Официальный канал Финансового университета при Правительстве Российской Федерации
Предложить новость или задать вопрос: @finuniversitet_bot
Сайт: fa.ru
VK: vk.com/finuniversity
Rutube: rutube.ru/u/finuniver/
МАХ: max.ru/finuniversity
Created
26 September 2016 — measured — cross-checked against a third-party dataset (ext.tg_channel)
Other / unclassifiable — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 58% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
35 measurements spanning 43 days, net +1,648. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 25,298–27,541 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 35
Measured (UTC)
Subscribers
Change
17 Sept 2026, 15:39
27,205
-16
15 Sept 2026, 16:59
27,221
+2
14 Sept 2026, 01:01
27,219
-25
12 Sept 2026, 09:41
27,244
-37
10 Sept 2026, 05:35
27,281
+7
6 Sept 2026, 23:19
27,274
-8
4 Sept 2026, 06:41
27,282
+44
2 Sept 2026, 16:34
27,238
+65
1 Sept 2026, 18:54
27,173
+57
31 Aug 2026, 21:43
27,116
+1
30 Aug 2026, 23:54
27,115
+6
30 Aug 2026, 03:04
27,109
-12
29 Aug 2026, 01:09
27,121
+21
28 Aug 2026, 03:42
27,100
+47
27 Aug 2026, 00:24
27,053
+22
25 Aug 2026, 21:04
27,031
+74
24 Aug 2026, 23:52
26,957
+79
23 Aug 2026, 12:59
26,878
+172
21 Aug 2026, 20:57
26,706
+194
20 Aug 2026, 18:02
26,512
first reading
Engagement
103 posts held, back to 31 July 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 60 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
11.7%
avg views ÷ 27,205 subscribers
Avg views / post
3,200
43 posts measured
Reaction rate
1.06%
reactions ÷ views · ER floor
Posts in window
43
of 103 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 19 September 2026
Posts held
103 (31 July 2026 – 19 September 2026)
Views total
137,410
Reactions total
1,462
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
19 Sept 2026, 16:23 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Photos
≈7,190
Videos
≈248
Links
≈7,640
Lifetime counters from Telegram’s own channel header, read 19 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
47m 05s
Average length
6m 44s
Measured directly from 7 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
4,074 reactions across 97 posts, in 18 distinct kinds. The most used accounts for 55.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
2,249
55.2%
🔥
494
12.1%
❤🔥
479
11.8%
custom 5323288436390504312
196
4.81%
👍
164
4.03%
custom 5346217686235911159
153
3.76%
🎉
71
1.74%
🕊
62
1.52%
😍
38
0.933%
⚡
37
0.908%
💔
35
0.859%
🙏
30
0.736%
👀
26
0.638%
🏆
12
0.295%
🤝
11
0.27%
😎
6
0.147%
🤩
6
0.147%
💯
5
0.123%
Custom emoji. 2 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegram’s.
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 103 of the 103 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 4,295 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 103 most recent posts we hold, published 31 July 2026 to 19 September 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.
Telegram Stars
Stars received
7
across the posts below
Posts paid on
4
of 103 we hold a reading for · 4%
Most on one post
4
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @finuniverchan. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 103 most recent posts we hold for this entry, published 31 July 2026 to 19 September 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
✔️ Ректор Финуниверситета проголосовал онлайн
Ректор Финансового университета Станислав Прокофьев принял участие в выборах депутатов Государственной Думы дистанционно — через электронное голосование
Еще несколько лет назад проголосовать можно было только одним способом — лично, на своем участке. Сегодня достаточно телефона и нескольких минут
✅ Электронное голосование идет с 18 по 20 сентября.
Проголосовать можно …
Стартовала регистрация на Всероссийскую шахматную киберлигу «Ход за тобой» 🎉
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3️…
МФФ-2026
🔗 21 сентября ректор Станислав Прокофьев выступит на деловой сессии «Государственные средства – драйвер развития денежного рынка России», которая пройдет в рамках работы Московского финансового форума — 2026
Состояние денежного рынка — один из ключевых маркеров финансового развития государства 💡
💬 Как госсредства уже сегодня меняют рынок?
