They included “pig butchering” a way of fattening up victims with affection, the missing person scam which involves posting fake content on social media pages, the traditional PayPal scam, and a new scam called the “fake app alert” in which malware is hidden on apps that look legitimate…Continue reading….
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Critics:
Confidence tricks exploit characteristics such as greed, dishonesty, vanity, opportunism, lust, compassion, credulity, irresponsibility, desperation, and naïvety. As such, there is no consistent profile of a confidence trick victim; the common factor is simply that the victim relies on the good faith of the con artist.
Victims of investment scams tend to show an incautious level of greed and gullibility, and many con artists target the elderly and other people thought to be vulnerable, using various forms of confidence tricks. Researchers Huang and Orbach argue: Cons succeed for inducing judgment errors—chiefly, errors arising from imperfect information and cognitive biases. In popular culture and among professional con men, the human vulnerabilities that cons exploit are depicted as ‘dishonesty’, ‘greed’, and ‘gullibility’ of the marks.
Dishonesty, often represented by the expression ‘you can’t cheat an honest man’, refers to the willingness of marks to participate in unlawful acts, such as rigged gambling and embezzlement. Greed, the desire to ‘get something for nothing’, is a shorthand expression of marks’ beliefs that too-good-to-be-true gains are realistic. Gullibility reflects beliefs that marks are ‘suckers’ and ‘fools’ for entering into costly voluntary exchanges. Judicial opinions occasionally echo these sentiments.
Accomplices, also known as shills, help manipulate the mark into accepting the perpetrator’s plan. In a traditional confidence trick, the mark is led to believe that he will be able to win money or receive some benefits by doing some task. The accomplices may pretend to be strangers who have benefited from performing similar tasks in the past.
Fraud has rapidly adapted to the Internet. The Internet Crime Complaint Center (IC3) of the FBI received 847,376 reports in 2021 with a reported loss of money of $6.9 billion in the US alone. The Global Anti Scam Alliance annual Global State of Scam Report, stated that globally $47.8 billion was lost and the number of reported scams increased from 139 million in 2019 to 266 million in 2020.
Government organizations have set up online fraud reporting websites to build awareness about online scams and help victims make reporting of online fraud easier. Examples are in the United States (FBI IC3, Federal Trade Commission), Australia (ScamWatch ACCC), Singapore (ScamAlert), United Kingdom (ActionFraud), Netherlands (FraudeHelpdesk). In addition, several private, non-profit initiatives have been set up to combat online fraud like AA419 (2004), APWG (2004) and ScamAdviser (2012).
The falsification of documents, known as forgery, and counterfeiting are types of fraud involved in physical duplication or fabrication. The “theft” of one’s personal information or identity, like one finding out another’s social security number and then using it as identification, is a type of fraud. Fraud can be committed through and across many media including mail, wire, phone, and the Internet (computer crime and Internet fraud).
Given the international nature of the web and ease with which users can hide their location, obstacles to checking identity and legitimacy online, and the variety of hacker techniques available to gain access to PII have all contributed to the very rapid growth of Internet fraud. In some countries, tax fraud is also prosecuted under false billing or tax forgery.
There have also been fraudulent “discoveries”, e.g., science, where the appetite is for prestige rather than immediate monetary gain. A hoax is a distinct concept that involves deliberate deception without the intention of gain or of materially damaging or depriving a victim.
The detection of fraudulent activities on a large scale is possible with the harvesting of massive amounts of financial data paired with predictive analytics or forensic analytics, the use of electronic data to reconstruct or detect financial fraud. Using computer-based analytic methods in particular allows for surfacing of errors, anomalies, inefficiencies, irregularities, and biases which often refer to fraudsters gravitating to certain dollar amounts to get past internal control thresholds.
These high-level tests include tests related to Benford’s Law and possibly also those statistics known as descriptive statistics. High-level tests are always followed by more focused tests to look for small samples of highly irregular transactions. The familiar methods of correlation and time-series analysis can also be used to detect fraud and other irregularities.
Beyond legislation directed at preventing or punishing fraud, some governmental and non-governmental organizations engage in anti-fraud efforts. Between 1911 and 1933, 47 states adopted the so-called Blue Sky Laws status. These laws were enacted and enforced at the state level and regulated the offering and sale of securities to protect the public from fraud.
Though the specific provisions of these laws varied among states, they all required the registration of all securities offerings and sales, as well as of every U.S. stockbroker and brokerage firm. However, these Blue Sky laws were generally found to be ineffective. To increase public trust in the capital markets the President of the United States, Franklin D. Roosevelt, established the U.S. Securities and Exchange Commission (SEC).
The main reason for the creation of the SEC was to regulate the stock market and prevent corporate abuses relating to the offering and sale of securities and corporate reporting. The SEC was given the power to license and regulate stock exchanges, the companies whose securities traded on them, and the brokers and dealers who conducted the trading.
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