Prism Geo · city intelligence · pilot
Prism Geo · Rankings · Cryptocurrency Scam
Corruption Fraud · evidence ranking · 2021–2025

Which Indian cities show the strongest cryptocurrency scam reporting signal?

A comparison of 45 Indian cities covered by Prism Geo. 15 pass the evidence gates and are ranked by exact cryptocurrency_scam-tagged news reports per 10,000 civic reports. This measures the prominence of a topic in coverage—not real-world incidence, prevalence, or safety.

Geographic view · 15 city-linked districts

Where the cryptocurrency scam reporting signal is concentrated

Every highlighted polygon is the 2021 administrative district containing a ranked city's coordinate. Color shows the city's reporting-signal rank band—not a measured district-wide rate, prevalence, or severity assessment.

Ranks 1–5Ranks 6–10Ranks 11–15 Not ranked
Indian districts containing cities in the cryptocurrency scam reporting ranking India's national silhouette has a soft boundary shadow. District lines are subdued, while the 15 districts containing ranked cities are highlighted by rank. #8 Indore — Indore district proxy — 4.41 tagged reports per 10,000 civic reports#10 Gurugram — Gurgaon district proxy — 3.36 tagged reports per 10,000 civic reports#14 Chandigarh — Chandigarh district proxy — 1.34 tagged reports per 10,000 civic reports#7 Raipur — Raipur district proxy — 5.61 tagged reports per 10,000 civic reports#4 Dehradun — Dehradun district proxy — 6.15 tagged reports per 10,000 civic reports#12 Kolkata — Kolkata district proxy — 1.60 tagged reports per 10,000 civic reports#6 Bengaluru — Bangalore district proxy — 5.67 tagged reports per 10,000 civic reports#3 Pune — Pune district proxy — 6.62 tagged reports per 10,000 civic reports#1 Thane — Thane district proxy — 17.48 tagged reports per 10,000 civic reports#13 Mumbai — Mumbai Suburban district proxy — 1.34 tagged reports per 10,000 civic reports#5 Nagpur — Nagpur district proxy — 5.74 tagged reports per 10,000 civic reports#9 Bhubaneswar — Khordha district proxy — 3.45 tagged reports per 10,000 civic reports#2 Jodhpur — Jodhpur district proxy — 15.36 tagged reports per 10,000 civic reports#11 Noida — Gautam Buddha Nagar district proxy — 2.46 tagged reports per 10,000 civic reports#15 New Delhi — Central district proxy — 1.21 tagged reports per 10,000 civic reports

Boundary geometry: geoBoundaries, ADM2, 2021 representation, Open Data Commons Open Database License 1.0. Districts are visual locators for city-ranked data and may not reflect later administrative changes.

How to read this ranking

Thane leads the normalized comparison at 17.48 tagged reports per 10,000 civic reports. New Delhi leads raw volume with 36 reports. The two leaders can differ because normalization controls for each city's overall civic-news footprint.

Cities evaluated
45
existing India profiles
Cities ranked
15
passed both evidence gates
Normalized leader
Thane
17.48 per 10K
Raw-volume leader
New Delhi
36 tagged reports
Largest recent rise
Thane
+14.43 per-10K points
National comparison
+0.37
recent per-10K change
Computed findings
What stands out
Complete ranking
Primary and companion measures

Cryptocurrency Scam reporting signal by city

The primary rank uses tagged reports per 10,000 civic reports. Raw rank, recent change, and active years show whether a result depends on city size, timing, or a narrow burst.

RankCitySignal / 10KTagged reportsRaw rankRecent changeActive years
1Thane
Maharashtra
17.48135+14.434/5
2Jodhpur
Rajasthan
15.36511+15.553/5
3Pune
Maharashtra
6.62243-0.295/5
4Dehradun
Uttarakhand
6.1568+13.412/5
5Nagpur
Maharashtra
5.7469-0.422/5
6Bengaluru
Karnataka
5.67332-5.615/5
7Raipur
Chhattisgarh
5.61514+9.853/5
8Indore
Madhya Pradesh
4.41510-3.453/5
9Bhubaneswar
Odisha
3.4567-1.542/5
10Gurugram
Haryana
3.3686-4.003/5
11Noida
Uttar Pradesh
2.46513-2.133/5
12Kolkata
West Bengal
1.60512-0.613/5
13Mumbai
Maharashtra
1.34164+0.745/5
14Chandigarh
Chandigarh
1.34315+0.073/5
15New Delhi
Delhi
1.21361+1.125/5

A city qualifies with at least 3 exact-tag reports and 300 total civic reports across complete years 2021–2025.

