HSBC Electronic Data Processing Interview Questions, Process, and Tips

You will have to complete 3 assessment to clear the round

Q1. You will have to go to the location for interview
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Psychometric type questions exam

Q1. About process of previous organisation work and asked questions from JD
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Q2. Pep related question
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Q3. Sanction related question
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Q4. NRI account documents and corporate account requirement
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Q1. Salary discussion
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Q1. Basic and good questions not confusing employee
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Q2. Operation rounds was good not tough
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Q1. Basic questions and good listening skills for Managers
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Q2. Basic interview as per my background
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Q3. About my work experience
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Good questions on aptitude and statistics were asked

Group discussion were held

Q1. Difference between pop and remove in python
Ans. 
pop() removes and returns the last element of a list, while remove() removes the first occurrence of a specified value.
• pop() modifies the original list, while remove() only removes the specified value

• pop() requires an index as an argument, while remove() requires the value to be removed

• pop() returns the removed element, while remove() does not return anything
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Q2. Difference between shallow copy and deep copy
Ans. 
Shallow copy only copies the references of objects, while deep copy creates new copies of objects.
• Shallow copy creates a new object but does not create copies of nested objects.

• Deep copy creates new copies of all nested objects.

• Shallow copy is faster and more memory efficient, but changes to nested objects affect both copies.

• Deep copy is slower and uses more memory, but changes to nested objects do not affect the origi
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Q1. Explain linear regression, cost function, Ridge and Lasso regression
Ans. 
Linear regression is a statistical technique to model the relationship between a dependent variable and one or more independent variables.
• Linear regression is used to predict a continuous outcome variable based on one or more predictor variables.

• The cost function measures the difference between the predicted values and the actual values in linear regression.

• Ridge regression is a regularization technique that adds a pen...read more
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Q2. Explain missing value treatment
Ans. 
Missing value treatment refers to the process of handling and managing missing values in a dataset.
• Missing values can occur when data is not collected or recorded for certain observations or variables.

• Common methods for missing value treatment include deletion, imputation, and prediction.

• Deletion involves removing observations or variables with missing values, but this can lead to loss of information.

• Imputation replace...read more
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Q3. Difference between mean, median and mode
Ans. 
Mean is the average of a set of numbers, median is the middle value, and mode is the most frequently occurring value.
• Mean is calculated by summing all the values and dividing by the number of values.

• Median is the middle value when the numbers are arranged in ascending or descending order.

• Mode is the value that appears most frequently in the set of numbers.

• Mean is affected by outliers, while median and mode are not.

• For ...read more
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Questions around Anti Money Laundering

Q1. Culture fit round to see if my goals are aligned to company's goal
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Q2. Where do you see yourself in 5 years?
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