11 Securian Financial SQL Interview Questions (Updated 2024)
Securian Financial employees often use SQL for analyzing insurance-related data patterns, such as identifying trends in policyholder behavior and claims frequency, as well as transforming raw data into insightful financial reports, like quarterly earnings statements. Because of this, Securian Financial often tests SQL problems in interviews for Data Science and Data Engineering positions.
So, to help you prep for the Securian Financial SQL interview, we've curated 11 Securian Financial Group SQL interview questions in this article.
11 Securian Financial Group SQL Interview Questions
SQL Question 1: Identify High Value Customers at Securian Financial
Securian Financial is interested to know who their high value customers are - these can be defined as customers who have initiated multiple insurance policies and have a high premium amount. Please write a SQL query that identifies these customers. The database contains two tables – and .
They are defined as follows:
Example Input:
| customer_id | first_name | last_name |
|---|---|---|
| 101 | Jim | Hawkins |
| 102 | Sarah | Jones |
| 103 | Michael | Smith |
| 104 | Emily | Ross |
Example Input:
| policy_id | customer_id | coverage_amount | premium |
|---|---|---|---|
| 1001 | 101 | 50000 | 1200 |
| 1002 | 101 | 25000 | 700 |
| 1003 | 102 | 100000 | 2500 |
| 1004 | 103 | 100000 | 2500 |
| 1005 | 103 | 50000 | 1200 |
| 1006 | 104 | 75000 | 1800 |
We define a high value customer as one with more than one policy and overall premium amount higher than $2000.
Your SQL query should return a list of their customer ids, names, number of policies, and total premium.
Answer:
This query works by joining the and tables on . It then groups the resulting table by customer and calculates the number of policies and total premium for each customer. The clause filters the results to only include customers with more than one policy and a total premium greater than $2000.
To practice a related super-user data analysis question on DataLemur's free interactive coding environment, try this Microsoft Teams Power User SQL Interview Question:
SQL Question 2: Employees Earning More Than Managers
Imagine you had a table of Securian Financial employee salaries. Write a SQL query to find all employees who earn more than their direct manager.
Securian Financial Example Input:
| employee_id | name | salary | department_id | manager_id |
|---|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 | |
| 2 | Daniel Rodriguez | 2230 | 1 | 10 |
| 3 | Olivia Smith | 8000 | 1 | 8 |
| 4 | Noah Johnson | 6800 | 2 | 8 |
| 5 | Sophia Martinez | 1750 | 1 | 10 |
| 8 | William Davis | 7000 | 2 | NULL |
| 10 | James Anderson | 4000 | 1 | NULL |
Example Output:
| employee_id | employee_name |
|---|---|
| 3 | Olivia Smith |
This is the output because Olivia Smith earns $8,000, surpassing her manager, William Davis who earns 7,800.
You can solve this problem interactively on DataLemur:
Answer:
First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.
If the solution above is confusing, you can find a detailed solution with hints here: Employees Earning More Than Their Boss.
SQL Question 3: What distinguishes an inner join from a full outer join?
An inner join returns only the rows that match the join condition between the two tables, whereas a full outer join returns all rows from both tables, including any unmatched rows.
Example:
Example:
SQL Question 4: Calculating the Average Premium and Claims for Each Insurance Policy
Suppose you work for Securian Financial as a data analyst. You are given a task to analyze the company's insurance policies. Specifically, you are asked to calculate the average monthly premium and the total claims per policy for the last year. The company has two main types of insurance policies: "Life Insurance" and "Auto Insurance".
Use the tables , , and . The table contains information about each policy such as its type and the id of the insured client. The table contains the monthly premiums paid by the clients for each policy. Finally, the table contains information about the claims made by the clients.
Example Input:
| policy_id | client_id | policy_type |
|---|---|---|
| 101 | 1 | Life Insurance |
| 102 | 2 | Life Insurance |
| 103 | 3 | Auto Insurance |
| 104 | 4 | Auto Insurance |
Example Input:
| policy_id | paid_date | premium |
|---|---|---|
| 101 | 01/05/2021 | 500 |
| 101 | 02/05/2021 | 500 |
| 102 | 01/05/2021 | 600 |
| 103 | 01/05/2021 | 200 |
| 104 | 01/05/2021 | 300 |
Example Input:
| policy_id | claim_date | claim_amount |
|---|---|---|
| 101 | 01/20/2021 | 1000 |
| 103 | 01/30/2021 | 500 |
Answer:
This PostgreSQL query uses the window function to calculate the average premium and the window function to calculate the total claim amount for each insurance policy.
This query first joins the three tables on the policy_id. It then filters the data for the last year using the paid_date in the premiums table. The function calculates the average monthly premium and the function calculates the total claims for each policy using the syntax. The function is used to replace null values with 0 in the total_claims column when no claims were made for a given policy.
p.s. Window functions show up pretty frequently during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: What's the purpose of the constraint?