City-by-city evidence
Normalized #1 · raw-volume #5 · qualified coverage base

Thane: Cryptocurrency Scam reporting profile

13 tagged reports appeared within 7,439 civic reports in 2021–2025, equal to 17.48 per 10,000. The recent-period comparison shows a rising share of local civic coverage: 12.42 in 2021–2023 versus 26.85 in 2024–2025. The city's peak normalized year was 2024.

Normalized signal
17.48
per 10K civic reports
Tagged coverage
13
4 active years
Recent change
+14.43
per-10K points
Action marker
15.4%
classifier coverage
20212025
Annual evidence
2021 · 0.00/10K (0 reports)2022 · 12.00/10K (2 reports)2023 · 19.31/10K (4 reports)2024 · 34.67/10K (5 reports)2025 · 17.17/10K (2 reports)
Classifier category mix
Corruption Fraud · 13

The classifier marked authority or institutional action in 2 reports (15.4%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Thane's broader civic problems analysis →
Normalized #2 · raw-volume #11 · qualified coverage base

Jodhpur: Cryptocurrency Scam reporting profile

5 tagged reports appeared within 3,256 civic reports in 2021–2025, equal to 15.36 per 10,000. The recent-period comparison shows a rising share of local civic coverage: 9.68 in 2021–2023 versus 25.23 in 2024–2025. The city's peak normalized year was 2025.

Normalized signal
15.36
per 10K civic reports
Tagged coverage
5
3 active years
Recent change
+15.55
per-10K points
Action marker
60.0%
classifier coverage
20212025
Annual evidence
2021 · 0.00/10K (0 reports)2022 · 23.01/10K (2 reports)2023 · 0.00/10K (0 reports)2024 · 21.51/10K (1 reports)2025 · 27.62/10K (2 reports)
Classifier category mix
Corruption Fraud · 5

The classifier marked authority or institutional action in 3 reports (60.0%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Jodhpur's broader civic problems analysis →
Normalized #3 · raw-volume #3 · established coverage base

Pune: Cryptocurrency Scam reporting profile

24 tagged reports appeared within 36,239 civic reports in 2021–2025, equal to 6.62 per 10,000. The recent-period comparison shows a broadly stable share of local civic coverage: 6.75 in 2021–2023 versus 6.46 in 2024–2025. The city's peak normalized year was 2022.

Normalized signal
6.62
per 10K civic reports
Tagged coverage
24
5 active years
Recent change
-0.29
per-10K points
Action marker
12.5%
classifier coverage
20212025
Annual evidence
2021 · 1.65/10K (1 reports)2022 · 13.71/10K (10 reports)2023 · 4.07/10K (3 reports)2024 · 9.86/10K (8 reports)2025 · 2.71/10K (2 reports)
Classifier category mix
Corruption Fraud · 24

The classifier marked authority or institutional action in 3 reports (12.5%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Pune's broader civic problems analysis →
Normalized #4 · raw-volume #8 · qualified coverage base

Dehradun: Cryptocurrency Scam reporting profile

6 tagged reports appeared within 9,750 civic reports in 2021–2025, equal to 6.15 per 10,000. The recent-period comparison shows a rising share of local civic coverage: 0.00 in 2021–2023 versus 13.41 in 2024–2025. The city's peak normalized year was 2025.

