Three Ways Scammers Use AI to Steal From the Unwary

By Robert L. Cain, Copyright 2023, Cain Publications, Inc.

Never was there a new technology that scammers didn’t figure out a way to take advantage of to rip off the unwary. Imagine their joy today. Scammers hit the goldmine with Artificial Intelligence. They have come up with ways to scam not possible before, ways they couldn’t have dreamt about five or so years ago. By the time we’ve figured out how to stop them, millions of people and businesses will have been scammed out of billions of dollars.

We’ll look at three different Artificial Intelligence “techniques” scammers use to steal money from the unwary: voice cloning, prompt injection attacks, and phishing.

Voice cloning

Numerous sites on the internet provide apps for cloning anyone’s voice. They market it as having fun with your own voice. For example, suggests “generating faceswap videos, photos, and GIFs. Over 150 million users make funny face swapping here, including movie role refacing, gender swaps, face memes, etc. Spoof your friends now!” Yes, “spoof your friends.” How about spoofing people into sending you money such as with the notorious “grandparent scam.”

Before voice cloning, they had to just hope a grandparent didn’t know for certain the sound of the voice of his or her grandchild. The scammers would call the grandparent pretending to be a grandchild, usually a grandson, saying he’d been arrested, had been in an automobile accident, or some such and needed bail money right away or he’d be put in jail for who knows how long. They instruct the grandparent to either go to Walmart and buy sufficient gift cards, wire money, transfer it using Zelle or Venmo,  or go to the bank and withdraw money and somebody would come by to pick it up. That last one is the most perilous for scammers, of course, because a suspicious grandparent who spotted the scam could have police waiting for the pickup. With voice cloning, one possible snag had been removed. Scammers can download as little as 10 seconds of someone’s voice from a social media site such as Facebook or Tik Tok, and clone their own cloned voice into the grandson’s. For the unwary, terrified grandparent, it works.

The cost of using voice cloning? “premium” service is $9.99 a month or $49.99 for the first year, going up to $99.99 after that. Other sites are just as inexpensive. advertises a free trial with up to 30 minutes of synthesis time and $20 for four hours.  Others are equally reasonable considering the thousands of dollars scammers will extort from the less-than-suspicious.

Voice cloning works for more than just the grandparent scam. Politics. Considering how much politicians talk, it’s simple to download that voice and have it say anything you want it to. Especially right before an election, imagine the words they could put in a politician’s mouth too late to have the ad or news release cancelled, but not too late for people to believe what they heard the “politician” say.

Businesses aren’t immune, either. Scammers can clone the voice of the owner, CEO, Executive Vice President or some other high-ranking person whom an employee wouldn’t dare disobey or question, and get passwords or other means of accessing company servers. The result could be a ransomware attack or access to company bank accounts.

Injection attacks

These pose equal danger to a business or individual. The example used “You feed an AI chatbot, like the Bing assistant, a prompt, like ‘Hi, can you find me a cheap flight to Madrid in May?’ And Bing finds you a cheap flight.

Enter the hacker looking to slither his way into your convo and pocketbook. He’s already injected a prompt of his own into a website that you happen to have open in a separate tab. No one knows the prompt is there — not you, not the website owner. That rogue code jumps into the Bing chat box like a flea and hijacks your conversation.” Consumer affairs reports that programmers at GitHub engineered a virus to impersonate a Microsoft employee dealing in cheap laptops

Phishing Attacks

Then come the phishing attacks. With Artificial Intelligence software, a scammee doesn’t even have click on a message. As soon as someone visits an infected website, that person’s computer or phone is infected by code that had been injected by a scammer giving him or her access to all the information the unsuspecting person’s computer, bank records, Social Security number, and with the ability to bleed someone’s bank accounts dry. How do they inject that code? Artificial intelligence alters the source code of the website just like in an injection attack. And no one could ever see the code if they looked because the scammer writes the code in white type on a white background. It only takes a few line so even the most wary programmer would think it was just a space in the code, a line break maybe.

Phishing attacks have risen exponentially in the past year or so, showing a 47.2 percent increase since 2022. For some reason, education has been targeted most with an increase of 576 percent since 2022.

How do we protect ourselves? First, trust nothing you see or hear until you verify its accuracy. Second, never, ever send cryptocurrency, buy gift cards, or use some other untraceable method of payment. Third, be wary of voice quality with no background noise. After all, the scammer is alone calling from an empty room, not  police station. Fourth, listen for inconsistencies in the information provided, and ask questions. Several places also suggest using “safe” words that only family members would know. Scammers won’t know them.

Never, ever click on unknown software ads. Go directly to the website of the company by using your search engine to find it. Most of all, be skeptical of anything you find online. For any suspicious call, end it and contact your friend or family member directly or call someone who can confirm any situation. And social media, don’t give away personal information that a scammer can use to dig down and find out more. Scammers depend on believability to fool people, so they’ll use personal information they find about your family, friends, neighborhood, or anything else to lend to their believability.

With the increasingly sophisticated Artificial Intelligent software, scammers are digging in their gold mine and coming up with huge gold nuggets they can use to steal from the unwary or unsophisticated. We need to be more skeptical than ever.

Written for Zip Reports where they do employment and rental screening. Contact Robert L. Cain at

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Why the Federal Reserve Builds In Inflation and How That Affects Consumer Debt

By Robert L. Cain, Copyright 2023 Cain Publications, Inc.

The Federal Reserve (Fed) builds inflation into our economy. Official Fed inflation policy states that the health of our economy depends on a specific amount of inflation, 2 percent a year the “ideal” figure. That doesn’t seem like much, but run the numbers. With 2 percent inflation every year for 10 years, $1,000 drops in value to $817.07 losing $182.93. Inflation will never be consistent at 2 percent for each of the 10 years, but the Federal Reserve aims to keep that as the average and worries when it gets too high or too low. More about that in a minute.

The Fed enshrined that 2 percent policy in 2012 making it the standard for saving us from monetary disaster. That’s the goal, 2 percent, but why 2 percent?  Explained St. Louis Fed President James Bullard in a January 16, 2019 paper by the St. Louis Fed, “To clarify, this does not mean inflation must be 2 percent in the short term; rather, monetary policy should be set so that inflation moves toward the target over time and, in the absence of unpredictable changes in either supply or demand, would reach 2 percent in the medium term.”

