In my current role as Senior Content Marketing Manager, I work with Experian product and data experts to drive awareness and demand for our business data, analytics, and enterprise credit solutions. As the host of our Small Business Matters podcast, I love to interview people, write articles, host webinars, and generally create a wide variety of content.

-- Gary Stockton

All posts by Gary Stockton

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Today we are celebrating Veterans Day in the United States. With deep gratitude for their service and the many sacrifices made for our country, Experian salutes Veterans across the country, and around the world, and we extend our warmest wishes for a Happy Veterans Day.   So, where are our Veterans?  Well, according to the U.S. Census many of our Veterans  are located in Montana, Wyoming, Virginia and Alaska. [Source: U.S. Census Bureau] Veterans Day originated as “Armistice Day” on Nov. 11, 1919, the first anniversary marking the end of World War I. Congress passed a resolution in 1926 for an annual observance, and Nov. 11 became a national holiday beginning in 1938. President Dwight D. Eisenhower signed legislation in 1954 to change the name to Veterans Day as a way to honor those who served in all American wars. The day honors military veterans with parades and speeches across the nation and a remembrance ceremony takes place at the Tomb of the Unknowns at Arlington National Cemetery in Arlington, Va. The ceremony honors and thanks all who served in the U.S. armed forces. Did You Know? 18.2 Million The number of military veterans in the United States in 2017. 1.6 Million The number of female veterans in the United States in 2017. 50.0% The percentage of veterans age 65 and older in 2017. At the other end of the age spectrum, 8.9 percent were younger than age 35. Veteran-owned Businesses in the U.S. In the US there are around two and a half million businesses that are majority-owned by veterans and growing. Veteran-owned firms have receipts in excess of a trillion plus dollars, and annual payroll of almost $200 billion. These are not insignificant figures as Veteran-owned small business owners drive to succeed in their business while supporting job growth. To perform well they need continued support and commercial credit can be an invaluable tool to an emerging business and its longevity and stability in the small business development.     Veteran Strength Experian commercial credit data on Veteran-owned businesses highlights remarkable similarity between veteran owned businesses and the industry overall in terms of sales, commercial credit quality, indebtedness, and credit utilization.   Stability Veteran-owned businesses typically employ more people, and show remarkable stability in terms of commercial risk and delinquency. Most Veteran-owned businesses are small and emerging. A positive trend in small business launches in recent years has resulted in a downward trend in the statistic below as more small businesses emerge in the 1-4 employee range and work to grow and survive in market. Avg. Owner Employee Size Infogram   Infogram Veterans who own businesses in the US are an average of 4 years older than their civilian counterparts, and are 10% more likely to own homes. The strength of the housing market in the past few years has given small business owners the ability to source equity from their homes to strengthen their small business and to thrive. Veterans are applying the tools, learning, work ethic and dedication learned from their military service to build stable businesses that support employment and the small business ecosystem.  We expect credit performance in the U.S. to remain strong in the short term but signals of approaching resets could change and impact the market in the short term. Veteran-led businesses will continue to charge forward and remain a vital part of our economy.    

