Cognext Analytics
e-con Systems Interview Questions and Answers
Q1. What are mutable and immutable data types in Python?
Mutable data types can be modified after creation, while immutable data types cannot be changed.
Mutable data types: lists, dictionaries, sets
Immutable data types: strings, tuples, integers
Example: list is mutable - myList = [1, 2, 3]; tuple is immutable - myTuple = (1, 2, 3)
Q2. How do you rate a customer on the basis of credibility
To rate a customer's credibility, we consider their payment history, credit score, references, and industry reputation.
Evaluate payment history and credit score
Check references and past work experience
Assess industry reputation and online presence
Consider any legal or financial issues
Use a scoring system or rating scale to quantify credibility
Q3. What do you understand by clean code principles?
Clean code principles refer to writing code that is easy to read, understand, and maintain.
Writing clear and descriptive variable names
Breaking down complex functions into smaller, more manageable pieces
Avoiding redundant or unnecessary code
Following consistent formatting and indentation
Writing comments to explain the purpose of the code
Q4. How do you know the customer is going to default?
Customer default can be predicted based on various factors.
Analyzing credit history and payment patterns
Assessing financial stability and debt-to-income ratio
Monitoring changes in employment status or income
Identifying external factors such as economic downturns or industry changes
Using predictive modeling and machine learning algorithms
Working closely with collections and risk management teams
Regularly reviewing and updating risk assessment strategies
Q5. What is Significant increase in credit risk? Does SICR posses when an account moves from Stage 2 to Stage 3?
Q6. What is PD, Cumilative PD, Marginal pd
PD stands for Probability of Default, Cumulative PD is the sum of PD over time, Marginal PD is the change in PD for a small change in time.
PD (Probability of Default) is the likelihood that a borrower will default on a loan within a given time period.
Cumulative PD is the sum of PD over time, representing the total probability of default by a certain point in time.
Marginal PD is the change in PD for a small change in time, indicating how the probability of default is changing ...read more
Q7. What is PD ?
PD stands for Probability of Default, a measure used in credit risk analysis to estimate the likelihood of a borrower defaulting on a loan.
PD is a key metric used in credit risk assessment to determine the likelihood of a borrower defaulting on a loan.
It is expressed as a percentage and represents the probability of a borrower failing to meet their financial obligations.
PD is calculated based on various factors such as credit history, financial stability, and market condition...read more
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