Townhall84%

Gang Member's Instagram Cash Flexes Unravel $2.8M Fraud Ring 4%

By Scott McClallen27%

7/17/2026, 2:00:27 PM

BS Summary: This article contains 7 faulty reasoning types, including Appeal to Emotion, Indoctrination, and Attempt to Sell a Product or Service, with Biased Writer Voice as the most egregious example at 9.5% saturation with 44 hits. Analysis detected 182 faulty-reasoning hits from 465 analyzed words, generating a BS Score of 17.4% and a BS Rank of 4% (21,112 of 21,887 articles). This article is better (less manipulative) than 96.50% of the article peer group.

A member of the South Los Angeles-based Crips street gang was sentenced to 108 months in federal prison for a $2.8 million scheme in which he stole checks in the mail, altered them, then used Instagram to recruit bank account holders to give him access to their accounts so he could deposit the checks and quickly withdraw the funds before banks could detect the fraud. 
Chase Matthew Griffin, 26, a.k.a. 
“Trey,” of Atlanta, who also resided in Ontario and South Los Angeles, was sentenced by United States District Judge Josephine L. 
Staton, who also ordered him to pay $307,386 in restitution. 
Griffin pleaded guilty on March 5 to one count of conspiracy to commit bank fraud. 
He has been in federal custody since September 2025. 
According to court documents, from 2022 to September 2025, Griffin participated in a criminal conspiracy in which he and others obtained checks stolen from the mail, then altered them or created counterfeit versions so they appeared to be payable to their accomplices. 
After he recruited an accomplice, Griffin and his co-conspirators deposited these fraudulent checks, which were typically for tens of thousands of dollars, into the accomplice’s bank account, then raced to withdraw the funds before the bank could detect the fraud. 
For example, in December 2023, a North Hollywood business reported to law enforcement that it had mailed three checks totaling approximately $84,490 from a United States Postal Service collection box in Tarzana. 
However, the checks were stolen and then deposited into JPMorgan Chase accounts not belonging to the intended recipients. 
The business representative provided images of the checks that had been deposited and confirmed the listed payee on each check had been changed from the intended recipient. 
A law enforcement review of a Chase bank account where one of those checks was deposited revealed a previous deposit of approximately $22,487 made at an ATM in Upland. 
This check, along with another check for approximately $29,081, was stolen and used to create counterfeit checks with the same date, check number, and amount as the original, but with different payees. 
The money was quickly withdrawn from the account and used for ATM withdrawals, Zelle and CashApp payments, a plane ticket, and card purchases at a San Bernardino County casino. 
Law enforcement later traced the scheme to Griffin. 
The United States Postal Inspection Service investigated this matter with assistance from the Upland Police Department. 
Assistant United States Attorney Andrew Brown of the Major Frauds Section prosecuted this case. 
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Article reasoning-pattern comparisonThis article: 0.0%Scott McClallen: 2.4%Townhall: 5.3%Confirmation Bias0.0%This article: 0.0%Scott McClallen: 0.8%Townhall: 0.7%Anchoring Bias0.0%This article: 0.0%Scott McClallen: 1.5%Townhall: 2.8%Availability Heuristic0.0%This article: 0.0%Scott McClallen: 0.7%Townhall: 0.8%Representativeness Heuristic0.0%This article: 0.0%Scott McClallen: 0.4%Townhall: 0.7%Hindsight Bias0.0%This article: 0.0%Scott McClallen: 1.3%Townhall: 1.7%Overconfidence Bias0.0%This article: 0.0%Scott