💬 Какое влияние на его участников оказывают проекты Казначейства Ро…
Авторский коллектив Финансового университета стал лауреатом премии имени С. И. Мосина 🎓
🔗 Награда входит в число наиболее известных российских премий в области научно-технических исследований и разработок
Премия присуждена за работу «Система поддержки принятия решений в информационно-управляющей системе мониторинга космического пространства в условиях стохастических деструктивных воздействий»
📎 Торжественная церем…
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В Risk Research Сбера открываем набор стажёров по трём направлениям для студентов из Москвы, Санкт-Петербурга и Владивостока
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AI-агенты, multi-agent системы, SFT, LoRA, GRPO, RL и reasoning
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Модели ценообразования и риск-метрик, финансовые рынки, transformers, diffusion, VAE, LLM и RL
3️⃣Data…
Ваша сила — в ваших компетенциях! ✈️
📎 Паспорт компетенций — это документ, подтверждающий прохождение студентом тестирования на платформе АНО «Россия — страна возможностей» ✨
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В Финуниверситете обсудили принципы использования ИИ в клиентских сервисах 💡
🔗17 сентября в пространстве Цифровой учебной биржи MOEX LAB в Финансовом университете состоялась первая встреча Клуба Банка России по клиентоцентричности «Я - Клиент»
Центральной темой встречи стало применение ИИ в клиентских сервисах и его влияние на качество взаимодействия финансовых организаций с клиентами ✔️
Мероприятие стало началом …
Голос каждого из вас имеет важное значение для будущего нашей Родины!
🔗 Совсем скоро состоится знаковое событие в жизни нашей страны – с 18 по 20 сентября пройдут выборы депутатов Государственной Думы Федерального Собрания Российской Федерации
✔️Проголосовать на выборах депутатов Госдумы можно на избирательном участке лично или онлайн, если ранее была подана соответствующая заявка
Важно: не переходите по подозрите…
Вперёд, к победам! Презентация регбийного клуба «Финансовый университет»
🔗 13 сентября состоялась презентация регбийного клуба «Финансовый университет» на 2026/2027 учебный год
Команда открыла новую главу своей истории: гостям представили игровую форму Artletica с обновленным логотипом клуба
🔍 Регбийный клуб «Финансовый университет» благодарит Федерацию регби Москвы, а также партнеров и всех гостей презентации за …
Поступить на бюджет? Начните с олимпиады! 🎓
💬 Подготовительные курсы Финуниверситета запускают программу комплексной подготовки к олимпиадам для учащихся 10-11 классов
Направления олимпиады (предметы на выбор) ⬇️
▫️ Экономика — 2 уровень
▫️ Обществознание — 3 уровень
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Организатор — Фонд «Росконгресс» при поддержке Правительства РФ 💡
Ведущий научный сотрудник Института региональной экономики и межбюджетных отношений Финансового университета Андрей Жуковский выступил спикером основной программы на сессии «Цифровая трансформация строител…
❤10🔥3❤🔥1
Showing the 12 most recent of 103 posts we hold for @finuniverchan. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Posts edited after publishing
@finuniverchan edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
19 August 2026
Most recent edit
19 August 2026
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 30 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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.
Cross-platform identity — Wikidata
A Wikidata item names this Telegram handle as belonging to the entity it describes. This is Wikidata’s claim, not a verification made by this register — nobody here confirmed that the account is genuinely operated by the entity named. Wikidata content is CC0; every fact below is dated to when it was read from Wikidata, not to when the association was first made there.
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 17 September 2026 — this
entry's latest reading, not the date you are reading this.
“Финансовый университет” (@finuniverchan), 27,205 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/finuniverchan.
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.