That still doesn’t answer the question. Why not 0 percent, 1 percent, or 3 percent? One of the Fed’s most important mandates along with low unemployment is to maintain stable prices. And 2 percent does that how? One way is by keeping inflation from being “too low.” Jerome Powell, current Fed chairman finds too-low inflation concerning. Too-low inflation can result in deflation, and they just can’t let that happen. Deflation can devastate the economy, they say, because people put off buying or don’t buy at all. If prices drop, people put off purchases waiting for prices to drop further. Thus, if say a 60-inch smart TV’s price drops to $700, people in the market for one might just wait for the price to drop to $650, and when it does, to avoid paying “too much,” wait again until it drops to $600. Spread that through the entire economy and slower sales in all categories can result in businesses laying off workers thus driving up unemployment, Powell warns.

The last time this country went into a “deflationary spiral” occurred in 1954 during the 1953- 1954 Post-Korean War Crisis when prices deflated, going down below zero to a minus-.07 percent. Coincidentally, that also marked the time when the Dow returned after 25 years to its 1929 high. The panicked Fed for the first time in history intervened and initiated a Federal Funds rate of 1.25 percent. Ever since, the Fed has seen to it that the inflation rate never again drops into negative territory.

Why did it pick that 2 percent figure? Not from any research, but just from a side comment by the New Zealand Finance Minister Don Brash in September of 1988. He commented in a TV interview that he thought the maximum inflation target should be 2 percent. Why? he never said. It was just his idea and opinion, supposedly from careful reasoning, but if he had a reason, he never let on what that reason was. Nevertheless, that 2 percent figure stuck in the notions of economists with the Fed and other bastions of economics ever since.

In 1996 becoming unofficial policy and in January 2012 written–in-stone, it still leaves unanswered the question of why that 2 percent figure, or any specific figure. Explanations run the gamut from speculation to monetary policy.

With monetary policy, the reason they most often pulled out in defense, the 2 percent figure gives the Fed room to move the federal funds rate up and down without dropping into negative territory, a territory where banks would have to charge saving account holders to have savings accounts. Sweden’s central bank used them first when in July 2009 the Riksbank cut its overnight deposit rate to -0.25 percent. The European Central Bank (ECB) joined the club in June 2014 when it dropped its deposit rate to -0.1%. Other European countries and Japan have imposed negative interest rates since, resulting in $9.5 trillion worth of government debt carrying negative yields in 2017. That didn’t go over well with governments and savers.

But still, a question still remains, why 2 percent, or even one percent? Apparently there is no concrete reason. It’s just that the Fed decided on that figure because it was as good as anything and some Finance Minister in New Zealand suggested it once in passing.

Far from an accurate measure of the cost of living, the official inflation rate measures prices selectively. The Bureau of Labor Statistics calculates the inflation rate by taking the Personal Consumption Expenditures (PCE) and dividing it by the Gross Domestic Product (GDP). What’s not included in the PCE and thus the inflation figures are food and energy. Thus, food prices might increase by 10 percent and gasoline by 20 percent, for example, and the inflation calculation won’t include those. In February 2023, food prices had increased by 10.2 percent over February 2022’s prices while the official inflation figure measured five percent over the same period.  At the same time, gas prices rose exponentially as we see every time we drive past a gas station. Still those price increases are left out of the official inflation numbers. The reason, claims the Bureau of Labor Statistics: food and gas prices are too volatile,.

In the meantime, inflation affects people’s purchasing power. Some wages have kept up with inflation while others have dragged behind. The big winners, if you can call them that, are low-paying jobs. With labor shortages in leisure, hospitality, and other service industries, employers have resorted to offering higher wages. Industries with higher average pay have done the opposite. For example, the BLS reported in March average pay for new hires fell 9 percent in insurance, 8 percent in real estate, 5 percent in finance, and 15 percent in information, including technology. Employees in other industries have fared even more poorly. Gusto, a payroll processor for small businesses, reports that advertised salaries for Class A truck drivers fell 33 percent, for landscapers 44.5 percent, for customer service specialists 21.3 percent, for surgical nurses 5 percent, and for delivery drivers 4.5 percent.

Overall wages were up 5 percent year over year in March, just keeping up with the rate of inflation that dropped to 5 percent in March. That worries the Fed, which now may decide that they have to keep raising interest rates so wages fall behind inflation once again resulting in higher consumer debt because people have to use credit cards and other debt to pay monthly expenses such as food and gas, items not even included in inflation figures.

Inflation continues while the Federal Reserve keeps raising interest rates, wages can’t keep up because of the rise in interest rates, and inflation means consumer debt creeps up. That 2 percent inflation target looking pretty good in comparison, still eats into our earning power just not so much.

Written for Zip Reports where they do employment and rental screening. Contact Robert L. Cain at

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Credit Bureaus Fail to Correct Inaccurate Credit Reports

By Robert L. Cain, Copyright 2023, Cain Publications, Inc.

“I’ve been in constant dispute with the credit bureaus for almost a year now and have yet to get … the inaccurate accounts on my credit report removed. I feel like I am being taken advantage of and have been throughout this whole situation. I’ve been getting ignored for months on top of months and it is leaving me no other choice but to take these matters to court if the issue doesn’t get resolved.”—so wrote a consumer to the Consumer Finance Protection Bureau (CFPB) in June of last year reported by the CFPB in a January 3, 2023 report.

Far from the exception, this consumer reflects ongoing problems with and failures of credit reporting. The credit bureaus, Experian, Transunion, and Equifax receive more complaints than any other industry. It has gotten worse. In 2022, 604, 221 complaints were directed to the CFPB, compared to 307,658 in 2021, an increase of 61 percent year over year. They’re all three guilty. Experian’s complaints jumped 334 percent, Transunion’s 183 percent, and Equifax 24 percent year over year.

Not much, if anything, ever gets resolved. Fewer than two percent of the complaints found relief in 2021, reports the CFPB. Ed Mierzwinski, senior director of the U.S. Public Interest Research Group, said the credit bureaus “have never considered consumers as their customers. They’ve always considered consumers as a nuisance.”

“America’s credit reporting oligopoly has little incentive to treat consumers fairly when their credit reports have errors,” CFPB Director Rohit Chopra wrote in a news release. The credit bureaus make money three ways: selling data to lenders, selling individual credit reports to lenders and individuals, and selling information about individuals consumers’ credit worthiness to marketers who sell such things as credit cards to consumers. As a result, they have little incentive to correct errors because dealing with consumer complaints just costs them money.

The Consumer Data Industry Association (CDIA) replying to the CFPB complaint wrote, “We are reviewing the CFPB report in detail. We agree that responding to legitimate complaints and getting credit reports right are paramount.”

