's actually going to reduce the losses that you'll be incurring, and I briefly touched upon this in your previous question, but what many companies do when they're not able to differentiate between credit losses and fraud losses, they tighten their decisioning in their credit applications. Those potentially good customers don't make it through, but fraudsters make it through with no problem at all. Because the decisioning system that they have for credit purposes does not do much for mitigating the fraudsters. [Patricio]: Many times, these companies don't invest in fraud solutions until they've gotten this big hit from a fraud attack, at that point, it's already too late. So, I would say that the best thing to do to help your profit is to be proactive because fraud can affect your profit if you get impacted. If you're proactive about it, you can protect or reduce those fraud losses that you're currently seeing as overall fraud, or losses that could be a fraud and not just credit losses. [Gary]: What's the number one step that commercial business, especially a small business can take to combat this wave of commercial fraud? [Chris]: Awareness must be built into the culture and it must be built into the solution and how the firm deals with the solution because there's no way to solve the fraud problem with a turnkey black box, turn it on, and forget it, we don't have that. And we may not have that for many, many years. [Gary]: Can you tell me more about the first payment defaults and how lenders are addressing that problem? [Chris]: We spoke a bit about payments in general as a fraud channel, but this is a particularly aggressive form of fraud or credit abuse. And it happens when the borrowing party just never ever makes one payment on the account. They may utilize the entire credit line and they just don't ever pay. So when the first payment is in default, there's a high suspicion that this could be a fraudster. There's a little ambiguity, as I said, but the credit and the fraud dimensions are rather close. They're rather parallel, in terms of how they are dealt with. [Chris]: What are we doing about accounts that are very brazen and do this on the first payment due?  We evaluate the risk at the time of enrollment. This is very important, we don't know, who's not going to pay us the first time. So we need a tool that evaluates, in this case, we offer a score, a commercial first payment default score, which is very high performance and very friendly to the combined mix of consumer and commercial data that a firm might have. Second,  it pays to look at the risk of the entire portfolio for first payment default periodically.  Again, is done with a score, it could be the same score I mentioned. In the third category, if it's necessary,  the host firm may wish to use scoring the individual payment item, the check, the online payment as a fraud evaluation, which is done by a different set of scores to manually perform systemic checks. [Gary]: So Patricio what are some of the most common misunderstandings in fraud prevention products? [Patricio]: Fraud filters will affect the number of applications that you are able to approve. As we mentioned before, it does affect the number of applications that you'll see come through, but it will help increase your profit by incurring fewer losses. Again, fewer fraudsters make it through equals fewer losses coming into your system. The second one would be that most fraud can be solved by verifying the identity of the user. And sure, it's because third-party fraud solutions are very popular, but that's not going to help you with all types of fraud. That's why you do need a layered approach for mitigating what's going to come through the door because, at the end of the day, you don't know what type of fraud you're going to be seeing. [Patricio]: By implementing a solution that will verify the identity of the user, that's not going to help you fight all types of fraud. In fact, stand-alone, you will do very little to mitigate first-party fraud and likewise with synthetic fraud. So again, if the way to solve fraud is not with a one size fits all approach, it's layered whether you have the resources and the capacity to implement a geolocation verification, or verify the validity of the data or verify the identity of the business owner. These are all things that are just going to prevent and help you weed out the different types of application fraud that you could see (coming) through the door. [Gary]: Chris, what can small businesses do to engage with Experian and minimize their fraud exposure? [Chris]: We love to talk, especially to small businesses on a very global scale in terms of their business operations and where it is that we might be able to help them. They may come to us with a great deal of awareness that they have a fraud problem and they kind of know where it is, but they look for a specific solution. Other small businesses may come to us with general concern. And in those, and in other cases, we are happy to sit down with them and do what I would call a free consultation and look at their information and make some suggestions. [Chris]: What we do is we offer solutions, but we like to add to that the knowledge of the particular client's situation, so that they become wiser and they become enabled by the kind of services that we provide, and they become enabled by the information we can bring to them upfront so they can make a wise consumer solution as it were. [Gary]: Well fraud in the payment protection program or the PPP program is all over the news. What do you make of that?  Are these fraudulent applications affecting lenders, even though the losses would be absorbed by the government? [Patricio]: While many of these lenders know and think that the loss of the potential losses would be absorbed by the government, the reality is that it's uncovering many gaps for these lenders. First, we understand there's a greater volume of applications going through their systems. So what many of these lenders have done is either turn off, completely turn off their fraud mitigation systems, or they've reduced the amount of vetting that they do, because they're not too worried because they know that the government is going to absorb those losses because of the volume of applications that they see. Now, the problem with that is that if they completely turned off the system, now they have potential fraudsters within their portfolio, or on the other hand, if they lessened the amount of filtering that they do, and yet still some fraudsters make it through, it's going to be very hard to weed out those fraudsters down the line. It's just putting more risk to your overall portfolio, and, people, once they're in there, they've already uncovered some gaps in your underwriting process. So again, just down the line is going to be very hard to weed out these fraudsters that made it through your portfolio, [Gary]: Chris, anything to add? [Chris]: That was a good summary. I would add only that the other side of the coin is when you put many, many tens of millions of good Government money into the hands of fraudsters, you're sort of inflating the entire credit system. You're allowing bad people to get what appears to be credit for good loans until they're discovered. Many of these will probably not be discovered. So you're kind of adding bads to the system and calling them goods. And that's never good for all of us. [Gary]: Well, this has been very helpful guys.  I want to say thank you very much for coming on Business Chat and sharing your insights.

