Channel
@moneytraill
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
104subscribers
-16 since we began measuring on 20 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003976051690 |
|---|---|
| Type | Channel |
| Username | @moneytraill |
| Created | Between 1 April 2026 and 15 August 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 20 August 2026 |
| Last confirmed live | 15 September 2026 |
| Measurements held | 5 |
| Confirmed unchanged | 1 time, most recently 15 September 2026 |
| On Telegram | t.me/moneytraill |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 15 Sept 2026, 08:01 | 104 | -3 |
| 7 Sept 2026, 00:58 | 107 | -6 |
| 28 Aug 2026, 17:26 | 113 | -26 |
| 20 Aug 2026, 23:02 | 139 | +19 |
| 20 Aug 2026, 01:30 | 120 | first reading |
20 posts held, back to 15 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 19 August 2026. An engagement rate over an empty window would be a number about nothing.
13 reactions across 5 posts, in 7 distinct kinds. The most used accounts for 23.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 3 | 23.1% | |
| ❤ | 2 | 15.4% | |
| 👌 | 2 | 15.4% | |
| 👍 | 2 | 15.4% | |
| 👏 | 2 | 15.4% | |
| 🙏 | 1 | 7.69% | |
| 🤯 | 1 | 7.69% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 7 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 13 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 15 August 2026 to 19 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
🇺🇸 USA: Woman Loses $576K in Gold Bar Scam A 63-year-old Connecticut woman lost her entire $575,799 life savings after scammers posing as government and law enforcement officials convinced her she was under investigation for money laundering. Why it matters 👇 The victim converted much of her retirement savings into 105 one-ounce gold bars worth $354K, while another $173K was handed over in cash to couriers. One all…
🤯1
🇮🇳🇨🇳🇵🇰 India → China → Pakistan: International “Boss Scam” Network Uncovered Indian police uncovered an international cyber fraud network linked to China and Pakistan, seizing around 4,500 SIM cards and identifying 21,000 OTPs allegedly supplied to cybercriminals. Why it matters 👇 Investigators linked the infrastructure to 251 fraud cases across 26 Indian states, with Chinese malware, an Islamabad-based call center…
🇦🇺 Australia: Hundreds of Millions in Mortgage Fraud Uncovered Across 10 Major Banks Australia’s financial intelligence agency AUSTRAC uncovered potentially hundreds of millions of dollars in fraudulent mortgage loans across 10 major Australian banks. Why it matters 👇 Fraudulent applications used inflated incomes, fake employment records and fabricated businesses, while some loans were funded or repaid using offsho…
🇮🇳 India: 6 Arrested in Delhi Water Board Fraud Probe India’s Anti-Corruption Branch arrested former Delhi minister Satyendar Jain and five others over an alleged fraud involving contracts for sewage treatment plant projects. Why it matters 👇 Investigators traced ₹1.52 crore ($180K+) in alleged bribe money through intermediary companies and bank accounts linked to the former CEO of Delhi Jal Board and his relatives…
🇲🇾 Malaysia: Investment Firm Director Faces RM13.4M Money Laundering Charges Malaysian prosecutors filed 10 new charges against investment firm director Norliza Mohd Noor for allegedly receiving RM13.4 million ($3.2M+) in proceeds from illegal activities. Why it matters 👇 The funds were allegedly moved through cheques and bank transfers into her personal account and an account linked to the company. Source: Malays…
🇺🇸 USA: Businessman Charged in $24M Bank Fraud U.S. prosecutors charged Thomas Mwangi, former owner of Georgia-based manufacturer CAMaster, with allegedly obtaining $24 million in fraudulent loans from First Financial Bank. Why it matters 👇 Prosecutors say Mwangi fabricated financial records and claimed to have $22 million in a brokerage account when he actually had less than $1 million. The bank allegedly lost mor…
🇫🇷 France: 912 Crédit Agricole Accounts Compromised in Phishing Operation A sophisticated phishing network compromised 912 Crédit Agricole customers, collecting banking credentials and detailed account information through fake bank pages. Why it matters 👇 The stolen data — including balances, branch details and adviser names — was used for targeted calls impersonating bank employees. 83 victims ultimately sent mone…
❤1👌1🔥1
🇰🇪 Kenya: 9 Arrested in KSh1.57B Treasury Fraud Case Kenya’s anti-corruption agency arrested 9 suspects, including senior Treasury officials, over the alleged theft of KSh1.57 billion ($12M+) from a government financial inclusion programme. Why it matters 👇 Investigators say KSh175 million was routed through an unauthorized bank account, laundered and largely withdrawn in cash. Source: EACC Money Trail #Fraud #AML…
👌1👍1🔥1
🇺🇸 USA: $165M Crypto Ponzi Suspect Deported from Fiji Edward Zimbardi was deported from Fiji to the U.S. to face federal charges over an alleged $165 million crypto Ponzi scheme involving more than 6,000 investors. Why it matters 👇 Prosecutors allege investors were promised 25% monthly returns, while funds were used to pay earlier investors, make risky trades and cover personal expenses. Source: U.S. Department of…
❤1👍1👏1
🇮🇳🇨🇳 India → China: $128M Cyber Fraud Network Uncovered Indian police arrested an alleged financial handler linked to 1,090 cyber fraud cases worth ₹1,071.5 crore ($128M+). Why it matters 👇 Stolen funds were split across 1,754 bank accounts, converted into cryptocurrency and allegedly sent to criminal networks in China. Source: Gujarat CID Money Trail #Fraud #Crypto #Banking #India #China
👏1🔥1🙏1
🇺🇸 USA: Woman Loses $4.3M in Fake FBI Crypto Scam An Arizona woman lost more than $4.3 million after scammers posing as FBI and NYPD officers convinced her she was under investigation for money laundering. Why it matters 👇 Over two months, the victim transferred $4.3M+ in cryptocurrency, which was then moved through multiple accounts that investigators have been unable to trace. Source: Yavapai County Sheriff’s Of…
🇳🇬 Nigeria: ₦1.34B Stolen Through Access Bank’s Online Banking Fraudsters allegedly transferred ₦1.34 billion ($900K+) without authorization from four Access Bank customer accounts through its SME banking app. The funds were routed across accounts linked to 71 banks and fintechs. Why it matters 👇 A Nigerian court ordered the receiving accounts and linked BVNs frozen to prevent further movement of the stolen funds. …
Showing the 12 most recent of 20 posts we hold for @moneytraill. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Named by 3 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 15 September 2026 — this entry's latest reading, not the date you are reading this.
“Money Trail” (@moneytraill), 104 subscribers as measured 15 September 2026. Telegram Register, tgregister.com/channel/moneytraill.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.