Wait a minute, he said “legitimate consumer complaints.” What exactly to they consider legitimate complaints. For one thing, if someone uses a third-party, such as a credit repair company, to deal with an issue, the credit bureaus think of it as an illegitimate complaint.

Chi Chi Wu, staff attorney at the National Consumer Law Center, said, “If you’re using a credit repair, there’s a good chance the bureaus aren’t going to deal with your dispute at all.” The bureaus’ excuse, “Certain credit repair companies falsely promise consumers they can remove negative, but accurate, information from their credit report and drive activity which inflates complaint numbers and undermines the process of addressing legitimate requests,” the association wrote in an email. A valid point, but that throws all the credit-repair companies into the same vat of crookedness and gives the credit bureaus an excuse to ignore inaccuracies on credit reports.

Still, they promised to “do better.” The bureaus created “online dispute centers” to address their failings, reminiscent of appointing a committee to solve a problem: hold lots of meetings, talk a lot, make lots of plans, make lots of promises, and do nothing substantive.

They say they have begun issuing “more substantive responses” because of the CFPB reports and complaints. What “more substantive” means exactly is subject to who is saying it. The credit bureaus say they’re doing much better while those people stuck in complaint purgatory see no difference.

The three credit bureaus keep credit records on some 200 million consumers. The Brookings Institute reported September 28, 2017 that one in five reports contained a “potentially material error.” Assuming that figure is still accurate, that means of the 200 million credit files, 40 million of them contain errors.

What kinds of errors do you find on credit reports? Many you can spot easily, just by reading your credit report.

Incorrect personal information may be easiest. You name is misspelled or someone with a similar name appears on your credit report. It could also be an incorrect address, birthdate, or Social Security Number.

Incorrect accounts resulting from identity theft resulted in 167,000 people reporting fraudulent credit cards with their information on them. Identity theft can come from hacking or outright theft of personal data.

An authorized user might be shown as the account holder. That would be, for example, when a son or daughter has a card and shows up as the owner.

Other errors could be closed accounts showing as open, duplicate accounts maybe with different names, inaccurate payment history reporting paid off debts showing as late or delinquent, incorrect date of the last payment, the date the account opened, or date of first delinquency (if any), and outdated balance or credit limit information.

When someone complains about an inaccuracy such as an incorrect charge, the bureaus contact the creditor who has 30 day to verify the reported charge. Sometimes they confirm that the charge is legitimate despite the fact that it is paid off. That means the inaccurate record stays on the credit report. Then the consumer has to deal with the creditor to have the error removed. In many cases, good luck with that.

Even worse, the complaint actually gets the inaccurate data removed from the report. Then when the bureaus install a backup of their data, the error can be migrated right back on the credit report. It might stay corrected on one or two of the bureaus’ records but not on a second or third one’s. The purgatory starts all over again.

Eternal vigilance is all that can save us from credit-report purgatory. Checking credit reports for errors and filing complaints to the CFPB when those errors have not been corrected is about the only way to hope to keep credit reports accurate, albeit at a snail’s pace. Can you trust credit reports? If one in five has errors, how can you? Just like any other statement, verify everything and ask for explanations from applicants.

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The end or onset of the debt crisis? The debts just keep growing

By Robert L. Cain, Copyright 2023, Cain Publications. Inc.

When will it end?  Credit card debt just hit a record high, jumping $60 billion to almost a trillion dollars, $986.5 billion, in the three months ending December 2022.  That goes along with interest rates increasing on that debt, sucking the savings rate people accomplished during the pandemic down to 3.4% from 33%.

That goes along with a jump in household debt of 2.4 percent to almost $17 trillion over the last

three months of 2022 while average credit card rates increased to 21.6 percent, up from 14.5 percent in November 2022 or just 12 percent in August 2012.

The money is running out. Greg Daco, chief economist at EY-Parthenon, wrote in a market commentary on February 22, “for lower-income families, their excess savings have vanished, and they are now dipping into their regular savings and using credit to offset the burden of inflation.”

“They’re out of cash,” Mark Zandi an economist for Moody’s Analytics, said, “They’re turning to debt to try to supplement their income, and they having trouble paying down that debt.”

Greg Daco said in an interview with Vox, “We’re seeing not just an increase in the transitions into delinquency but also an increase in the debt servicing costs because of higher interest rates and because the levels of leverage are rising. And then we’re also seeing banks and financial institutions being more cautious with credit.” Delinquencies will rise and the economy will at least shudder and at worst go into recession, how severely, we can’t predict. Too many factors enter into the picture.

The reason the economy hasn’t crashed and burned under the weight of that debt is that almost no one who wants to work is unemployed.  Most people can still make the minimum payments on their credit cards, keeping their FICO score tolerable.

Adding to that we have the monkey wrenches waiting to be hurled into the economic machines: student loans.  Some student loan borrowers have never had to make a payment nor been expected to.  Those who graduated with student loan debt in 2020, for example, got a reprieve from both Donald Trump and Joe Biden who put the payment moratoriums put in place.

Because they didn’t have to pay on their student loans, millions of people who had borrowed lots of money to go to school, more than $20,000, got pandemic cash in addition to their salaries and could spend all that money on something other than paying down student loans. Now they wait.  The moratorium, extended eight times, may be ending and threatening to make them start paying again, possibly as soon as August.

Thus, that money they’d been using to pay the rent, their car payments, and maybe stash away a little, will need to be used for that debt they ran up in student loans plus their credit cards, car payment, not to mention regular living expenses.

Their hope is that at least some of their debt will be forgiven. Maybe, but probably not.  The Supreme Court has heard arguments against that debt forgiveness and may toss the whole notion of debt forgiveness, squashing any hope of relief for borrowers with government-backed loans. Maybe the moratorium will be continued, and maybe not.  At some point, though, the payments will come due. That student-loan debt of $1.75 trillion will have to begin to be paid, month by month, eating into the incomes of people, some of whom have never had to pay a dime on their loans, and those who have gotten used to not making payments.

Betsy Mayotte of the Institute of Student Loan Advisors tells those folks to avoid spending money.  But when they don’t spend money, that affects national consumer spending, $14.227 trillion in the third quarter of 2022.  Lots of that spending came from credit card sales, those same sales that jumped the debt $60 billion to $986.5 billion.