McClallen: 7.7%Townhall: 11.2%Framing Effect0.0%This article: 0.0%Scott McClallen: 0.2%Townhall: 0.4%Loss Aversion0.0%This article: 0.0%Scott McClallen: 0.2%Townhall: 0.3%Status Quo Bias0.0%This article: 0.0%Scott McClallen: 0.1%Townhall: 0.1%Sunk Cost Effect0.0%This article: 0.0%Scott McClallen: 0.8%Townhall: 1.4%Optimism Bias0.0%This article: 0.0%Scott McClallen: 0.9%Townhall: 1.9%Pessimism Bias0.0%This article: 0.0%Scott McClallen: 8.5%Townhall: 13.5%Negativity Bias0.0%This article: 0.0%Scott McClallen: 1.9%Townhall: 1.8%Self-Serving Bias0.0%This article: 0.0%Scott McClallen: 0.8%Townhall: 1.8%Fundamental Attribution Error0.0%This article: 0.0%Scott McClallen: 0.1%Townhall: 0.1%Actor-Observer Bias0.0%This article: 0.0%Scott McClallen: 2.8%Townhall: 4.6%In-Group Bias0.0%This article: 3.7%Scott McClallen: 0.9%Townhall: 3.2%Out-Group Homogeneity Bias3.7%This article: 0.0%Scott McClallen: 1.4%Townhall: 1.8%Halo Effect0.0%This article: 0.0%Scott McClallen: 0.4%Townhall: 0.9%Horn Effect0.0%This article: 0.0%Scott McClallen: 0.0%Townhall: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Scott McClallen: 0.5%Townhall: 1.3%Recency Bias0.0%This article: 0.0%Scott McClallen: 0.3%Townhall: 0.6%Primacy Effect0.0%This article: 0.0%Scott McClallen: 0.0%Townhall: 0.0%Blind-Spot Bias0.0%This article: 3.7%Scott McClallen: 1.5%Townhall: 5.0%Ad Hominem3.7%This article: 0.0%Scott McClallen: 0.5%Townhall: 2.0%Straw Man0.0%This article: 0.0%Scott McClallen: 4.2%Townhall: 4.4%Appeal to Authority0.0%This article: 0.0%Scott McClallen: 0.7%Townhall: 1.9%False Dilemma0.0%This article: 0.0%Scott McClallen: 0.5%Townhall: 1.6%Slippery Slope0.0%This article: 0.0%Scott McClallen: 0.1%Townhall: 0.2%Circular Reasoning0.0%This article: 0.0%Scott McClallen: 2.3%Townhall: 9.1%Hasty Generalization0.0%This article: 0.0%Scott McClallen: 0.1%Townhall: 0.6%Red Herring0.0%This article: 0.0%Scott McClallen: 0.7%Townhall: 1.3%Bandwagon0.0%This article: 6.5%Scott McClallen: 10.3%Townhall: 11.1%Appeal to Emotion6.5%This article: 0.0%Scott McClallen: 1.1%Townhall: 2.2%Begging the Question0.0%This article: 0.0%Scott McClallen: 1.4%Townhall: 2.4%Post Hoc (False Cause)0.0%This article: 0.0%Scott McClallen: 0.0%Townhall: 0.6%Tu Quoque0.0%This article: 0.0%Scott McClallen: 0.7%Townhall: 1.5%Burden of Proof0.0%This article: 0.0%Scott McClallen: 0.1%Townhall: 0.1%Appeal to Nature0.0%This article: 0.0%Scott McClallen: 0.1%Townhall: 0.1%Composition/Division0.0%This article: 0.0%Scott McClallen: 0.2%Townhall: 1.4%Anecdotal0.0%This article: 0.0%Scott McClallen: 0.0%Townhall: 0.1%No True Scotsman0.0%This article: 0.0%Scott McClallen: 1.7%Townhall: 2.2%Ambiguity (Equivocation)0.0%This article: 0.0%Scott McClallen: 0.0%Townhall: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Scott McClallen: 0.0%Townhall: 0.1%Middle Ground0.0%This article: 0.0%Scott McClallen: 0.0%Townhall: 0.2%Personal Incredulity0.0%This article: 0.0%Scott McClallen: 0.0%Townhall: 0.2%Special Pleading0.0%This article: 0.0%Scott McClallen: 0.0%Townhall: 0.4%Genetic Fallacy0.0%This article: 0.0%Scott McClallen: 2.0%Townhall: 3.4%Unattributed Quote0.0%This article: 0.0%Scott McClallen: 3.2%Townhall: 3.0%Quote-first Misdirection0.0%This article: 9.5%Scott McClallen: 5.5%Townhall: 16.1%Biased Writer Voice9.5%This article: 6.5%Scott McClallen: 4.0%Townhall: 5.6%Indoctrination6.5%This article: 0.0%Scott McClallen: 0.1%Townhall: 0.2%Politically Left Leaning Bias0.0%This article: 3.7%Scott McClallen: 5.5%Townhall: 13.8%Politically Right Leaning Bias3.7%This article: 5.8%Scott McClallen: 3.8%Townhall: 5.0%Attempt to Sell a Product or S…5.8%

465 words analyzed.

Speakers

No attributed speakers were identified in this analysis.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.