EU financial services markets fragmentation works as tariff, Albuquerque says
- Bias Rating
- Reliability
40% ReliableAverage
- Policy Leaning
14% Somewhat Right
- Politician Portrayal
N/A
Continue For Free
Create your free account to see the in-depth bias analytics and more.
By creating an account, you agree to our Terms and Privacy Policy, and subscribe to email updates.
Bias Score Analysis
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
-11% Negative
- Liberal
- Conservative
Sentence | Sentiment | Bias |
---|---|---|
Unlock this feature by upgrading to the Pro plan. |
Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
Extremely
Liberal
Very
Liberal
Moderately
Liberal
Somewhat Liberal
Center
Somewhat Conservative
Moderately
Conservative
Very
Conservative
Extremely
Conservative
-100%
Liberal
100%
Conservative

Contributing sentiments towards policy:
53% : In the past months, however, EU leaders have pledged to intensify efforts to integrate the bloc's financial markets as one of ways of boosting Europe's competitiveness.51% : Addressing a diplomatic event in Lisbon, Albuquerque said the EU needed to complete its banking union and deepen the capital market integration.
46% : LISBON, Jan 7 (Reuters) - European Union's financial industry faces burdens equivalent to a 110% tariff because of the fragmentation of the bloc's markets for financial services, EU Commissioner for Financial Services Maria Luis Albuquerque said on Tuesday.
44% : A Capital Markets Union would unify national rules on bankruptcies, prospectuses, listing requirements and taxation to make it easier to raise funds in Europe, making it a viable alternative to deep U.S. capital markets.
*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.