Published: November 11, 2018 by Gary Stockton

Experian Business Information Services recently introduced a powerful new marketing platform called Business TargetIQ. Product Manager, Kelly DeBoer answered a few questions about the product and described use cases that promote greater collaboration between credit and marketing departments. What does Business TargetIQ do? Business TargetIQ is our new marketing platform so it's a B2B marketing platform where clients can access data for marketing applications. How is it different from other business marketing platforms? It is unique in that it not only includes your standard or core firmagraphic information but also includes Experian's credit attributes. Does it have credit data? What does that mean to marketing or collaboration? Typically marketing data and credit data are housed in separate silos of information. With this tool the information will be combined together which will allow the tool not only to be used in traditional marketing applications for targeting but can also be in that risk factor which applies to different divisions within our client's applications or use cases of the data. Who would most benefit from Business TargetIQ? The thing about Business TargetIQ is it truly applies to all different verticals, as well as all different contacts within the company. So whether it's a financial vertical or a trade vertical, retail, just across the board all clients can utilize this. Anybody that's doing marketing can utilize this platform. What core problems does Business TargetIQ solve? It solves a lot of different problems, so, the most common client issues that are brought to our attention are gaps in data, as well as in the marketing initiatives. So they may have data in-house but they have holes within the data. Our tool will allow them to not only upload their client records and fill in a lot of those gaps that they may have, whether it be contact information, or firmagraphics or address information. It will standardize that data and fill in those gaps. But will also provide the means to again use that data. Our business database which has over 16 million records. They can then utilize that information for prospecting, for data append, for analytics, for research applications, so it solves a lot of problems with regard to marketing and data concerns. How does credit data help with prospecting? So what we find is clients come to us and they may say you know I have an idea of what our clients look like, they're in this SIC or in this industry code, or they have this sales volume or employee size, but what they may not know is on the back end which really helps identify and target those businesses is the credit attributes, so the risk factors around those. So do they have delinquencies in their payments? Have they filed bankruptcies? Do they have UCC filings? So it allows them to take it that next step and not only really define what their clients look like, but identify clients that look like that. Learn More About Business TargetIQ

Published: November 5, 2018 by Gary Stockton

As a Senior Consultant with Experian Advisory Services, Gavin Harding works closely with many of Experian's FinTech and Financial Institution clients to find solutions to complex problems. We sat down recently to talk about bank partnerships, how they come about, what makes them successful, and how Experian supports them. Do you see a lot of collaboration between banks and FinTechs? The latest statistics show that 67 percent of banks and FinTech’s are either currently cooperating, or in discussions about cooperating, or exploring collaboration. So, yes a very significant proportion are considering collaborations. Why collaborate at all? You know it's interesting, they have different skill sets, different assets, different backgrounds. So for example; banks have really deep, broad customer relationships. You know think about your Mom or Dad bringing you to your local bank to open up your first account. Think about your student loan. Think about your mortgage. What kinds of relationships exist? So banks have really deep and broad relationships. But traditionally the experience with banks has not necessarily been great in terms of turnaround, in terms of the friction or pain involved in getting a loan or opening an account. On the other side, FinTech’s are really good at that customer experience. They describe it as either low or no friction. So very quick turnaround times. But they're very much transactional-focused, meaning single products. So FinTech has the technology and the experience, and banks have the depth of relationships with customers. You bring those two parts together and you've got a pretty amazing potential opportunity.  