Normalized signal
6.15
per 10K civic reports
Tagged coverage
6
2 active years
Recent change
+13.41
per-10K points
Action marker
16.7%
classifier coverage
20212025
Annual evidence
2021 · 0.00/10K (0 reports)2022 · 0.00/10K (0 reports)2023 · 0.00/10K (0 reports)2024 · 4.22/10K (1 reports)2025 · 23.74/10K (5 reports)
Classifier category mix
Corruption Fraud · 6

The classifier marked authority or institutional action in 1 reports (16.7%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Dehradun's broader civic problems analysis →
Normalized #5 · raw-volume #9 · qualified coverage base

Nagpur: Cryptocurrency Scam reporting profile

6 tagged reports appeared within 10,447 civic reports in 2021–2025, equal to 5.74 per 10,000. The recent-period comparison shows a broadly stable share of local civic coverage: 5.89 in 2021–2023 versus 5.47 in 2024–2025. The city's peak normalized year was 2022.

Normalized signal
5.74
per 10K civic reports
Tagged coverage
6
2 active years
Recent change
-0.42
per-10K points
Action marker
50.0%
classifier coverage
20212025
Annual evidence
2021 · 0.00/10K (0 reports)2022 · 15.53/10K (4 reports)2023 · 0.00/10K (0 reports)2024 · 12.85/10K (2 reports)2025 · 0.00/10K (0 reports)
Classifier category mix
Corruption Fraud · 6

The classifier marked authority or institutional action in 3 reports (50.0%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Nagpur's broader civic problems analysis →
Normalized #6 · raw-volume #2 · established coverage base

Bengaluru: Cryptocurrency Scam reporting profile

33 tagged reports appeared within 58,199 civic reports in 2021–2025, equal to 5.67 per 10,000. The recent-period comparison shows a falling share of local civic coverage: 8.42 in 2021–2023 versus 2.81 in 2024–2025. The city's peak normalized year was 2023.

Normalized signal
5.67
per 10K civic reports
Tagged coverage
33
5 active years
Recent change
-5.61
per-10K points
Action marker
6.1%
classifier coverage
20212025
Annual evidence
2021 · 9.52/10K (6 reports)2022 · 2.78/10K (3 reports)2023 · 12.69/10K (16 reports)2024 · 5.25/10K (7 reports)2025 · 0.66/10K (1 reports)
Classifier category mix
Corruption Fraud · 30Crime & violence · 3

The classifier marked authority or institutional action in 2 reports (6.1%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Bengaluru's broader civic problems analysis →
Normalized #7 · raw-volume #14 · qualified coverage base

Raipur: Cryptocurrency Scam reporting profile

5 tagged reports appeared within 8,910 civic reports in 2021–2025, equal to 5.61 per 10,000. The recent-period comparison shows a rising share of local civic coverage: 1.82 in 2021–2023 versus 11.67 in 2024–2025. The city's peak normalized year was 2024.

Normalized signal
5.61
per 10K civic reports
Tagged coverage
5
3 active years
Recent change
+9.85
per-10K points
Action marker
40.0%
classifier coverage
20212025
Annual evidence
2021 · 0.00/10K (0 reports)2022 · 0.00/10K (0 reports)2023 · 4.11/10K (1 reports)2024 · 19.47/10K (3 reports)2025 · 5.30/10K (1 reports)
Classifier category mix
Corruption Fraud · 5

The classifier marked authority or institutional action in 2 reports (40.0%) and conclusion language in 1 (20.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Raipur's broader civic problems analysis →
Normalized #8 · raw-volume #10 · qualified coverage base

Indore: Cryptocurrency Scam reporting profile

5 tagged reports appeared within 11,332 civic reports in 2021–2025, equal to 4.41 per 10,000. The recent-period comparison shows a falling share of local civic coverage: 5.74 in 2021–2023 versus 2.29 in 2024–2025. The city's peak normalized year was 2021.