Ending the moratorium can make living more precarious for those whose incomes barely cover their expenses now.  Already many lower-income people have to use their credit cards just to live, unable to pay them fully at the end of the month. They have to charge highly inflated food to eat and pay for gas to get to work, then have a card balance at the end of the month on which they hope they can make the minimum payment. Add the student loan payments to the mix and creditors, utilities, or landlords, or all three, will not get paid.

What happens when rent, credit card bills, and car payments don’t get made? In a couple of months, debtors won’t have a place to live, won’t have use of their credit cards anymore, or a car to drive in a few months.  Exacerbating the problem: 202 Million new credit accounts opened in the fourth quarter of 2022 mostly from adults 18 to 25 including subprime customers who have FICO scores 600 or lower. Credit card companies have begun marketing to these less-than-prime credit candidates.  Figure, as does Transunion, that delinquency rates will grow.

Incomes haven’t kept pace with inflation. Clarify Capital, a small business lender reported that in the United States, even though the average annual salary increased 31.2 percent from 2010 to May 2021, the average incomes adjusted for inflation dropped 4.5 percent. The labor department keeps saying how consumer spending is great and how it’s pushing the economy upward. But they only mention the raw figures. Never do they factor in how inflation has eaten up the purchasing power of consumers, forcing them to rely on credit cards that eventually they could max out and be unable to make even minimum payments on.

As the delinquencies begin to grow, the ripple will start affecting businesses that won’t have those previously great sales figures propped up by credit sales and negatively affecting the credit card companies that will lose money writing off debts.

Debt crisis? It’s gathering steam, fed by rising prices, stagnant to declining incomes, and late payments. Those with a vested interest in evading the facts say “not yet.” But the signs all foretell a debt debacle.

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Artificial Intelligence: Its Perils and Promise in Applicant Recruiting and Screening

By Robert L. Cain, Copyright 2023, Cain Publications, Inc.

In 2014, Amazon got itself a new recruiting tool that used artificial intelligence (AI) to recruit employees. “Everyone wanted this holy grail,” an Amazon spokesperson said and Reuters reported. “They literally wanted it to be an engine where I’m going to give you 100 resumes, it will spit out the top five, and we’ll hire those.” It would also mean that every resume would get full attention rather than get cast aside because the person reviewing it was tired, distracted, or didn’t like the applicant’s favorite sports team.

To enable the AI machine to do a proper job of sorting the resumes, Amazon uploaded the resumes submitted to the company for the previous 10 years. They trained the computer models to look for patterns of the qualities that made for a successful employee.

By the next year, 2015, the problem became obvious. Because the vast majority of resumes came from men, the computer penalized any resume that included the words woman or women, such as “women’s rowing team” or “women’s tech club.” It also downgraded any resume from graduates of two all-women colleges. Amazon had left itself wide open for a EEOC complaint.

By the start of 2017, Amazon had disbanded the team because, according to the Reuters article, “executives lost hope for the project.”

Even with this warning in place, Reuters reported, “Some 55 percent of U.S. human resources managers said artificial intelligence, or AI, would be a regular part of their work within the next five years.”

Software companies abound with promises that employers will have the ability to recruit “fairly” and quickly, avoiding biases of HR people who might reject an applicant because of some inconsequential prejudice. But in order to recruit and screen quickly, the computer has to be told what criteria to judge applicants on. Therein lies the rub. Computers do what they’re told, and if you tell them to do something illegal or unethical, they do exactly that, no questions asked because they don’t know about laws and ethics.

The old computer maxim “Garbage in Garbage Out” rules every item of computer output. If, as in Amazon’s case, the computer’s garbage-out criteria dismisses applicants who are members of protected classes, in their case women, the employer ends up on the receiving end of a fair employment complaint or a rental owner of a Fair Housing complaint.

For example, if they tell the computer to only look in certain zip codes for acceptable employees,  that could eliminate any applicant living in a zip code with a primarily minority population. Tell the computer to only look for applicants who attended specific colleges and universities, and

that would most likely eliminate any applicant who graduated from a predominately Black college. Advertise job openings or vacancies only on Facebook, and since Facebook’s users tend to be younger, it could have the effect of eliminating employees more than 40 years old, a protected class.

It has to do with Disparate Impact, which defines as the “judicial theory . . . that allows challenges to employment or educational practices that are nondiscriminatory on their face but have a disproportionately negative effect on members of legally protected groups.” The key is it’s not what you meant; it’s what somebody thinks you might have meant that guides government investigations into illegal hiring and renting processes. You had no intention of illegally discriminating against anyone, but what you told the computer to do was discriminate with a disparate impact on some protected class.

AI can be a useful tool. It comes in three flavors, narrow AI, Generalized AI, and Artificial Super Intelligence.

Narrow or “weak” AI does specific tasks, ones you instruct the computer to do. It could be a robot in a factory, music selection, think Alexa and Siri that is told to find out what you prefer in shopping and music, and a neural network that runs a power grid, for example. Neural networks process information, inspired by how brains’ neural systems process data. Artificial intelligence tries to simulate biological neural networks, so they can be more like a human brain.

Generalized AI emulates the human mind and learns and remembers from what it does and can incorporate what it learned and seem to think on its own. In its infancy now, it promises to become even more “useful” in learning what works and what doesn’t. Faced with an unfamiliar task, it can figure out and remember how to do it most effectively. Designed to be able to learn new tasks and adapt to new situations, generalized AI is meant to be more intelligent than narrow AI and is capable of making decisions and acting autonomously. Examples of generalized AI include facial recognition, autonomous driving, and natural language processing, as well as more complex tasks such as machine learning and deep learning.

Artificial Super Intelligence is maybe in the future. Its current developmental progress, though, resembles a fully loaded freight train picking up speed barreling downhill, all but unstoppable. That would be or will be a machine with intelligence equal to that of humans and a self-awareness giving it the ability to solve problems, learn, and plan for the future. Search for LAMda for details. And think HAL in “2001 Space Odyssey” and Skynet in the “Terminator” movies. The doomsday scenarios have Super AI taking over the world and wiping out humanity.

AI can be a valuable tool to use in screening and recruitment. Presumably, employers and landlords have specific criteria for whom they will accept as employees or tenants. Those need to be programmed into the AI platform so they can quickly qualify or disqualify applications. Chances are you don’t have the training or capabilities yourself, so you will have to employ an AI software company to set it up for you. That’s where the peril lurks. If they set it up so it illegally discriminates against protected classes of people, you are responsible just as you are for the conduct of any contractor such as a carpenter who repairs the front steps on a rental. If the carpenter installs the steps unsafely, it’s your responsibility even though the carpenter did the work. Likewise, if a software company installs an AI recruiting system that discriminates against a protected class, it’s your fault.

