Revealed: Credit Suisse leak unmasks criminals, fraudsters and corrupt politicians
- Bias Rating
-26% Somewhat Liberal
- Reliability
N/AN/A
- Policy Leaning
-26% Somewhat Liberal
- Politician Portrayal
37% Positive
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The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.
Sentiments
N/A
- Liberal
- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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-100%
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100%
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Contributing sentiments towards policy:
48% : "However, it is likely that a significant number of these accounts were opened with the sole purpose of hiding their holder's wealth from fiscal institutions and/or avoiding the payment of taxes on capital gains."46% : That changed in 2007, when the UBS banker Bradley Birkenfeld voluntarily approached US authorities with information about how the bank was helping thousands of wealthy Americans evade tax with secret accounts.
40% : That includes the $2.6bn the Swiss bank agreed to pay US authorities after pleading guilty to conspiring to aid tax evasion in 2014; the $536m it was fined by the US five years before for deliberately circumventing US sanctions against countries including Iran and Sudan in 2009, and other payouts to Germany and Italy over tax evasion allegations.
38% : One Algerian client was Khaled Nezzar, who served as minister of defence until 1993 and participated in a coup that precipitated a brutal civil war in which the military junta he was part of was accused of disappearances, mass detentions, torture and execution of detainees.
33% : Clients would face intensified scrutiny when flagged as a politically exposed person from a high-risk country, or a person involved in a high-risk activity such as gambling, weapons trading, financial services or mining, the report said.
*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.