Commercial fraud prevention causing unintended harm We often hear anecdotes from our clients about a recent string of bad debt, soliciting advice on how best to prevent future losses. Typically, with an increase in credit loss, maybe your natural reaction is to tighten up on credit evaluation criteria to screen out look-alikes?  In so doing, you can also impact the ability to grow, and in the process, exclude good customers by retooling your lending criteria, weeding out fraud. In our upcoming 15-minute Sip and Solve webinar, we'll explore whether tightening your credit score cards could unintentionally cause dozens, hundreds, thousands of small businesses not to receive the credit they deserve. Date: Thursday, April 22nd, 2021 Time: 10:30 a.m. (Pacific) 1:3- p.m. (Eastern) Session highlights Find out why misclassifying losses due to fraud as credit write-offs could impact your ability to grow your business. Learn more about delinquent small business credit behaviors versus small businesses looking to commit fraud. Discover how you can assess whether past charge-offs were actually due to fraud. Save my seat

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  

  In this Business Chat, we sat down with Experian's Director of Data Management, Ben Bargoil, and Cloudera Chief Customer Officer, Anupam Singh to talk about the data management investments Experian is making in machine learning and A.I, and how these investments are helping our clients. Ben, can you share a little bit about some of the data challenges we are having here at Experian? [Ben]: Most of the challenges we've been facing and working closely with Cloudera and solving over the last say two years have been in response to growing demands from the marketplace, right? What was considered acceptable even two years ago, in terms of data coverage and data accuracy, is no longer meeting our customers' needs in the marketplace. And add to that the legacy processes and legacy environment that we operated in, we're challenged with keeping up with the variety, the volume, and the velocity of data that Experian has, and that coupled with our previous approaches to data management, that weren't flexible enough necessarily to empower these new approaches. Right? Again, most of what we wanted to solve were related to how we can continue to do what we're doing but do it in a much more efficient, much more impactful way for our customers. Anupama turning to you; what solution did Cloudera prescribe to Experian to help us address some of these challenges? [Anupam]: Machine Learning is only as good as the data, and so the solution that we provided is a comprehensive solution called Cloudera Data Science Workbench. Yes, the more charismatic part of the product is that you can do Machine Learning apps and build neural networks. But in reality, where we saw Experian needed the product is things like data de-duplication, classification. So it is almost a prologue to the machine learning problem. So that's the solution that we provided. Ben, can you explain how these investments help Experian clients? [Ben]: When we were creating this new, these new approaches, and this new team, one thing that I was determined that I needed this centralized hub, right. I wanted a central hub in which we could build an entirely new ecosystem, and as we worked with the Cloudera team, it became obvious to us that CDSW was going to be our best choice. [Ben]:  So while we were investing in a CDSW, Experian had also been investing in our new technology environment, and putting those two together was the key to our success. Each one of these challenges has a direct line of sight to our clients. And most of them are based on direct feedback we've received from clients over the previous years if you will, and one of the great things that we've done inside of CDSW inside of the applications is measuring the impact to Experian customers. So we know confidently, we can state that millions and millions of customer interactions with our data have been improved thanks to the solutions we've built inside of CDSW. Anupam, did Experian have any unique challenges that stood out to Cloudera when we engaged with you? [Anupam]: Of course, with Experian, you know, I tell the team internally at Cloudera that we are all Experian customers indirectly, right? Anytime I'm going to buy something, Experian is in the workflow. So that always stands out for us. But the sheer scale of Experian, when you have almost a billion unique users that you're serving, you guys are one of the biggest Internet properties on the planet that nobody has heard of. When we were looking at the nomination for Data Impact awards, any small gains, 10% for Experian's actually a hundred million human beings on the planet, and so, that stood out for us. That's what got us excited about working with Experian on this problem, the sheer scale of it. How, how long did it take before you saw measurable results in working with the Cloudera solution? [Ben]: If you go back, let's go back two years ago when we were first creating this new ecosystem, and we first started our engagement with CDSW. There were the normal growing pains associated with a new environment, a new toolset, and a new team that we were onboarding onto Experian as well. So between the time we started working with Cloudera, it was many months until we had created a team, launched our first application, and started to make improvements to the database. Fast forward to today, we have many applications that have been created and launched in production, and the great thing is, this is very typical of most machine