Normalized signal
4.41
per 10K civic reports
Tagged coverage
5
3 active years
Recent change
-3.45
per-10K points
Action marker
60.0%
classifier coverage
20212025
Annual evidence
2021 · 12.66/10K (2 reports)2022 · 7.81/10K (2 reports)2023 · 0.00/10K (0 reports)2024 · 5.49/10K (1 reports)2025 · 0.00/10K (0 reports)
Classifier category mix
Corruption Fraud · 5

The classifier marked authority or institutional action in 3 reports (60.0%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Indore's broader civic problems analysis →
Normalized #9 · raw-volume #7 · qualified coverage base

Bhubaneswar: Cryptocurrency Scam reporting profile

6 tagged reports appeared within 17,398 civic reports in 2021–2025, equal to 3.45 per 10,000. The recent-period comparison shows a falling share of local civic coverage: 4.13 in 2021–2023 versus 2.59 in 2024–2025. The city's peak normalized year was 2023.

Normalized signal
3.45
per 10K civic reports
Tagged coverage
6
2 active years
Recent change
-1.54
per-10K points
Action marker
83.3%
classifier coverage
20212025
Annual evidence
2021 · 0.00/10K (0 reports)2022 · 0.00/10K (0 reports)2023 · 11.54/10K (4 reports)2024 · 0.00/10K (0 reports)2025 · 4.99/10K (2 reports)
Classifier category mix
Corruption Fraud · 6

The classifier marked authority or institutional action in 5 reports (83.3%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Bhubaneswar's broader civic problems analysis →
Normalized #10 · raw-volume #6 · qualified coverage base

Gurugram: Cryptocurrency Scam reporting profile

8 tagged reports appeared within 23,841 civic reports in 2021–2025, equal to 3.36 per 10,000. The recent-period comparison shows a falling share of local civic coverage: 5.01 in 2021–2023 versus 1.01 in 2024–2025. The city's peak normalized year was 2022.

Normalized signal
3.36
per 10K civic reports
Tagged coverage
8
3 active years
Recent change
-4.00
per-10K points
Action marker
12.5%
classifier coverage
20212025
Annual evidence
2021 · 0.00/10K (0 reports)2022 · 8.74/10K (5 reports)2023 · 3.64/10K (2 reports)2024 · 0.00/10K (0 reports)2025 · 2.12/10K (1 reports)
Classifier category mix
Corruption Fraud · 8

The classifier marked authority or institutional action in 1 reports (12.5%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Gurugram's broader civic problems analysis →
Normalized #11 · raw-volume #13 · qualified coverage base

Noida: Cryptocurrency Scam reporting profile

5 tagged reports appeared within 20,361 civic reports in 2021–2025, equal to 2.46 per 10,000. The recent-period comparison shows a falling share of local civic coverage: 3.33 in 2021–2023 versus 1.20 in 2024–2025. The city's peak normalized year was 2022.

Normalized signal
2.46
per 10K civic reports
Tagged coverage
5
3 active years
Recent change
-2.13
per-10K points
Action marker
100.0%
classifier coverage
20212025
Annual evidence
2021 · 3.08/10K (1 reports)2022 · 6.47/10K (3 reports)2023 · 0.00/10K (0 reports)2024 · 1.96/10K (1 reports)2025 · 0.00/10K (0 reports)
Classifier category mix
Corruption Fraud · 5

The classifier marked authority or institutional action in 5 reports (100.0%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Noida's broader civic problems analysis →
Normalized #12 · raw-volume #12 · qualified coverage base

Kolkata: Cryptocurrency Scam reporting profile

5 tagged reports appeared within 31,282 civic reports in 2021–2025, equal to 1.60 per 10,000. The recent-period comparison shows a broadly stable share of local civic coverage: 1.90 in 2021–2023 versus 1.29 in 2024–2025. The city's peak normalized year was 2023.

Normalized signal
1.60
per 10K civic reports
Tagged coverage
5
3 active years
Recent change
-0.61
per-10K points
Action marker
60.0%
classifier coverage
20212025
Annual evidence
2021 · 0.00/10K (0 reports)2022 · 1.55/10K (1 reports)2023 · 3.70/10K (2 reports)2024 · 1.94/10K (2 reports)2025 · 0.00/10K (0 reports)
Classifier category mix
Corruption Fraud · 5

The classifier marked authority or institutional action in 3 reports (60.0%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Kolkata's broader civic problems analysis →
Normalized #13 · raw-volume #4 · qualified coverage base

Mumbai: Cryptocurrency Scam reporting profile

16 tagged reports appeared within 119,517 civic reports in 2021–2025, equal to 1.34 per 10,000. The recent-period comparison shows a broadly stable share of local civic coverage: 1.06 in 2021–2023 versus 1.80 in 2024–2025. The city's peak normalized year was 2025.

