9 Country Financial SQL Interview Questions (Updated 2024)
Country Financial employees use SQL for analyzing and managing insurance and financial data, such as tracking policyholder behavior and identifying areas of risk, as well as optimizing underwriting processes through structured queries, including automating policy approvals and streamlining claims processing. Because of this, Country Financial often asks SQL query questions during interviews for Data Science and Data Engineering positions.
Thus, to help you prep, we've curated 9 Country Financial SQL interview questions – can you answer each one?
9 Country Financial SQL Interview Questions
SQL Interview Question 1: Calculate Running total of policy premiums
At Country financial, you would have data related premiums of various policies that each customer enrolled. A Premium in insurance is the amount of money one must pay for an insurance policy. Run a SQL query to calculate the running total of paid by each for each year in ascending order of . The table is with attributes , , , . We would be using the SQL Window function to solve this question.
Sample Input:
| policy_id | customer_id | premium | date |
|---|---|---|---|
| 501 | 105 | 2000 | 2020-01-01 |
| 521 | 105 | 4000 | 2020-05-05 |
| 532 | 105 | 2500 | 2020-10-10 |
| 783 | 205 | 3000 | 2020-04-01 |
| 802 | 205 | 3500 | 2020-04-14 |
| 813 | 205 | 4000 | 2020-10-01 |
Sample Output:
| customer_id | date | running_total_premium |
|---|---|---|
| 105 | 2020-01-01 | 2000 |
| 105 | 2020-05-05 | 6000 |
| 105 | 2020-10-10 | 8500 |
| 205 | 2020-04-01 | 3000 |
| 205 | 2020-04-14 | 6500 |
| 205 | 2020-10-01 | 10500 |
Answer:
The above query works as follows:
- separates the data into partitions based on the 'customer_id'.
- orders the rows in each partition.
- calculates the running total of 'premium' within each partition.
For more window function practice, try this Uber SQL problem within DataLemur's online SQL code editor:
SQL Question 2: Top Department Salaries
Assume you had a table of Country Financial employee salary data. Write a SQL query to find the top 3 highest earning employees within each department.
Country Financial Example Input:
| employee_id | name | salary | department_id |
|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 |
| 2 | Daniel Rodriguez | 2230 | 1 |
| 3 | Olivia Smith | 2000 | 1 |
| 4 | Noah Johnson | 6800 | 2 |
| 5 | Sophia Martinez | 1750 | 1 |
| 8 | William Davis | 6800 | 2 |
| 10 | James Anderson | 4000 | 1 |
Example Input:
| department_id | department_name |
|---|---|
| 1 | Data Analytics |
| 2 | Data Science |
Example Output:
| department_name | name | salary |
|---|---|---|
| Data Analytics | James Anderson | 4000 |
| Data Analytics | Emma Thompson | 3800 |
| Data Analytics | Daniel Rodriguez | 2230 |
| Data Science | Noah Johnson | 6800 |
| Data Science | William Davis | 6800 |
Check your SQL query for this question directly within the browser on DataLemur:
Answer:
We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.
If the code above is hard to understand, you can find a step-by-step solution here: Top 3 Department Salaries.
SQL Question 3: What does the SQL command do?
is used to combine the results of multiple statements into a single result set.
Suppose you were doing an HR Analytics project for Country Financial, and needed to analyze both Country Financial's contractors and employees. You could use in the following way:
This statement would return a combined result set of Country Financial contractors and employees who were hired after the start of the year 2023.
SQL Question 4: Filter Customer Records based on Policy and State
Given the following customer records that contains , , and , find all customers who live in either 'IL' or 'GA' states and have either 'Auto' or 'Home' policy. Also, their premium should be above 1500.
Example Input:
| customer_id | state | policy_id | premium |
|---|---|---|---|
| 5678 | IL | Auto | 2000 |
| 9102 | GA | Home | 1800 |
| 1121 | WI | Auto | 1600 |
| 3465 | FL | Life | 1200 |
| 7293 | IL | Home | 1950 |
| 8746 | GA | Business | 2000 |
| 6381 | IL | Auto | 1000 |
Example Output:
| customer_id | state | policy_id | premium |
|---|---|---|---|
| 5678 | IL | Auto | 2000 |
| 9102 | GA | Home | 1800 |
| 7293 | IL | Home | 1950 |
Answer:
In this query, we are using the keyword in our clause to filter customers by state ('IL' or 'GA') and policy_id ('Auto' or 'Home'). We further enhance our filter by stating that the premium should be more than 1500. This query will return only the records that meet all the specified conditions.
SQL Question 5: What's the difference between a left and right join?
In SQL, both a left and right join is used to combine rows from different tables based on a shared key or set of keys, resulting in a single merged table of data. However, here's the difference:
LEFT (OUTER) JOIN: Retrieves all the records/rows from the left and the matched records/rows from the right table.
RIGHT (OUTER) JOIN: Retrieves all the records/rows from the right and the matched records/rows from the left table.
SQL Question 6: Average Insurance Claims Per Customer
In this question, you are given a database for a financial institution that offers various types of insurance plans such as health, home, auto, etc. You are asked to calculate the average number of insurance claims per customer.
