Критерии создания регламента проверки контрагентов
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Intermunicipal administration office Ministry OF Internal Affairs of the Russian Federation "Novocherkassk city"
OGRN: 1116183003397
TIN: 6150068224
Active
Profile views
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Subscribers
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Company-related news
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OKVED2
84.24
Public order and safety activities
Monitoring
Notes
Reports
Contact information
Revenue
No data
Chief
Beletsky Sergei Mikhailovich
100
Reliability Score
Chief
Beletsky Sergei Mikhailovich
13
years
Established
November 21, 2011
City Novocherkassk
Revenue
No data
184
Connections
+0
last week
Employees
No data
Stats Over Time
| Participation | Total number of cases | For the last year |
|---|---|---|
|
✖
Plaintiff
|
17 cases (▒▒▒▒▒ ₽) | 4 cases (▒▒▒▒▒ ₽) |
|
✖
Defendant
|
66 cases (▒▒▒▒▒ ₽) | 1 case (▒▒▒▒▒ ₽) |
|
✖
Third party
|
3 cases (▒▒▒▒▒ ₽) | 0 cases (▒▒▒▒▒ ₽) |
|
✖
Other party
|
5 cases (▒▒▒▒▒ ₽) | 0 cases (▒▒▒▒▒ ₽) |
Positive outcome — ▒▒%
▒▒▒▒▒₽
- 12 cases (▒▒▒▒▒ ₽) won
- 1 case (▒▒▒▒▒ ₽) partially won
- 3 cases (▒▒▒▒▒ ₽) not lost
Negative outcome — ▒▒%
▒▒▒▒▒₽
- 48 cases (▒▒▒▒▒ ₽) lost
- 5 cases (▒▒▒▒▒ ₽) partially lost
- 3 cases (▒▒▒▒▒ ₽) not won
Type of dispute
%
Administrative
%
Civil
%
Bankruptcy-related
%
Other
Current cases
As defendant (1)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
Completed cases
As plaintiff (17)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
As defendant (65)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
As third party (3)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
As other party (5)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
Data sources
Information about company arbitration cases is collected from public sources.
Accurate binding to a company can be created only if the information source contains its TIN and OGRN values. If identification details are not specified, the binding is created by using linguistic algorithms. Although these algorithms are being constantly improved, some information may be absent.
If you have noticed an error or lack of information, please let us know about it. Let's improve Seldon.Basis together!
Data sources
Information about company arbitration cases is collected from public sources.
Accurate binding to a company can be created only if the information source contains its TIN and OGRN values. If identification details are not specified, the binding is created by using linguistic algorithms. Although these algorithms are being constantly improved, some information may be absent.
If you have noticed an error or lack of information, please let us know about it. Let's improve Seldon.Basis together!