How can you tell if the criteria inputted are fair to everyone? Good question. You have to do considerable “what-if” thinking. What if I were a black person? Would I feel as if I could apply for that position? What if I were a single woman? Would I feel as if I could apply to rent that unit? What if I were 45 years old and looking for work? Would I see the ad on Facebook since I don’t use Facebook but my kids do? Would it were that simple.

Amazon stopped using its biased recruiting system because they couldn’t figure a way to make AI recruiting fair even though they have some of the most highly skilled programmers and engineers in the world. You probably don’t have the equivalent programmers. What an employer or rental owner must do is look at lots of what-ifs and think critically about whom their recruiting and screening efforts end up being aimed at. Who might be left out?

Written for Zip Reports where they do employment and rental screening. Contact Robert L. Cain at

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Screening Using Social Media: Advantages and Traps

By Robert L. Cain, Copyright 2023, Cain Publications, Inc.

They tried to think of everything. With dummied up bank records, tax records, employer and landlord references complete with phone numbers of friends, they created a history that showed them to be stable and responsible. But they forgot one thing: social media.

Some 70 percent of employers use social media to screen applicants. Social media has been a go-to source of screening ever since Facebook, LinkedIn, Twitter, and TikTok became popular.

People say stupid stuff and think no one will notice. That’s the advantage of using social media for screening and verifying what’s on an application. All that money they paid companies to create phony documents, and time they took time preparing everything, can end up wasted because their social media accounts tell a different story,

Social media use varies by age. posted that of the 2.93 billion active and 1.96 billion daily users of Facebook, 86 percent of people 18–29 and 77 percent of people ages 30–49 use Facebook. Instagram’s 500 million users have 67 percent of 18-29-year olds and 47 percent of 30-49-year-olds using it daily. Of Twitter’s 436 million active and 238 million daily users, 38 percent are 18-29 and 26 percent 30-49. Since the vast majority of users of these social media platforms are in their 20s and 30s, expect that any applicant in that age group will be present on social media.

LinkedIn, a more business-oriented site, shows a different age profile. Only 21 percent of 18-24–year-olds use it daily as compared to 60 percent of 25-34-year-olds. On LinkedIn, you are more likely to find people posting about business and employment. On Facebook, Instagram, and Twitter you find more personal information and maybe some things that call into question the documents an applicant provided.

Checking social media is free, requiring only a little time searching and maybe occasional creativity. Someone with even a little experience in tracking people down on social media can avoid a bad hire or a bad tenant. Of course, it can also confirm desirable qualifications.

How to Do It

Usually, it’s easy. Just type the person’s name into a search on Facebook, Twitter, or TikTok and see what comes up. With some names, you may have to focus your search more by adding the city where the person lives or maybe their school or some other defining criteria just to be sure you are looking at the right person.

Look for anything that tells you enough about the applicant regarding his or her character and qualifications to help you decide if this is the person who deserves to work for you or live in your property.  For example, what if you find that Joe Blow brags about how he just ripped off his employer and got the blame placed on someone else? What if Geraldine Moe posted how much she hates Blacks, Hispanics, and anyone else who’s not Caucasian? What if Joe Blow’s back at it and posts pictures of himself drunk out of his mind and trashing the house where the party is? Are these people you want to hire or have living in your rental properties?

Personal information people post about themselves such as where they work and how long they’ve worked there also often shows up on someone’s Facebook or Twitter account. Does that information match what’s on their applications?

You might also find information that confirms what a responsible citizen and all-around good person he or she is. Look for information that might be in addition to or contradict what’s on his or her application. provides a list of the things that employers look at when they research someone on social media. At the top of the list is “provocative or inappropriate photos and video,” followed closely by “information about the candidate drinking or using drugs.” “Discriminatory comments on race, gender, religion, etc.” comes in a close third. Naturally one of the first reasons we think to check is if your “candidate lied about qualifications” or “badmouthed previous employer.” They list a few more, any of which could help you decide on a candidate’s qualifications. warns us, though, to “take everything with a grain of salt.” It’s easy to fake profiles on social media. They think nobody checks or cares, after all.

Be especially careful about illegal discrimination. If you reject an applicant who happens to be a member of a protected class, it’s not what you meant; it’s what someone thinks you might have meant. If what you found on social media causes you to reject an applicant, take screenshots of the information that caused you to reject and save it.

If you can’t locate a candidate on social media and your candidate is under 35, be suspicious. It’s possible that your candidate is one of the 14 percent of that age group that has no Facebook account but probably not. Sometimes people use pseudonyms so no one except friends will know who they are. They might also have deleted their social media accounts before they applied to you because what they posted would immediately turn off an employer or landlord. Finding them is more difficult and not always worth the time, but not impossible.

Mostly it’s a wild goose chase and you might just need to verify everything more carefully than usual because of the time it will take to drill down into social media and the unlikely results. Hashtags probably are the easiest to use to look for posts by people who have pseudonyms or have deleted their accounts. They are a sorting system to help locate specific information about any topic or person. For example, do a search using #company name (whatever that is) using either Twitter or Facebook and see what comes back. I just did a search using #wellsfargo and got hundreds of posts on both Facebook and Twitter. Probably more than you’d want to wade through.

Four things are most important to remember. First, leave social media to end of the process. Check only those who might be qualified. Second, don’t decide based solely on social media because it’s not all that reliable. Most reliable are the verifications you do. Social media only give you clues—albeit sometimes valuable ones. Third, since you can only get a limited amount of information from social media, assume nothing and verify everything on both their applications and social media. Fourth, your social media qualification criteria must match the written criteria you use for hiring and renting.

Social media screening provides another tool in the application box. You wouldn’t use a screwdriver to drive in a nail, so use the tool that best fits your needs and suspicions. But when you find information that can determine the quality of an applicant by using social media, you’ve done yourself a favor.

Written for Zip Reports where they do employment and rental screening. Contact Robert L. Cain at

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Layoffs and Hiring Freezes Are Taking Their Tolls on the Economy

By Robert L. Cain, Copyright 2022, Cain Publications, Inc.

If they take $11 billion out of the economy, the effects will be less than pretty. They did and it isn’t pretty. As of November 18, 120,000 tech workers had been laid off in 2022. And the layoffs continue along with hiring freezes. Marc Weil, who has worked in tech since 2010, and one of the 120,000, was quoted in a Washington Post article, “Year after year goes by and the tech economy keeps getting bigger and bigger with no end in sight. Everyone in tech has been warned by people who lived through the last few decades that this will end. And so it ended.”