There are as many relationship types shapes and sizes as there are people on the planet. Everything from cooperation on basic operations, meaning, a FinTech takes applications for a bank and then passes them on. All the way over to full-fledged integration of systems, personnel, capabilities, skill sets, and so on. So pretty much the broad spectrum. What works well? So it works really well when they are well-matched. So what I mean by that is, when the skill sets from one organization match the other. When one enhances the other, and it works really well when there are long and detailed discussions and preparations for the relationship. Meaning, they align and discuss goals, objectives, what each organization's role is, what each brings to the table, and very specifically how they are going to cooperate. What are the pitfalls? Well, the same pitfalls. So the pitfalls are that the relationship goals differ, or aren't aligned, or that one organization feels like they are bringing more to the relationship and that the partnership is equal, or when it feels as if each partner, each organization is not getting value from the relationship over time, and once again that reinforces the need for those detailed discussions before getting into that partnership or relationship. How does the process work? So it begins with a discussion. I've seen these partnerships start with a discussion over dinner at a conference. I've seen them start through a LinkedIn connection. I've seen them start over coffee. So it really starts with an exploration of who's out there? What organizations may be interested in even discussing some kind of collaboration? So it starts with the conversation at the very basic level, even when we see in the Wall Street Journal major strategic alliances between organizations, starts with people, and starts with that very simple conversation and connection. What are some key elements to be aware of? Well again it comes down to what each party brings to the relationship and what the goals are. So a good alignment of the capacity of skill sets, an alignment of investment in terms of time and resources, and very specifically a definition of who does what, what the accountabilities are, and what everybody's expectations are. They are fundamental to the success of any type of business arrangement or partnership. How does Experian support these partnerships? So the interesting thing is we have very deep relationships with both sides. So we bring data, solutions, consulting expertise to FinTech’s and to banks. So, it's really interesting we find ourselves in the middle of a lot of these conversations, and how we help is by understanding systems, technology, data, the best of both organizations involved in the conversations, and how to bring all of that together for a good focused efficient successful outcome. A couple of years ago this was new meaning that banks saw FinTech’s growing, and kind of looked at them a little bit maybe as competition, as potentially the enemy, FinTech’s saw themselves as disrupting the world and completely innovative and new. What's starting to happen is both sides are coming together, realizing that they are both part of the same financial industry, serving the same customers, maybe in different or new ways with different products. But in the same industry. So there is very much a coming together, an alignment a co-mingling, consolidation of all these various aspects of the industry. And I think it's really positive for consumers. More products, more quickly, and a better experience overall. Do you think a FinTech's ability to create more dynamic mobile experiences is a key element Certainly and so the big question we help banks answer in this space is, do we build it? Do we buy it? Do we partner? and build and buy or partner refers to the technology the infrastructure and the experience. So if you have a pretty big bank and they've got a old website, old process, lots of paper, lots of regulations, lots of pain in the process. Well they can look at one of the more advanced sophisticated mature FinTech’s and essentially use their platform, their engagement, their data, connect that to the bank's customers and in a very very short time transform that experience in a very positive way for their banking customers.   Learn about FinTech Lending Solutions