Normalized signal
1.34
per 10K civic reports
Tagged coverage
16
5 active years
Recent change
+0.74
per-10K points
Action marker
31.2%
classifier coverage
20212025
Annual evidence
2021 · 0.43/10K (1 reports)2022 · 1.40/10K (4 reports)2023 · 1.28/10K (3 reports)2024 · 0.48/10K (1 reports)2025 · 3.00/10K (7 reports)
Classifier category mix
Corruption Fraud · 16

The classifier marked authority or institutional action in 5 reports (31.2%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Mumbai's broader civic problems analysis →
Normalized #14 · raw-volume #15 · qualified coverage base

Chandigarh: Cryptocurrency Scam reporting profile

3 tagged reports appeared within 22,311 civic reports in 2021–2025, equal to 1.34 per 10,000. The recent-period comparison shows a broadly stable share of local civic coverage: 1.32 in 2021–2023 versus 1.39 in 2024–2025. The city's peak normalized year was 2024.

Normalized signal
1.34
per 10K civic reports
Tagged coverage
3
3 active years
Recent change
+0.07
per-10K points
Action marker
33.3%
classifier coverage
20212025
Annual evidence
2021 · 2.32/10K (1 reports)2022 · 1.73/10K (1 reports)2023 · 0.00/10K (0 reports)2024 · 2.60/10K (1 reports)2025 · 0.00/10K (0 reports)
Classifier category mix
Corruption Fraud · 3

The classifier marked authority or institutional action in 1 reports (33.3%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open Chandigarh's broader civic problems analysis →
Normalized #15 · raw-volume #1 · established coverage base

New Delhi: Cryptocurrency Scam reporting profile

36 tagged reports appeared within 297,207 civic reports in 2021–2025, equal to 1.21 per 10,000. The recent-period comparison shows a rising share of local civic coverage: 0.77 in 2021–2023 versus 1.89 in 2024–2025. The city's peak normalized year was 2025.

Normalized signal
1.21
per 10K civic reports
Tagged coverage
36
5 active years
Recent change
+1.12
per-10K points
Action marker
30.6%
classifier coverage
20212025
Annual evidence
2021 · 1.10/10K (5 reports)2022 · 1.08/10K (7 reports)2023 · 0.28/10K (2 reports)2024 · 0.97/10K (6 reports)2025 · 2.91/10K (16 reports)
Classifier category mix
Corruption Fraud · 33Crime & violence · 2Policing & law enforcement · 1

The classifier marked authority or institutional action in 11 reports (30.6%) and conclusion language in 0 (0.0%). These are article-level signals: repeated coverage can refer to the same underlying event, and the markers do not prove official resolution.

Open New Delhi's broader civic problems analysis →
National trend and methodology
All 45 cities

Annual normalized signal

20212025
2021 · 1.15/10K (18)2022 · 2.20/10K (48)2023 · 1.89/10K (41)2024 · 2.05/10K (42)2025 · 2.33/10K (45)

Annual values use all covered cities, including cities that do not pass the page-level ranking gate.

Transparent limits

How Prism Geo built this ranking

  • Universe: 45 Indian cities with an existing Prism Geo city manifest; conservative legacy names such as Bangalore/Bengaluru are merged.
  • Window: complete calendar years 2021–2025. Partial 2026 data is excluded.
  • Signal: the exact source tag cryptocurrency_scam; topic variants are not silently combined.
  • Score: tagged reports ÷ all civic reports × 10,000; raw volume is shown alongside it.
  • Coverage, action, and conclusion figures are classifier outputs. Multiple reports can concern one event, and absence of coverage is not absence of a problem.

Source: marketai.civic_geo_agg. This dataset supports comparison of reporting patterns only; it cannot establish actual case counts, risk, prevalence, or official performance.

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