Just the tip of the iceberg, tech accounts for a small part of the US economy. But considering its influence on spending and business, its effects swallow a much larger piece of the economic pie than its perceived size. The average salary of a tech workers is a little more than $94,000 a year. Every dollar spent turns over seven times, advises the economic axiom. That means that one tech worker’s salary contributes more than $658,000 to the economy every year. Multiply that times 120,000 and you get more than $11 billion. Where does that money go? Much of it goes to the incomes of such small businesses as restaurants, coffee shops, gyms, movie theaters, professional services. Those businesses employ thousands of people, but may now employ fewer and fewer. The rest may well go to the government in taxes.

The layoffs and hiring freezes go beyond tech. According to a survey by LinkedIn, most industries’ hirings have plummeted with tech not even in first place.  Far and away in first, or maybe last, place are holding companies whose hiring year over year dropped 23.3 percent, followed by tech at 17.1 percent. Others follow closely such as entertainment providers (small businesses) at 14.2 percent, professional services (another small business industry) at 15.6 percent, and retail at 12.5 percent (much of that small business).

Winners stand out, though. Utilities hired at a 23.3 percent increase, so if you’re an electrician, for example, and want to work for a power company, or a plumber and want to work for the water company, you’ve most likely got a job.

Also increasing in recent months, after declining year over year, were government, education, construction, farming, and health care.

Jim Harrison, of the Utility Workers of America, AFL-CIO, quoted in Money magazine, explained about utilities, “It’s a recession-proof sector for the most part. People still have to have the essentials of modern-day life. They need to have light, heat, power and water and those kinds of things.” But they don’t have to have restaurants, hair dressers, and holding companies.

“Big picture,” though says Julia Pollak, chief economist for Zip Recruiter, “companies are very much preparing for the possibility of a downturn. They’re focusing on hiring rather than nice-to-have hiring. But many are still continuing to hire because they absolutely have to.”

And they don’t “absolutely have to” keep raising wages. Sure, hourly earnings keep going up but more slowly. In September, for example, they rose just 0.3 percent to $32.46 an hour. Companies figure they can attract workers without increasing pay much.

Even so, some economists discount the tech layoffs and less hiring by citing the Labor Department figures of the 261,000 jobs added in October. They claim that the tech layoffs have no effect on the economy saying that tech accounts for an infinitesimal part of unemployment.  They also point to consumer spending, which increased by 0.8 percent in October as proof that everything is all right. That increase has been skewed by the inflation that rose 0.7 percent for the month with much of the rest of it consisting of people having to catch up with their unmet needs such as buying gas and groceries and taking money out of savings, which decreased to 2.3 percent down from 2.4 percent in September.

Those laid-off tech workers will have to go job hunting with no guarantees that the jobs they get will come close to paying what they made at Facebook, Google, or Twitter. That’s a good thing, says Erik Brynjolfsson, a Stanford University economist, “I think the salaries in tech were unrealistic. Now there’s a bunch of really good coders and engineers for the rest of the economy where they are needed a lot more.” Might he have been forgetting about the effect that taking a good portion of the income they had earned out of the economy? Remember, you can’t do just one thing. The unpredictable ripples of layoffs and hiring freezes affect the economy cutting into hiring both for large and small businesses.

Layoffs don’t make up the whole problem. Jim McCoy of Manpower said, “They’re planning for uncertainty. Companies are slowing down replacing people so they don’t have to do layoffs next year.” He added that companies because of “economic uncertainty” have chosen not to hire for around one-third of the open positions. It costs money to lay off workers what with severance packages. But it costs nothing to not hire in the first place. Instead, may companies hire contractors. They may not cost less, but they are infinitely easier and cheaper to lay off.

Put the layoffs and hiring freezes together and the witches brew bubbles with a smell that bodes ill for the economy. In September, 6.1 million people got hired, the lowest level since February 2021. With job growth at 261,000, the lowest since April 2021.

The upside, if there is one, is that employers can be more selective when they actually do hire someone. They can screen thoroughly and set standards higher than they were able to before. Chad Leibundguth of Robert Half Staffing remarked in a USA Today article, that employers are “taking their time to identify the right person.” That’s if they look for new hires at all. Now is the time for businesses to describe their ideal applicant and wait for him or her to show up, which might be sooner than later.

Written for Zip Reports where they do employment and rental screening.

Contact Robert L. Cain at

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Buy Now Pay Later’s Impending Downside

By Robert L. Cain, Coopyright 2022, Cain Publications, Inc.

They took a market served by check-cashing and payday loan stores and offered credit to their customers. Buy Now Pay Later (BNPL) began as a way to reach an underserved or ill-served $3.9 trillion credit market seen as a giant money-making opportunity. Making money hasn’t been part of the planned equation though. So far so bad.

BNPL companies such as Klarna, Affirm, Afterpay, Zip, and Sezzle lose money on every transaction. It costs them more to market their services than they make from lending with the 2 percent to 8 percent discount retailers pay when those companies’ borrowers buy from one of their merchants. Customers pay no interest if they pay off their purchase within six weeks. After that, depending on the lender, the interest rate can vary between 25 percent and 36 percent. One company, Affirm, advertises that it doesn’t charge late fees, something other companies do, but charges an interest rate of 36 percent after the six-week grace period expires and their customers still owe on the loan.

Even with extra, added charges and interest, the industry profit margin sits at a minus 2.6 percent. Apparently, they figure they can make up the loss in volume with the, according to Reuters, 180 million loans they made in 2021, a 200 percent income increase from 2019. Most likely, it just increases their number of losses by the 200 percent range.

Check cashing stores and payday lenders whose customers the BNPL companies are trying to gobble up have built-in safeguards. Check-cashing stores discount checks after they verify the funds, so they have no risk. Payday loan stores always verify customers’ employment before they loan to their customers. Traditional lenders such as credit card companies won’t even accept a customer who doesn’t meet their credit standards and report to credit reporting companies. The BNPL industry has no such safeguards in place. Their loans don’t show up on credit reports, and since they don’t communicate with other BNPL companies, don’t know if one of their customers has outstanding loans with other companies. Gee, how might that go wrong?

