Регламент проверки контрагента в компании
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Administration of the administrative district Leninsk of Omsk city
OGRN: 1035509001395
TIN: 5505012857
Active
Profile views
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Subscribers
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Company-related news
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OKVED2
84.11.3
Activities of local government bodies for general questions management
Monitoring
Notes
Reports
Contact information
Revenue
No data
Head of administration
Khrolenko Nikolay Mikhaylovich
100
Reliability Score
Head of administration
Khrolenko Nikolay Mikhaylovich
33
years
Established
December 25, 1991
City Omsk
Revenue
No data
528
Connections
+0
last week
Employees
No data
Stats Over Time
| Participation | Total number of cases | For the last year |
|---|---|---|
|
✖
Plaintiff
|
162 cases (▒▒▒▒▒ ₽) | 43 cases (▒▒▒▒▒ ₽) |
|
✖
Defendant
|
131 cases (▒▒▒▒▒ ₽) | 0 cases (▒▒▒▒▒ ₽) |
|
✖
Third party
|
38 cases (▒▒▒▒▒ ₽) | 8 cases (▒▒▒▒▒ ₽) |
|
✖
Other party
|
10 cases (▒▒▒▒▒ ₽) | 2 cases (▒▒▒▒▒ ₽) |
Positive outcome — ▒▒%
▒▒▒▒▒₽
- 22 cases (▒▒▒▒▒ ₽) won
- 4 cases (▒▒▒▒▒ ₽) partially won
- 46 cases (▒▒▒▒▒ ₽) not lost
Negative outcome — ▒▒%
▒▒▒▒▒₽
- 23 cases (▒▒▒▒▒ ₽) lost
- 2 cases (▒▒▒▒▒ ₽) partially lost
- 17 cases (▒▒▒▒▒ ₽) not won
Type of dispute
%
Administrative
%
Civil
%
Bankruptcy-related
%
Other
Current cases
As plaintiff (35)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
As third party (5)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
As other party (1)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
Completed cases
As plaintiff (127)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
As defendant (131)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
As third party (33)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
As other party (9)
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!