Published: November 1, 2018 by Gary Stockton

We sat down with John Krickus, Senior Product Manager for Experian's Scoring solutions to ask about the new Social Media Insight, and how this data and score are being used to help businesses strengthen scoring models, and create opportunities for emerging small businesses with limited credit history but strong social media profiles.  What is Social Media Insight? We're very excited to bring what we consider a breakthrough capability. Social Media Insight is an expansion, a use of new information beyond traditional credit data, that both improves the performance of our scores, provides attributes to our clients, and is directly sourced from the social media providers - no screen scraping. What type of social media data is used? So the social media data comes from sources that, like with our other data sources, we are not allowed to publicly disclose, but we are focused on business social media sites. So we're not going after consumer social media data, but social media data from business-oriented sites, so that we can better evaluate small and midsize businesses. What steps are taken to prevent artificially boosting the ratings of a business? So that's a question that we often receive about artificially boosting ratings. We work with social media companies, they have many techniques to identify where the reviews are coming from and to prevent someone gaming the system. Is it 100 percent full proof? No, but it is very effective. How effective has social media data been in predicting risk? As we've seen with using the data in our scoring solutions, we've seen a tremendous boost in score performance. There have been two real gains from using social media data. First is, we've developed about 70 social media attributes. We can now include those attributes and make these attributes available to our clients to improve the performance of risk scores. The second area really devolved from client feedback as we piloted the data. They indicated to us that there were social media data elements that are very helpful. So, we've been able to attain information such as pricing, parking situation, hours of operation, and those additional data elements have also helped our clients in improving their risk performance scores. What type of data do our clients get with Social Media Insight? We're able to provide our clients one of three types of data. First, we can provide a social media IntelliScore. That's our normal IntelliScore with commercial data, and now social media data. So, you get a higher performance. We've boosted performance by 37 percent with our IntelliScore. Second, we can provide those same social media attributes to our clients. So, they can incorporate those social media attributes into their scoring models. And third, we have the descriptive data. I mentioned hours of operation for example, social media data also provides a better description of the business. So, you just don't get an Exercise Gym, you get whether that gym is kickboxing or whether that's just exercise equipment. Can I target specific kinds of businesses? Can it be used for Marketing? We do have the ability to use social media data for identifying better businesses to do business with. Our initial focus though is in developing the attributes and the score for risk management. So that's really the focus for this first phase of Social Media Insight. How might Social Media Insight help an Insurance company? Insurance companies have been very anxious for this data, and they're getting a different view of the business. We're going beyond traditional trade, public record, background information, and now we're able to provide a view of how long has that business been rated? How are the ratings? What's the trend in the number of ratings? So, it's not just your level rating, but are you getting reviews over time? All that information provides a really unique view of the business that we've never seen before. How can Experian clients access Social Media Insight? Our clients can access the data one of two ways. We can provide a batch file. So, if you have a portfolio and you want to add social media attributes and a social media score to that you can provide us a file in batch. We also have our new API access, and we're very excited about that. So that allows you online real-time access to obtain the social media insight data, and it's very easy to program to. Can Social Media Insight help emerging businesses gain access to capital? Yeah that's an excellent area for Social Media Insight. It's really the newer smaller businesses that don't have a very deep credit history, that Social Media Insight now provides a view that previously it may have lacked information, therefore, credit may not have been extended. Now by having a social media site data available. We're adding depth of information to that business. We've actually found that businesses with social media data, as a group, are less risky than businesses without. How does Social Media Insight help improve risk model performance? So, the view that the social media data provides, we have found has boosted model performance, more than doubling model performance for those new emerging businesses. But even for established businesses we've seen double-digit gains in the measure of performance for models such as KS, and again you're getting a view of a business, number of reviews, and we normalized that. So, if you're in an area that's very active with social media data we take that into account. So, if you have 10 reviews in your history, which are in a very active area, you may not get as much of a positive as if you had 10 reviews and a less active social media area. So that combination really boosts performance and predictiveness of the data. How do Social Media Insight help our clients reduce risk? And really that's been one of the biggest breakthroughs with the social media data. Is by being able to boost the performance as I discussed earlier on KS, those new to the world businesses. They now are able to more confidently make decisions in their portfolio, because there is now a wealth of information. They're able to improve their models with this new additional information and have a very good performance improvement with it before and after. So, there's an across the board performance improvement. How does Social Media Insight help to automate the decisioning process? When you have an automated system, you want to have a higher level of confidence. The higher level of confidence you have, the stronger you can, for example, having automatic approve and automatic reject areas. By adding social media data we're able to get a stronger KS performance, which means you have more confidence in the models, and you can now increase the percentage your portfolios that you're putting through either automated or highly automated decision making. It's a significant boost in performance however you cut it. We're very excited about this unique new information source. Social media data is totally different from any other business credit information that's available, and when it's utilized in a model, in a decisioning system, the gain in performance are dramatic, and we're very excited to bring this capability to our clients. Learn about Social Media Insight  