BNPL companies are maybe less than forthright in their marketing. For example, read the reviews on all their websites. All seem to have been written by the same person: same sentence structure and same syntax, perfect spelling and grammar, even the negative reviews. In fact, the negative reviews it appears were used as sales pitches because they all promise some kind of compensation to the “injured” reviewer. That’s no financial damage to the companies because no real customer had a problem that they published, anyway.

With the somewhat tarnished shine coming off the Yugo business model, the wheels have begun to wobble. Delinquencies are up with a 2.39 percent charge off rate in 2021, or $109 billion compared to a 1.83 percent rate, or $70 billion in 2020. In contrast, charge off rates for credit cards amount to 1.8 percent.

BNPL companies make it easy to borrow money by users installing apps on their phones that they can use at POS terminals much like using credit cards. Trouble is, they only work for companies that accept BNPL payments, which isn’t close to every one of them.

It’s Buy Now Pay Much More Later if these companies expect to turn a decent profit, something they don’t expect to do until 2026 or 2027, says the rosy picture management paints after being in business since 2008. Amazon, in comparison, showed a profit in 2003 after being in business selling books out of Jeff Bezos garage in Bellevue, Washington since July 5, 1994, but they sold tangible merchandise that people wanted with a business model that invited and propelled growth. They also didn’t loan money to the unqualified unlike the BNPL companies that rely on people who are hanging on by their fingernails.

Trying all kinds of revenue generation techniques, BNPL companies pull out the revenue-generating playbook. One technique is accepting advertising.  Afterpay’s website is cluttered with ads. Whether those advertisers get a lower discount, Afterpay isn’t telling. Another idea is a “repeat user fee.” More than one BNPL company suggests that if borrowers borrow multiple times in a month, they’ll get hit with a fee for that. Of course, that would drive them to other BNPL companies where they could tack on more loans unbeknownst to any other BNPL company.

So what? Who cares if BNPL companies find themselves teetering on the edge of insolvency? If it only affected them, it would just add an item of interest. But it can and will affect the people who are supposed to be paying their loans back.  Already, just as credit card borrowers have, BNPL customers use BNPL loans to buy groceries and gas, possibly tacking loan upon loan just to keep food on the table and gas in the car to get to work. Credit card borrowers who have maxed out their cards might even find themselves needing to use BNPL to buy food and gas with inflation chewing up their incomes.

When the recession and layoffs expected to hit next year begin, the BNPL customer base could well find itself unable to pay back its accumulated loans. Since BNPL companies already paid the bill their customers ran up, if borrowers have no money to pay back the loans, the lending companies will have to eat the money they already paid.

The successful issuers of credit have the good sense to qualify their borrowers before they let them run up bills. BNPL companies loan and hope. They hope their borrowers are qualified, but can’t find out for sure before they lend. They hope their borrowers will be able to pay back the loans but have no way of qualifying them except their experiences after they make the loan. They hope the economy stays afloat and the inflation abates so debts can be paid back. They hope to come up with additional revenue sources so they actually make a profit, even though even they don’t expect it for at least four years. That’s a huge impending downside.

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How Liars Give Themselves Away

By Robert L. Cain, Copyright 2022, Cain Publications, Inc.

A boss  I had once gave away his lies with a gulp in his throat immediately before and after the lie exited his mouth. Once I heard the gulp, I dismissed any and everything that had followed or preceded it. 

Our last landlord, the one we had 40-plus years ago, gave herself away with the glazed look in her eyes, looking at empty air when she made up or otherwise embellished a story.  We always knew.

I knew one sleazy businessman who gave away his lies with a short “ha-ha” laugh.  Ask him a question and he after made up an answer he thought would please you, he added a “ha-ha” exclamation point onto the lie. 

Liars give obvious signs that what they are saying is not the entire truth, or maybe any of the truth. We all can identify them.

Most people, far from being “practiced at the art of deception,” have no idea they are giving away the fact they are lying through body language or vocal spasms.

Paul Eckman, of professor of psychology at the University of California in San Francisco, says that catching liars is an art almost anyone can learn.  People show tell-tale signs, he says, when they lie.  “Liars usually do not monitor, control, or disguise all their behavior.”

In the book The Art of Questioning: Thirty Maxims of Cross-Examination Peter Megargee relates this anecdote.

“Attorney Lloyd Paul Stryker was a keen observer.  He would watch carefully how the witness behaved in the courtroom and on the stand.  He would rivet his eyes on the quarry during direct examination. . . .  He looked for clues in the ways the individual expressed herself or himself.  He listened for variations in tone of voice caused by the tightening of vocal chords.  He noticed pauses.  He noted flashes of anxiety, dryness of mouth, moistening of lips, hesitations, discomfort, and uncalled-for repetitions of coached material.  He watched for stammer and for needless reference by the witness to counsel’s name. ‘I never was there, Mr. Prosecutor.’ Eyes were of particular interest.  How and when did pupils shift and dart?  When did eyes narrow or blink?  The giveaway laugh and wipe of forehead.  Hands wring, cling, scratch, and readjust.  Legs shuffle.  A hand touches the pocket with notes taken from his lawyers on what to avoid at all costs.”

We can’t be as accomplished at spotting liars as Lloyd Stryker was without years of practice, but let’s look at some of the obvious body language signs and vocal signals people make that give clues that they may not be telling you the entire truth.

When you ask a question, a “probing point,” just as Stryker did to a witness, watch your applicant or tenant carefully. A probing point may be evident when a word or phrase “touches a nerve” during a conversation.

Your question may elicit a lip-purse, a shoulder-shrug, or a throat-clear, for example.  Other signs may be stumbling over words, a higher voice pitch, or repeated swallowing.  However, Dr. Paul Eckman points out that “is no guarantee that a lie is being told, but it signifies a hot moment when something is going on you should follow up with interrogation.” The question has hit a sore spot.  Is it always something that will disqualify him or her? Of course not.  It could just be an unpleasant memory.  But you owe it to yourself to find out if it is important to you in your selection process and your decision whether to believe the person you are speaking with.

Body language expert John Mole provides the following list of body-language cues that could indicate someone is lying:

  • Touches face
  • Hand over mouth
  • Pulls ear
  • Eyes down
  • Glances at you
  • Shifts in seat
  • Looks down and to the left

How does it work on the field of battle with an applicant in front of you and his or her application in hand?  Here’s an example:

Finally! They look and talk like terrific people. They tour the property and pronounce it a “really nice place, someplace we could live forever.” They even talk about how close the unit is to the school their children attend and that they have friends just a couple of blocks away.