learning applications, you spend most of your time with the data, exploring, cleansing the data, creating the features you need to use within your machine learning application. [Ben]: But what we see is that the large bulk of the work, once we get to the point where we're ready to move into production through the combined power of CDSW and our new environment, we can make significant changes in a very short amount of time. I'm talking millions of improvements in a month or two months. To give you a good example of industry coverage, industry classification coverage, that was one of the challenges we wanted to solve was our customers wanted us to create more industry codes for businesses. So we spent many months building the application, doing all kinds of feature engineering. Within the course of about two to three months after we launched that application, I think we added somewhere in the 20 million range, new industry codes to our database. Again, lots of work on the front end, but as soon as we get into production, huge improvements in, in a short amount of time. What can you share about the Cloudera Data Impact Awards? [Anupam]: Our Data Impact Awards look for impact. We are all in the enterprise software business. Sometimes we forget what impact we have; if you have great fraud detection, you and I can safely shop on the Internet. We are talking today through some internet provider that runs its network management, and its network reliability analytics on top of Cloudera. For us, the Data Impact Awards are not just about our technology, but what impact we've had on the healthcare, banking, and telco systems of the world, of the world's government systems. That's how we measure, and it's fairly competitive every year. Can you share any criteria on what the judges looked for whenever they were choosing a winner? [Anupam]: What we look for,  is this real in terms of, does it have an impact or was it just a technology experiment? We found with Velcro, for example, de-duplication of records is one of the biggest problems in machine learning, and the scale at which Experian de-duplicated records, meaning, knowing which Ben is the right Ben when I'm looking it up is a very real problem. All of us face it as a consumer— the same thing with establishing a corporate identity. As somebody who runs a very large business for Cloudera, sometimes you don't even know what is the actual name of the customer. So the idea that you can resolve the name of a customer is a real problem. So taking these two or three real problems, we saw the level of impact that Experian was having on its customers, but more importantly, on its indirect, all the consumers in the world, and that stood out for us. Ben, what has the response been from Experian clients since deploying Cloudera?  [Ben]: Some of the problems and challenges we've been addressing are more behind the scenes, under the covers, like what Anupam just mentioned, improved entity resolution, improved structural integrity. So those may or may not be necessarily as overt as some of the other challenges we saw, like the industry classification example we mentioned, right? Adding all of those millions and tens of millions of codes to our database, our customers have a direct line of sight to that. We've received very positive feedback from the marketplace in terms of embracing these new approaches and being able to solve those challenges. I always like to say I'm not quite declaring victory on any of these challenges yet, but, you know, the end of the war is in sight on some of them. We've almost completely removed this as an area of opportunity, and we are meeting the needs of the marketplace. 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Michael Myers, Experian's Vice President of Products, assembled an impromptu roundtable discussion in March 2020 to discuss some of the key findings in a Forrester Study titled "Build Credit Risk Confidence Through Advanced Assessments." Mike is joined by Ann Skibicki, Sr. Director of Product Management and Brodie Oldham, Director of Analytics Consulting.  What follows is a lightly edited transcription of their discussion. Build Credit Risk Confidence Through Advanced Assessments [Mike]: Hi everyone. I'm Michael Myers. I am the Vice President of Products here at Experian Business Information Services and looking forward to talking to you today. We're going to share a number of findings from our most recent Forrester Research project entitled “Build Credit Risk Confidence Through Advanced Assessments”, and I'm joined today by Ann Skibicki, a Senior Director on our Product Management team.  We're also joined by Mr. Brodie Oldham all the way from Texas. He is a Director of Analytics Consulting here at Experian. [Mike]: All right guys, let's jump into it. We recently commissioned Forrester and ended up with our most recent study and what we want to do is share some of the key findings. Really the goal of the overall project was to get a sense of risk-based decisioning and what some of the firms in the industry's plans are around the future of their credit risk assessment practices. I'll start at a high level discussing some of the key findings and then with Ann and Brodie's help, we're going to dig into each one. [Mike]: So, finding number one, only half of decision-makers are very confident in their businesses, current approaches to risk management. The second finding, businesses struggle to deploy advanced analytics or automate account reviews, and last but not least, our third finding we're going to discuss today is most businesses are looking to a credit risk evaluation partner