Published: October 15, 2018 by Gary Stockton

For utility companies, the customer onboarding process can sometimes be a complex, time-consuming, and unpleasant experience, especially if a manual credit decisioning process is in play. Every time a customer interacts with your utility company — be it via the website, telephone, in-person service call, mobile app, or social media — their experience sets the tone for the overarching relationship between the customer and your company. To improve the onboarding experience, many utilities are turning to machine learning to make faster and simpler credit decisions. However, creating a custom machine-learning decisioning engine is complex and can be costly. By leveraging machine-learning capabilities through Decisioning as a Service (DaaS) offerings, utilities can automate the decisioning process and create a frictionless customer experience. For example, a customer applying for service – even with a large utility — can be approved within seconds by an agent using a tablet. Using DaaS to Automate Your Credit Decisions DaaS can be used for many different types of decisioning — prescreening, prequalification, or instant credit. Utilities also use DaaS for authenticating and resolving identities and assisting with the rationalization of deposits.  Other uses include improving the customer experience, credit line management, retention, cross-selling and collections optimization. The process is like using traditional decisioning methods where the customer or customer service agent enters the customer’s information into the website or system. The utility system then connects with the DaaS engine through an Application Programming Interface (API), The DaaS engine then aggregates real-time data from the credit bureaus and other data providers about the customer, runs them through business rules — and a decision is rendered. The decisioning engine uses rules and algorithms to create predictive models for credit, fraud and, bankruptcy risk, profitability, retention and other key areas. The DaaS engine then automatically determines the results, such as approval, decline, instant pre-screen, cross-sell, or a collection decision. More than just providing a result, the system helps your utility know exactly how to treat the customer based on their risk level. DaaS also helps utilities by customizing offers that deliver both business value and value to the specific customer.  Additionally, the algorithms are continually updated so your decisions are always based on the current business climate, market drivers, and regulatory conditions. Creating a Seamless and Personalized Customer Experience From the customer’s perspective, the process is simple and seamless. Instead of waiting for hours — or possibly days — the customer receives an answer in real-time. If the decision is good news for the customer, they can move on with the process. And if the decision is not what the customer was hoping to hear, they can quickly move on and determine their next steps. There is no waiting, wondering, or anxiety. Using DaaS also creates a more personalized experience for the customer. DaaS recommends the next best step based on the customer’s specific situation, which is an informed way to begin your relationship and sets the right tone for the future. For example, DaaS may recommend no deposit based on risk-level, or a specific product or offer of value to the specific customer. Improving Operational Efficiency and Growing Revenue In addition to more loyal and satisfied customers, your utility company will see operational benefits and lower costs from using DaaS. Your employees no longer need to manually process credit applications and make decisions, thus eliminating paperwork, tasks, and time. Because DaaS provides centralized decision making, you can use the technology across different enterprise frameworks, call center environments, and processing systems. This dramatically increases your efficiency by eliminating manual processes which give your employees more time working to improve the customer experience. Because the process is more accurate than the traditional credit decisioning model, utilities can make better credit decisions. As a result, your utility can significantly reduce bad debt and fraud, which improves your overall financial health. At the same time, you can increase revenue by approving customers who are good credit risks but may have been denied using a manual or out-of-date decisioning model, and thus improve the customer experience. Additionally, your ability to more effectively cross-sell customers will help grow your revenue. Your utility’s success depends on its ability to make quick and accurate credit decisions while also providing a positive customer experience. By using an API to integrate DaaS into your systems, you can have confidence you are making accurate decisions while creating customer loyalty, improving revenue, and reducing costs. It’s simple, it’s easy and your customers will love it.    

Published: August 13, 2018 by Gary Stockton

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.

Published: August 6, 2018 by Gary Stockton

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.    

Published: June 29, 2018 by Gary Stockton

All business customers are not created equal. Even companies that look solid at first glance can hide festering problems that eventually can impact your bottom line. Successful credit management requires you to carefully evaluate the financial health of every business that asks for credit terms. Here are 5 questions you should be able to answer before extending business credit: 1. Is the business what it claims to be? Sometimes, companies needing credit will provide inaccurate information to win approval. Before opening an account, you need to confirm the applicant‘s bona fides, including its location, size, number of employees, annual revenue, years of operation and similar financial indicators. 2. What is its payment history? Although past performance does not guarantee future results, a company’s payment history is often a strong indicator of how it is likely to behave in the future. Pulling a business' credit report can easily provide you a snapshot of a company's payment history as well as other risk measures.  3. Are there hidden factors that could affect its ability to pay? Are there pending judgments, lawsuits, bankruptcies, regulatory citations or other “red flags” that could make it difficult for the applicant to meet its obligations in the future? This is another area where a business' credit report will be a key factor in helping you uncover a potentially risky business.  4. How much credit should you extend? All credit contains an element of risk, but you can mitigate that risk by limiting the amount of credit you extend based on factors such as the customer’s sales volume, debt to-asset ratio and similar aspects. 5. Under what terms should you extend credit to this customer? You can mitigate risk further by carefully calibrating the combination of interest rates, minimum payments and other contract terms based on each customer’s individual financial metrics.  

