Регламент проверки контрагента в компании
Рассказываем, по каким причинам важно разработать внутренний документ проверки контрагента.
Details
City administration of the Izhevsk city
Udmurt Republic
OGRN: 1031800554400
TIN: 1826001137
Active. Last modified on: April 4, 2019
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Company-related news
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+5 last week
OKVED2 84.11.3
Activities of local government bodies for general questions management
Monitoring Notes Reports Contact information
22
Reliability Score
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Head of municipality
Chistyakov Dmitry Aleksandrovich
22
years
Established
June 21, 2002
City Izhevsk
Revenue
No data
8 511
Connections
+4 last week
Employees
No data

Litigation

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Stats Over Time

Participation Total number of cases For the last year
Plaintiff
3088 cases (▒▒▒▒▒ ₽) 57 cases (▒▒▒▒▒ ₽)
Defendant
2555 cases (▒▒▒▒▒ ₽) 136 cases (▒▒▒▒▒ ₽)
Third party
680 cases (▒▒▒▒▒ ₽) 27 cases (▒▒▒▒▒ ₽)
Other party
162 cases (▒▒▒▒▒ ₽) 2 cases (▒▒▒▒▒ ₽)

Positive outcome — ▒▒%

▒▒▒▒▒
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  • 1193 cases (▒▒▒▒▒ ₽) won
  • 124 cases (▒▒▒▒▒ ₽) partially won
  • 416 cases (▒▒▒▒▒ ₽) not lost

Negative outcome — ▒▒%

▒▒▒▒▒
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  • 1072 cases (▒▒▒▒▒ ₽) lost
  • 246 cases (▒▒▒▒▒ ₽) partially lost
  • 611 cases (▒▒▒▒▒ ₽) not won

Under consideration — ▒%

▒▒▒▒▒

Undefined — ▒▒%

▒▒▒▒▒
  • 1115 cases (▒▒▒▒▒ ₽) - plaintiff
  • 708 cases (▒▒▒▒▒ ₽) - defendant

Type of dispute

%
Administrative
%
Civil
%
Bankruptcy-related
%
Other
×
Claim amount
×
Type of dispute
×
Outcome of case
×

Current cases

As plaintiff (46)
Claims amount: ▒▒▒▒▒ ₽
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As defendant (112)
Claims amount: ▒▒▒▒▒ ₽
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As third party (26)
Claims amount: ▒▒▒▒▒ ₽
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As other party (3)
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Completed cases

As plaintiff (3042)
Claims amount: ▒▒▒▒▒ ₽
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As defendant (2443)
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As third party (654)
Claims amount: ▒▒▒▒▒ ₽
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Plaintiff
Defendant
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As other party (159)
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Defendant
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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!

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