to evolve their risk solutions. [Mike]: Okay so, before we jump into those, let me just give you a little bit of background about who we talked to and their background firmographics. We certainly wanted to talk to decision-makers, so we went after those at the C level down through Vice President, Director Management. We certainly want to make sure they were part of this conversation and had an active role in it. So, we talked to everyone that was just considering starting this journey, those that were mid-flight of the journey, and those that had actually implemented some more automated analytic approaches. [Mike]: One more slide on the background. We needed to make sure we had a wide variety across the spectrum of company sizes. You'll see on this graph on the left, you know, really the sweet spot in that mid to large size company. But we also covered the small business micro-business even as well as some of the larger firms out there. And with that comes really a wide array of industry verticalization. Everything from what you see here on the top right, financial services down to the agricultural food and beverage industry. [Mike]: Okay. So let's jump into it guys. Finding number one only of decision-makers are very confident in their business’s current approaches to risk management. Ann let's start with you. Give us your, take some of your thoughts. [Ann]: Uh, sure. Mike. Yeah, I think that that is interesting. But I think you do have to dig in a little bit further by the client's evolution as to where they're at in the adoption of advanced analytics and decisioning to really make meaning of that stat. You'll find that the folks that are actually adopting advanced analytics and decisioning are already on their path, are much more confident, almost twice as confident as the folks that have not implemented or have no plans at this point to implement. [Ann]: So I think there is something interesting to be said there about the level of competence that folks are having with their processes and advanced analytics, particularly with the folks that are already adopting. Brodie anything to add? [Brodie]: Well, sure Ann. As I've looked at this and we've talked to clients and part of the engagements that we've had, we find that a lot of times that confidence that they have has pulled back a little bit because they lack some of the automation there. We look behind the curtain, and we see it. What they end up with are inconsistent decisions. And so, what we're trying to do is give them a pathway or a framework to work with, and Forrester really showed us that they needed that. Some of the things that they need are a strong benchmark to start, you know, where they're really going to start their path. Those advanced analytics that you talked about are important, we have new methodologies that we can deploy and then a place to deploy them.  Really that decisioning platform is super important for their confidence. [Brodie]: So when they come out for that progression and for the performance to be there, they really need to have that confidence to progress their sales cycle, and we see that those that don't have that plan to implement. Only 12% of those folks really, they're not planning to grow. 12% of those that are planning to grow in the near future really aren't going to grow. So we found that in the Forrester study, it's very exciting to see. [Brodie]: But when we look at those that are really having some success. I know Mike in the Forrester study some of the things, there were some key points that we found that were helping some of those that are really pushing forward and pushing that limit to overcome. What are some of the challenges that they might be facing? [Mike]: Yeah, got it. Couldn't agree more Brodie and thank you both. Great insights on that first finding. Tell you what, let's jump into the second one. Finding number two, businesses struggle to deploy advanced analytics or automate account reviews. Let’s start with you Brodie, but I'll add a little bit of my insight on this one too. [Mike]: In my experience with our prospects, and with our clients, you know, account reviews are often overlooked, especially when the economy is doing as well as it is. You know, everyone's focused on origination, opening accounts, but they tend to forget the need to really focus on account reviews and really managing those accounts. So, Brodie give me some of your thoughts. [Brodie]: When we're looking at the Forrester study it really highlights what we've been seeing with our clients. We know that some of the strategies that we've been taking are implementing some of these more mature methodologies, more advanced cutting-edge methodologies for Machine Learning, and in our processes for an account review, even originations, but account review especially. We've seen lift over those tried and true logistic regression type models with our new Machine Learning models — 12% 15%,17% plus percent. So really some great value that's being added in these Machine Learning type models. [Brodie]: The hardest thing that we see with our clients is being able to install what we have here in this new methodology into the process, so into their account review process. With some of the new microservices that we have in place, we can deploy those. We have sub-second turnaround times with the new methodologies that we have. Which is really industry-leading, and it takes us into a place where our clients can deploy either models that we've built for them or models that they've built themselves and deploy it here at a significantly lower cost and they can really do it themselves. I