Регламент проверки контрагента в компании
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FGBOU VO "KNITU"
OGRN: 1021602854965
TIN: 1655018804
Active
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Higher education
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Contact information
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Chancellor
Kazakov Yury Mikhailovich
42
Reliability Score
Chancellor
Kazakov Yury Mikhailovich
27
years
Established
February 2, 1998
City Kazan
Revenue
No data
3 226
Connections
+6
last week
Employees
No data
Stats Over Time
| Participation | Total number of cases | For the last year |
|---|---|---|
|
✖
Plaintiff
|
106 cases (▒▒▒▒▒ ₽) | 10 cases (▒▒▒▒▒ ₽) |
|
✖
Defendant
|
144 cases (▒▒▒▒▒ ₽) | 3 cases (▒▒▒▒▒ ₽) |
|
✖
Third party
|
38 cases (▒▒▒▒▒ ₽) | 2 cases (▒▒▒▒▒ ₽) |
|
✖
Other party
|
10 cases (▒▒▒▒▒ ₽) | 0 cases (▒▒▒▒▒ ₽) |
Positive outcome — ▒▒%
▒▒▒▒▒₽
- 20 cases (▒▒▒▒▒ ₽) won
- 15 cases (▒▒▒▒▒ ₽) partially won
- 10 cases (▒▒▒▒▒ ₽) not lost
Negative outcome — ▒▒%
▒▒▒▒▒₽
- 15 cases (▒▒▒▒▒ ₽) lost
- 17 cases (▒▒▒▒▒ ₽) partially lost
- 4 cases (▒▒▒▒▒ ₽) not won
Type of dispute
%
Administrative
%
Civil
%
Bankruptcy-related
%
Other
Current cases
As plaintiff (1)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
As defendant (1)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
As third party (2)
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 (105)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
As defendant (143)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount
As third party (36)
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!