Published: June 21, 2018 by Gary Stockton

You likely go to great lengths to protect your own identity from fraud and theft. But are you actively protecting your business’s identity as well? Even more importantly, do you make sure you are not doing business with fraudulent companies that have been victims of identity theft themselves? In many ways it’s harder to protect your business identity than your consumer identity. Information about most businesses is publicly available – and as easy to find as a simple Google search. Because businesses self-report much of their own information, it’s easy for a thief to add their name or address to a company. To make it even easier, many businesses do not protect their EIN the same way as they secure their SSN – which they should. At first glance, you may think having your personal identity stolen to be more damaging than a business identity. But in fact, the opposite is often true. Business owners often personally guarantee loans, even if the loan turns out to be fraudulent. And then if a business must close its doors due to the losses from the theft, the business owner now has no income and must repay the loan. How Business Identity Theft Happens Some thieves steal business identities by purchasing a shell corporation. Others take over a company’s data. But regardless of how the left happens, the criminals often go to great lengths to mirror the company. Some even rent space in the same building as the original company and using the same suppliers. At this point, the fraudulent company can start physically intercepting deliveries as well as applying for loans and credit, posing as the original company. Criminals start with one piece of information that is real, such as an address or EIN number. And then start operating as if they are the company and changing the data. Criminals often wait patiently while building up their reputation and credit history, then “bust out” with a large amount of fraudulent activity in a short period of time, and then walk away before they are discovered. Protect Your Own Business Identity Business owners must constantly monitor their business information to spot red flags that criminals have taken over. The earlier the theft is discovered, the less damage that occurs. Here are three things to look for to spot business identity theft of your own business: Look for new addresses added. Check your credit reports and government filings to verify the address. One of the first signs of theft is often a new address added to your business information. Verify that new registered owners have not been added. Thieves will often add a new principal — CEO, owner or partner — to the list of owners. The criminals can then conduct business as if they are an owner. Check business accounts daily. Use online banking — which also reduces the risk of stolen paper statements — to look for any transactions that you or your employees did not make. Consider setting mobile alerts for suspicious transactions to spot issues even faster. Verify Your Customers are Not Fraudulent Companies Before doing business with a company, do a business verification by making sure the company is who they say they are and not a and not a fraudulent company. Since verifications cost time and money, take each customer on a case-by-case basis regarding how deep to dig. If a customer orders $100,000 worth of computer equipment, you should do a more thorough investigation than for a business ordering a single $500 laptop. However, anytime you are extending a line of credit to a company, you should deep dive into a companies' history and data because you are taking on a high risk. Stacking loans is a common tactic – meaning companies take loans from multiple companies at the same time. Because many companies often verify customers by looking at their relationship with the business, they are verifying in a vacuum instead of seeing the entire picture. By using databases and tools that provide a holistic view of all activity, it becomes much easier to find the fraud. Here are five things to look for when verifying a company: Verify the EIN number. One scheme is to use a different EIN number and have all other pieces of information the same. Make sure the company you are doing business with is using the same EIN number as the legitimate company. Consider the number of open lines of credit. Because fraudulent companies often open multiple lines of credit at the same time, determine the current amount of open credit. Multiple large lines opened around the same time can be a red flag. Look at the number of sub-companies and activity between the companies. Criminals often set up a fraud ring by operating as sub companies underneath a single company. The “companies” then loan money to each other to boost credit scores and credibility. Note for periods of dormancy. When a business identity is first stolen, the criminals set up the company and then go dormant to build credibility through age. The company will then “bust out” by making a lot of transactions very quickly with multiple companies. Look for additional addresses. Check to see if the address you have been given is the same as the company’s headquarters. Multiple similar addresses can be a red flag. As business identity theft continues to rise, you must keep your eyes open for signs of theft — both with customers and your own business. A single credit check or google search simply isn’t enough. You owe it to your business and your future.

Published: June 5, 2018 by Gary Stockton

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