know Ann, some of these, when we talk about implementing a key to that is data. Do you have some points that you want to make on that? [Ann]: Yeah, I was going to kind of bring it back to the fundamentals because when I read the study and looked at the results for me, a couple of things stood out. Not only were our clients and their survey respondents struggling with IT budget and system constraints, which I think we would all agree is a challenge across the board. What I thought was interesting was that they're having data quality challenges and that was across the board. Whether they were just starting to implement or if they were on the path of implementation. Everybody seemed to have really the same challenge with standardizing the data, finding good fill rates of the information of where the data's not complete or even the data privacy issues.  I'll say in working with some clients recently, I would definitely agree with this. You know, data standardization, data quality, especially with data and multiple systems becomes pretty challenging. And then you really want to leverage that information, right? Unlock the power of the data to be used in the advanced analytics portion, whether it's for portfolio management or new account acquisition. It can be a definite challenge for sure. [Mike]: Great job guys. You know, I just want to add to that too. I think you both hit on some key points. ML, Machine Learning, A.I. buzzwords, right? Really hot in this space right now. It’s really important not to forget what problem are you trying to solve, what are you trying to accomplish, and then how can you go about doing that? I think Brodie, you outlined some really good points of hey double-digit lift. That's no joke. How can we at Experian possibly help you implement that? And we do have a number of ways and a number of analysts that are really experienced in just that. [Mike]: So, bringing it back to your point too, Ann, it's easy to forget some of the basics, tie that together and you really have a compelling proposition. All right guys let's go to the third and final finding from our Forrester study. Most businesses are looking to a credit risk evaluation partner to evolve their risk solutions. Ann why don't we start with you. Talk to me about this finding. [Ann]: Yeah, I thought this was interesting as well. A very strong call to action for me. I saw that with our clients and respondents, this is not necessarily an emerging need. About 75% of the respondents are taking immediate action within the next 12 months. So, I'm happy to see that folks are definitely starting to adopt these new methodologies, are really looking at ways to transform their business. And that is happening right now at the present time. I'm sure Brodie, you're probably hearing a lot from clients working in the analytics space of folks that are looking to us maybe want to share some of your insight. [Brodie]: Well, they certainly are Ann, the way that we're really drawing this in to show the value they're there, they get the feeling that they're on the cutting edge and we really want them to see that, and as our clients move forward with us in partnership, to build out their account management and even their origination systems, as they're including some of these Machine Learning and advanced techniques into their processes. It's not just the performance that they're getting here, as far as their numbers and the dollars that they're earning, but their sales teams are getting that lift as well. And I like to call it the swagger factor. So, you mentioned a little bit earlier, you know, in this Forrester study what you're going to see is that swagger factor, which is up about a 200% increase in that confidence level that our clients are really feeling here. [Brodie]: When we look at those in this study that didn't feel like they had a good onboarding process, about 28% didn't in the group that wasn't going to implement in the next two years. So there are groups that are waiting to implement or looking out in the future to take these next steps into Machine Learning. The ones that are doing it more quickly in the next six months or so, 85% of them feel like they're really on the cutting edge. They're moving forward, they're going to have great sales and growth in the next six to 12 months. That's where the swagger factor comes in. This really reinforces the good value that we're seeing in a partnership with Experian. And Mike, can you tell us a little bit about how to get some of this information? [Mike]: Yeah, you got it. Brodie, thank you so much. We can help you. Let us help you increase your swagger factor, but first I just want to say thank you, Brodie, thank you Ann for joining us today. Really what we have available is a copy for download of this Forrester research study. It's available over on experian.com so please join us there and we'd love to talk to you further. We do have quite a bit of experience as you heard from Ann, Brodie, and myself today, and we'd love to help you on this journey. Thanks so much for joining us today. If you would like to download a copy of the full report visit our credit risk assessment page. Forrester Credit Risk Assessment

New Experian Report: Beyond the Trends Experian Business Information Services is excited to present our new quarterly report "Beyond the Trends." In this report, we'll be evaluating challenges to particular industries. We'll be looking at account management, pre-treatment, and treatment strategies for small businesses coming out of COVID. The Winter edition has just been released, download your copy below. . Download Report