An Overview of the Federal Trade Commission’s 2020 Consumer Reports

An Overview of the Federal Trade Commission’s 2020 Consumer Reports

While the U.S. Federal Trade Commission (FTC) exists to put forth pertinent regulations and publish findings, some of its best resources for new marketplace discoveries are consumers themselves. Through consumer reporting, the FTC can identify trends and questionable business practices from the perspectives of those who directly experience them. Consumer reports are stored in the Consumer Sentinel Network (Sentinel). Sentinel is a secure online database available to law enforcement, allowing the FTC’s law enforcement partners to use the information from the database to better enforce anti-fraud laws.

In February of this year, the FTC released their Consumer Sentinel Network 2020 Data Book, which aggregated more than 4.7 million consumer reports made in 2020 and sorted them into 29 top categories. The data is based on unverified reports made to the FTC’s call center or online, as well as reports filed with other federal, state, local and international law enforcement agencies, as well as organizations like the Better Business Bureau and Publishers Clearing House. The Data Book provides illuminating information on how a year defined by the pandemic influenced fraud methods and the trends anti-fraud professionals should expect in the years to come.

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Federal Trade Commission Makes Fraud Data Public and Interactive

Federal Trade Commission Makes Fraud Data Public and Interactive

The Federal Trade Commission (FTC) is a U.S. federal agency charged with protecting consumers from unfair, deceptive and fraudulent practices in the marketplace, and ensuring competition by enforcing antitrust laws. In addition, the FTC also collects consumer complaints around data security, deceptive advertising and Do Not Call Violations, which are then made available to law enforcement agencies around the world.

On January 23, 2020, the FTC announced access to data showing insights into their refund program.

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Why Artificial Intelligence Is the Next-Generation Weapon to Fight Fraud

Why Artificial Intelligence Is the Next-Generation Weapon to Fight Fraud

As the world witnesses a surge in fraud incidents, leveraging artificial intelligence (AI) for fraud detection could be the key to saving millions of dollars in financial fraud losses. Organizations worldwide are increasing their investment in AI-based fraud detection solutions, indicating that the industry is bullish on the capabilities of AI in fraud.

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8 Underrated Critical Types of Evidence in Email Reviews

GUEST BLOGGER

Sundaraparipurnan Narayanan
Associate Director of Forensic Services, SKP Business Consulting

In the current electronic age, e-discovery is considered one of the key approaches for gathering evidence in litigation and investigations into misconduct. With new tools being created to help uncover and understand electronic data, the industry is evolving to new heights. When there is a large amount of data to review, the process requires a purpose-led approach to ensure the evidence is compiled objectively and accurately.

E-discovery reviews are based on keywords, timelines and communication patterns relevant to a purpose or defined objective. Amidst multiple aspects — like the nature of email threading, parent-child linkages, text analytics and communication patterns considered for review — the following eight elements are essential types of email evidence to not overlook in your examinations:

  • Calendar: A potential subject may schedule meetings that are contextually important to a case.
    Example: In a Foreign Corrupt Practices Act investigation, a calendar appointment with an individual at a posh restaurant a few days prior to the approval for a regulatory license may be relevant if the individual’s name in the appointment and the name of the public official providing the license are the same or similar.
  • Automatic email: Dates mentioned in an automated out of office response may be important for connecting a chain of events associated with a concerned individual.
    Example: If the dates of out of office responses sent during a vacation conflict with contract negotiation dates with a third party it may be a red flag to look into.
  • Travel and hotel information: Travel and hotel booking information can contain vital evidence.
    Example: In a kickback investigation, payment details as part of a travel or hotel booking voucher that contain the name of a payee/credit card holder may be relevant to correlate an employee’s relations with a suspected vendor/third party.
  • E-commerce purchases/email alerts: Alerts from e-commerce sites or courier agencies can play key roles in examinations.
    Example: A dispatch intimation from a shipper from a suspected third party to an employee’s personal address may be relevant for further enquiry in a conflict of interest or kickback investigation. Similarly, banks and financial institutions send alerts (on cash deposits, exceeding limits, swipe of card in unusual locations, etc.) as email alerts. These email alerts may be relevant in a chain of events to correlate and corroborate with the available information in the context of a review.
  • Group/other registrations: Email IDs registered with certain sites (gambling, pornographic or dating) and emails received from such sites may be relevant during investigations into misconduct.
  • Task classification (flagging): Task classification and completion are used for the convenience of tracking key activities/communications. Such tagging may highlight certain patterns.
    Example: A pattern of prioritizing the approval of third party invoices over others along with task classification by a user department representative, who is using the services of the concerned third party, may show possible indications of favoritism by the employee.
  • Self-emails, notes/task listing: Many individuals send emails to themselves as a reminder, notification, to-do list, etc.
    Example: A self-email by an accountant containing the phrase ”change estimations” may be relevant in a financial statement fraud. It is necessary to understand that some of the content mentioned in self-emails may not necessarily have the keywords identified as relevant for the case. Similarly, subjects may update their tasks/notes as part of their email service, which may contain messages of evidentiary value.
  • Folder structures: Every individual has a way of organizing their email communications. This includes the way the individual has classified their folders within their email service or the archival methodology they had adopted. These aspects provide necessary insights in understanding which folders contain relevant information.

Reviewing digital data for evidence requires objective-driven searches in order to understand and interpret a given circumstance. Awareness of possible alternative evidence provides the ability to anticipate and look for some of the above categories of communications in search of evidence. While not all these categories may be relevant in every case, these are vital ways to find the evidence needed to detect fraud.