8 Genworth SQL Interview Questions (Updated 2024)

At Genworth Financial, SQL is used for analyzing customer data, including credit scores and transaction history, to predict financial risks, as well as managing databases to ensure secure and organized financial information, like encrypting sensitive customer data. Because of this, Genworth often asks SQL questions in interviews for Data Science and Data Engineering positions.

Thus, to help you study for the Genworth SQL interview, we've collected 8 Genworth Financial SQL interview questions in this article.

8 Genworth Financial SQL Interview Questions

SQL Question 1: Identify the VIP Customers for Genworth

Given a transaction table for insurance company 'Genworth', write a SQL query to identify the 'VIP' customers. The criteria for being a VIP customer is determined by the number of policies they have and the total premium they have paid. A VIP customer is one who holds more than 5 policies and has paid a total premium of over $5000.

Sample Table

Answer:

This SQL query works by grouping the transaction records by . The function is used to find the unique number of policies held by each customer. The function calculates the total premium paid by each customer. The clause then filters out the customers who hold more than 5 unique policies and who have paid a total premium of over $5000. These are categorized as the VIP customers based on the given criteria.

To solve a related super-user data analysis question on DataLemur's free interactive SQL code editor, try this recently asked Microsoft SQL interview question:

SQL Question 2: Department vs. Company Salary

Imagine you had a table of Genworth employee salaries, along with which department they were in. Write a query to compare the average salary of employees in each department to the company's average salary for March 2024. Return the comparison result as 'higher', 'lower', or 'same' for each department. Display the department ID, payment month (in MM-YYYY format), and the comparison.

Code your solution to this question and run your code right in DataLemur's online SQL environment:

The solution is LONG – 30+ lines of SQL. You can find a step-by-step solution here: Department Salaries.

SQL Question 3: What does it mean to perform a self-join?

A self-join is a operation in which a single table is joined to itself. To perform a self-join, you must specify the table name twice in the clause, giving each instance a different alias. You can then join the two instances of the table using a clause, and specify the relationship between the rows in a clause.

Think of using a self-joins whenever your data analysis involves analyzie pairs of the same things, like comparing the salaries of employees within the same department, or identifying pairs of products that are frequently purchased together (which you can do in this real SQL question from a Walmart interview).

For another self-join example, suppose you were conducting an HR analytics project and needed to examine how frequently employees within the same department at Genworth interact with one another, you could use a self-join query like the following to retrieve all pairs of Genworth employees who work in the same department:

This query returns all pairs of Genworth employees who work in the same department, and excludes pairs where the employee's id is the same (since this would represent the same Genworth employee being paired with themselves).

SQL Question 4: Policy Analysis with Window Functions

You are an analyst at Genworth and have been asked to analyze the "Annual Revenue" and "Number of Policies" for various policy types issued over several years.

Here's a hypothetical dataset:

Example Input:

The task is to write a SQL query to compute the total revenue and the total number of policies issued for each policy type, for each year. Include cumulative revenues and policy counts over the years in your result.

Example Output:

Answer:

This query first groups the policies by year and type, and for each grouping: calculates the revenue (by summing ) and calculates the number of policies (by counting ). It then uses window functions to calculate the cumulative sums of these values over the years (partitioned by ), providing a cumulative overview of Genworth's policy sales and revenues by policy type and year.

For more window function practice, solve this Uber SQL Interview Question within DataLemur's online SQL coding environment:

SQL Question 5: Why is database normalization a good idea?

Database normalization has several benefits:

• Reduces Redundancy: Normalization can minimize redundancy by breaking down a larger, general table into smaller, more granular tables. This often reduces the amount of data that needs to be accessed for particular queries, since some duplicated columns can be removed.

• Improves Data Integrity: Normalization can help to ensure the integrity of the data by minimizing the risk of data inconsistencies and errors. By establishing clear relationships between the tables via primary and foreign keys, and enforcing these constraints, you can have more reliable records and relationships stored in your DB.

• Improves Performance: Normalization can improve the performance of the database by reducing the amount of data that needs to be stored and accessed in a single table. This results in faster query times and better overall performance.

SQL Question 6: Calculate the Average Policy Duration

Genworth, being an insurance company, is interested in understanding the average duration of their policies in each year. You have been asked to find the average duration of policies initiated every year. Policies are considered in the year they were initiated.

Example Input:

Example Output:

Answer:

In this SQL query, we are first extracting the year from the initiation date. Then we compute the difference between the expiry date and initiation date. To convert the difference into the number of days, we extract the day part from this interval. After that, we take the average of these durations. Please note that for simplicity's sake, we're assuming policy dates are always exactly a year apart, but in a real-world scenario the dates might be more variable.

To practice a very similar question try this interactive Facebook Average Post Hiatus (Part 1) Question which is similar for focusing on period calculation or this Wayfair Y-on-Y Growth Rate Question which is similar for working with time-stamped data.

SQL Question 7: What are database views, and when would you use them?

A database view is a virtual table that is created based on the results of a SELECT statement, and provides you a customized, read-only version of your data that you can query just like a regular table.

Views in SQL can help you enforce data security requirements by hiding sensitive data from certain users, and can improve performance for some queries by pre-computing the results for an intermediate step and storing them in a view (which can be faster than executing the intermediate query each time). However, their read-only nature means that on any underlying update, the view has to be re-computed.

SQL Question 8: Filter Clients Based on Email Domain

As a data analyst at Genworth, you have been tasked to identify the set of clients who have registered with the company through a specific email domain for targeting marketing campaigns. For this study, you are interested in emails that end with '@genworth.com'. The customer data is stored in a database named .

Example Input:

Your TASK: Write a SQL query that will return the client ids, client names and email addresses of clients registered with a 'genworth.com' email.

Answer:

This query works by filtering out all the records from the table where the field ends with '@genworth.com'. The '%' sign is a wildcard character that matches any sequence of characters. The result set should only contain clients who used a 'genworth.com' email to register with Genworth.

Preparing For The Genworth SQL Interview

The key to acing a Genworth SQL interview is to practice, practice, and then practice some more! Beyond just solving the above Genworth SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Google, Facebook, Microsoft and Amazon.

Each DataLemur SQL question has multiple hints, detailed solutions and most importantly, there's an interactive SQL code editor so you can right in the browser run your SQL query answer and have it executed.

To prep for the Genworth SQL interview it is also helpful to practice SQL questions from other insurance companies like:

• Gallagher US SQL questions
• FM Global SQL questions
• First American Financial SQL questions
• Old Republic SQL questions

Stay ahead of the curve with Genworth's latest news and insights on the mortgage insurance and financial services industries!

However, if your SQL skills are weak, don't worry about jumping right into solving questions – go learn SQL with this free SQL tutorial.

This tutorial covers topics including aggregate functions and handling NULLs in SQL – both of these come up often in Genworth SQL assessments.

Genworth Financial Data Science Interview Tips

What Do Genworth Data Science Interviews Cover?

Besides SQL interview questions, the other types of problems to prepare for the Genworth Data Science Interview are:

• Statistics and Probability Questions
• Python or R Programming Questions
• Analytics and Product-Metrics Questions
• Machine Learning Questions
• Behavioral & Resume-Based Questions

How To Prepare for Genworth Data Science Interviews?

To prepare for the Genworth Data Science interview make sure you have a deep understanding of the company's values and company principles – this will be important for acing the behavioral interview. For the technical Data Science interviews, prepare by reading Ace the Data Science Interview. The book's got:

• 201 Interview Questions from companies like Microsoft, Google & Amazon
• A Refresher on Python, SQL & ML
• Great Reviews (1000+ 5-star reviews on Amazon)