The prospect of them living there forever pleases you because the last three tenants have moved out after just a couple of months. Now here is someone who wants to stay a long time.

Hardly able to contain your excitement, you ask a simple question, “Do you think your last landlord will give you a good reference?”

“Oh, sure, no problem,” the wife says as she covers her face with her hand.

“Yeah, we got along—along fine, yeah, uh, fine,” says the husband while pulling his ear lobe.  “He’s uh, uh, uh, uh, going to sell the building.  That’s why we’re getting kic—, er,. Moving.” At that point, he stares at the ground, seemingly intensely interested in the bug crawling along the sidewalk and glances at you out of the corner of his eye.

Too bad.  And here you thought these folks looked promising. You wonder why they don’t just tattoo “LIAR” across their foreheads.  You vow to quiz their last landlord after making sure the number they gave you for him on their application is the actual phone number of their last landlord and not of their friends who “live just a couple of blocks away.”

Other things to watch for that indicate deception are pupil dilation and fast blinking rates.  Eckman observes that people make “fewer hand movements during deception compared to truth telling.”

No clue assures absolute proof that an applicant’s answers are fabrications. They do mean that the person is anxious or feeling stress. Liars though, other than the pathological subspecies, feel stress or anxiety when they spout their lies.

These cues should arouse suspicion about what they have told you.  Remember which question or at what point their body language or vocal quirks indicated deception, and be extra vigilant in checking out that spot on the application.  You are simply using your applicant’s body language to give you a better idea about where they might be trying to put one over on you.

Just pay close attention not to just what they say but how they say it.

Written for Zip Reports where they do employment and rental screening.

Contact Robert L. Cain at

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Regulation F Affects Both Collection Agencies and Creditors

By Robert L. Cain, Copyright 2022, Cain Publications, Inc.

“Deadbeat! Just wait until I put you on the deadbeat list that I’m going to show everybody! My law firm and I will hound you forever! I’m going to have you arrested, too! Did you get that court order I sent you? Just wait, deadbeat!”

There might have been a time when it was legal to say any and all that to a debtor, but now danger lurks. Already it was mostly illegal under 15 USC 1692 (d-f). But under the Fair Debt Collection Practices Act (FDCPA) with Regulation F added protections were implemented Nov. 30, 2021.

These updated regulations, aimed specifically at some less-than-ethical collection agencies, also apply in many cases to creditors themselves attempting to collect a past-due balance from a customer or tenant. Creditors include landlords owed rent when a tenant moved out one midnight and business owners owed a debt and who haven’t been paid for 90-plus days by a customer.

Time-Barred Debt

One trick some less-than-ethical collection agencies used was to buy up old debt, debt that aged out past the statute of limitations, and attempt to collect it. They’d sue the debtor and count on him or her not showing up in court, resulting in a summary judgment against the debtor. If the debtor showed up with evidence that the debt had passed the statute of limitations date, the judge would dismiss it. Most often, though, they just didn’t show up in court and the judge issued a summary judgment.

Under the new Regulation F, the collection agency must first prove the debt is current before it can sue.

Credit Reports

Some small debts take too much effort and time to try to collect. Collection agencies and some creditors would simply report the debt to the credit reporting agencies without the debtor knowing. When they pulled their own credit report, the debtor was in for a surprise. Under the new FDCPA regulations, the creditor must get in touch with the debtor by mail, email, or text to tell him or her the debt will be reported. Until that contact, the creditor may not report to the credit reporting agency.

The question arises, then, can a deadbeat tenant or customer hide out or just return mail as undeliverable, bounce a text, or have an email come back as undeliverable and avoid having the debt reported? The answer is a qualified no. After considerable comments from collection agencies, inserted in Regulation F came the provision that the creditor must wait 14 days for the letter, email or text to come back undeliverable before reporting the debt. They are entitled to make “judgment calls” regarding compliance with the FDCPA and hope their “judgment” meets with the approval of the federal authorities and courts. One method that requires no waiting period or contact with the debtor is reporting to a check verification company. How effective? It’s debatable.

Constant Phone Calls

Another annoying trick collection agencies used was the hourly phone calls, harassing the debtor at all times of the day and night to beat them down so they’d pay the debt. I don’t know how well that worked to collect what was owed, but it did hound the debtor. Under the new Regulation F provisions, a creditor can call, text, or email only seven times in seven days, and if the creditor has spoken to the debtor on the phone, the company must wait seven days before making another call to that person.

Debt Validation

Within five days of the first contact with the debtor, the collector, that’s either the creditor him or herself or the collection agency, must send the debtor a Notice of Debt. The collector needs to provide a Debt Validation Notice (available from, which includes detailed information including one of five different dates such as the last statement date, the charge-off date, date of last payment, the judgment date, if there was one, or a couple more found on the form along with the name and address of the original creditor. That is supposed to ensure the debtor knows what the debt is for. The form also provides a way to dispute the debt, says under what circumstances the collector has to stop trying to collect, a way to ask for the name and address of the original creditor, and a way to ask about payment options.

Debt validation can throw a monkey wrench into the workings of collection agencies because they often don’t have the name and address of the original creditor. They may have bought the debt from another agency but without any original creditor information. They would have to get all that information from the original creditor who may not have any reason to provide it since the original creditor won’t get any of the money collected.

Creditor Responsibilities

If a company does its own collecting, the same provisions apply as those for collection agencies. Still required is supplying complete information to the debtor and following the same non-harassment rules. In addition, here’s one more vital concern. If they hire a collection agency and that agency violates any of the harassment or procedure rules, the creditor can and will be held responsible since the creditor is responsible for any and all actions of its agent. Thus, it pays to research any collection agency thoroughly before hiring them.

At least one technique survives. If a creditor gives up and figures the debt is uncollectable, it can let the IRS be its collection agency. No, there won’t be any money coming to the creditor, but it likely will result in an IRS audit of the debtor. Use the 1099-C form, forgiveness of debt if the debt is more than $600. Most likely the debtor won’t know it’s been filed and so won’t include it as income on his or her tax return. Come April 15, you can, albeit vicariously, imagine what the IRS will do to your debtor.

Debt collection just got more restrictive, but you can still get your money. Deadbeats are still on the hook for the debt. It just might be more complicated and maybe take a little longer to collect. Have a concern or question? Call an experienced regulatory attorney because some provisions of Regulation F might conflict with portions of the Fair Debt Collection Practices Act. warns that “substantial monetary penalties” await the unwary and indifferent violators of this regulation.

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