Example Input:
| claim_id | policy_id | customer_id | claim_date | claim_amount |
|---|---|---|---|---|
| 101 | 201 | 5001 | 01/05/2023 | 5000 |
| 102 | 202 | 5002 | 01/10/2023 | 500 |
| 103 | 203 | 5003 | 01/15/2023 | 1000 |
| 104 | 204 | 5001 | 01/20/2023 | 2000 |
| 105 | 205 | 5002 | 01/25/2023 | 1000 |
| 106 | 205 | 5001 | 01/30/2023 | 3000 |
Example Input:
| customer_id | first_name | last_name | signup_date |
|---|---|---|---|
| 5001 | John | Doe | 01/01/2023 |
| 5002 | Jane | Smith | 01/02/2023 |
| 5003 | Dave | Johnson | 01/03/2023 |
Answer:
This query starts by creating a subquery that counts the number of claims per customer. Then it calculates the average of these counts. This gives us the average number of insurance claims per customer.
To practice a very similar question try this interactive Stripe Repeated Payments Question which is similar for requiring calculations on a user basis or this Amazon Average Review Ratings Question which is similar for requiring average calculations on a per product (similar to per customer) basis.
SQL Question 7: What do stored procedures do?
Stored procedures are like functions in Python – they can accept input params and return values, and are used to encapsulate complex logic.
For example, if you worked as a Data Analyst in support of the Marketing Analytics team at Country Financial, a common task might be to find the conversion rate for your ads given a specific time-frame. Instead of having to write this query over-and-over again, you could write a stored procedure like the following:
To call this stored procedure, you'd execute the following query:
SQL Question 8: Analyzing Click-Through-Rate for Insurance Purchases
Given a table named , we are tasked to find the click-through-rate (CTR), defined as the number of insurance purchases per advertisement click, for each type of advertisement on a monthly basis.
Example Input:
| ad_id | ad_type | click_date | user_id |
|---|---|---|---|
| 1001 | Social Media | 06/01/2022 00:00:00 | 123 |
| 1002 | 06/02/2022 00:00:00 | 265 | |
| 1003 | Banner Ad | 06/03/2022 00:00:00 | 362 |
| 1004 | Social Media | 07/04/2022 00:00:00 | 192 |
| 1005 | Banner Ad | 07/05/2022 00:00:00 | 981 |
Example Input:
| purchase_id | purchase_date | user_id |
|---|---|---|
| 5001 | 06/01/2022 00:00:00 | 123 |
| 5002 | 06/03/2022 00:00:00 | 362 |
| 5003 | 07/04/2022 00:00:00 | 192 |
| 5004 | 07/06/2022 00:00:00 | 981 |
Answer:
This query first prepares two sub-queries: and . calculates the number of clicks for each ad type on a monthly basis, and does the same for insurance purchases. Then, the main query left joins these two sub-queries on and , computing the CTR as the ratio of to . If there are no clicks for a certain ad type in a certain month ( = 0), the CTR is defined to be 0. Finally, the result is sorted in ascending order by month and ad type.
To practice another question about calculating rates, solve this SQL interview question from TikTok on DataLemur's online SQL code editor:
SQL Question 9: Filter Customer Records based on insurance policy type
Given a table , you are asked to write an SQL query that will return all records of customers whose starts with 'Auto'. can have values like 'Auto Liability', 'Auto Comprehensive', 'Home Owner', 'Life Term', etc.
Assume we have the following table:
Example Input:
| client_id | first_name | last_name | insurance_type | |
|---|---|---|---|---|
| 8724 | John | Doe | johndoe@example.com | Auto Liability |
| 2543 | Jane | Smith | janesmith@example.com | Auto Comprehensive |
| 8432 | Emma | Johnson | emmajohnson@example.com | Home Owner |
| 6423 | Michael | Brown | michaelbrown@example.com | Life Term |
| 5124 | Emily | Taylor | emilytaylor@example.com | Auto Collision |
Expected Output:
| client_id | first_name | last_name | insurance_type | |
|---|---|---|---|---|
| 8724 | John | Doe | johndoe@example.com | Auto Liability |
| 2543 | Jane | Smith | janesmith@example.com | Auto Comprehensive |
| 5124 | Emily | Taylor | emilytaylor@example.com | Auto Collision |
Answer:
Below is the PostgreSQL query which would solve the problem:
This query uses the keyword to filter the records where the starts with 'Auto'. The percent sign () is a wildcard character that matches any sequence of characters. Since it's after 'Auto', it means we're looking for any strings that start with 'Auto'.
Preparing For The Country Financial SQL Interview
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Country Financial SQL interview is to solve as many practice SQL interview questions as you can! Besides solving the earlier Country Financial SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Google, Microsoft and Silicon Valley startups.
Each DataLemur SQL question has hints to guide you, detailed solutions and crucially, there's an online SQL coding environment so you can easily right in the browser your SQL query and have it checked.
To prep for the Country Financial SQL interview you can also be wise to practice interview questions from other insurance companies like:
- Country Financial SQL questions
- Brown & Brown SQL questions
- Voya SQL questions
- American National SQL questions
Discover how Country Financial is harnessing the power of technology to improve lives!
In case your SQL skills are weak, don't worry about going right into solving questions – refresh your SQL knowledge with this DataLemur SQL Tutorial.
This tutorial covers topics including cleaning text data and filtering data with WHERE – both of these come up frequently during SQL job interviews at Country Financial.
Country Financial Data Science Interview Tips
What Do Country Financial Data Science Interviews Cover?
Beyond writing SQL queries, the other question categories covered in the Country Financial Data Science Interview are:
- Probability & Stats Questions
- Coding Questions in Python or R
- Business Sense and Product-Sense Questions
- ML Interview Questions
- Behavioral Interview Questions centered on Country Financial culture and values
How To Prepare for Country Financial Data Science Interviews?
To prepare for Country Financial Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from FAANG (FB, Apple, Amazon, Netflix, Google)
- a refresher on Python, SQL & ML
- over 1000+ 5-star reviews on Amazon
Also focus on the behavioral interview – prep for that using this behavioral interview question bank.