A is a field in a table that references the of another table. It creates a link between the two tables and ensures that the data in the field is valid.
Say for example you had sales analytics data from Securian Financial's CRM (customer-relationship management) tool.
The FOREIGN KEY constraint ensures that the data in the field of the table is valid, and prevents the insertion of rows in the table that do not have corresponding entries in the table. It also helps to enforce the relationship between the two tables and can be used to ensure that data is not deleted from the accounts table if there are still references to it in the table.
SQL Question 6: Find Top Policy Holders Based on Total Policies and Claims
As Securian Financial deals with insurance policies, let's consider a scenario where we have policy holder data and their associated claim records. Your task is to write a SQL query that filters out the policy holders who have more than 10 policies and have made at least 3 claims.
Example Input:
| holder_id | name | address | total_policies |
|---|---|---|---|
| H001 | John Doe | 123 Main St, Maple City, NY 10753 | 15 |
| H002 | Jane Smith | 456 Cedar Ave, Willow Town, NC 27614 | 8 |
| H003 | Sarah Johnson | 789 Oak Blvd, Pine Village, CA 94544 | 11 |
| H004 | Michael Brown | 1011 Elm Dr, Palm City, FL 33461 | 7 |
Example Input:
| claim_id | holder_id | claim_amount | claim_date |
|---|---|---|---|
| C001 | H001 | 1500.00 | 2021-10-07 |
| C002 | H001 | 2500.00 | 2021-12-14 |
| C003 | H003 | 1000.00 | 2022-02-20 |
| C004 | H003 | 2000.00 | 2022-03-15 |
| C005 | H003 | 1800.00 | 2022-05-30 |
Answer:
This query first performs an inner join operation using field as a common key between and tables. It groups the result by , and fields. Finally, it filters out those policy holders using a clause who fulfill the condition of having total policies more than 10 and more or equal to 3 total claims.
SQL Question 7: What does the clause do vs. the clause?
The clause is used to filter rows from the result set of a , , or statement. It allows you to specify a condition that must be met for a row to be included in the result set.
The clause is used to filter groups created by the clause. It is similar to the clause, but it is used to specify conditions on the groups created by the clause, rather than on the individual rows of the table.
Say you were working on a social media analytics project for Securian Financial.
Here is an example of a SQL query that you might write which uses both the WHERE and HAVING clauses:
This query retrieves the total impressions and average conversions for each platform in the table, the date of the campaign is in January 2023. The rows are grouped by platform and the clause filters the groups to include only those with more than 5000 impressions and an average conversion rate above 0.2.
SQL Question 8: Calculate the Average Claim Amount by Insurance Type
Assume you have a table named that tracks all claims made by Securian Financial's customers. This table includes a column, which indicates the total amount of money claimed in each individual case, a indicating the date the claim was filed, a column indicating the customer who made the claim, and an indicating the type of insurance policy for which the claim was made.
Securian Financial would like to know the average claim amount for each type of insurance policy they offer. Write a SQL query that can provide this information.
Example Input:
| claim_id | user_id | claim_date | insurance_type | claim_amount |
|---|---|---|---|---|
| 1001 | 500 | 01/02/2021 | Car Insurance | 2500.00 |
| 1002 | 497 | 08/06/2021 | Life Insurance | 8000.00 |
| 1003 | 222 | 05/05/2021 | Home Insurance | 5000.00 |
| 1004 | 500 | 03/03/2021 | Car Insurance | 2000.00 |
| 1005 | 125 | 09/12/2021 | Car Insurance | 3000.00 |
Answer:
This query groups all claims by type of insurance. It then calculates the average claim amount for each insurance type via the function. The output will display each distinct type of insurance policy alongside the average claim amount for that particular type of policy.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating averages based on a specific column or this Alibaba Compressed Mean Question which is similar for use of aggregate functions in data analysis.
SQL Question 9: Calculate the Click-Through Rate for Securian Financial Digital Ads
Securian Financial uses digital ads to attract new customers. These ads are shown on different platforms (e.g., Google, Facebook) and link to Securian's different product pages (e.g., Life Insurance, Retirement Plans). As an analyst at Securian, your task is to calculate the click-through rate of these digital ads on a daily basis. The click-through rate (CTR) is defined as the total number of clicks that your ad receives divided by the total number of impressions (views) that your ad gets.
Please use the following tables for your analysis:
Example Input:
| day | platform | product | impressions |
|---|---|---|---|
| 2021-06-07 | Life Insurance | 1500 | |
| 2021-06-07 | Retirement Plans | 2200 | |
| 2021-06-07 | Retirement Plans | 1000 | |
| 2021-06-08 | Life Insurance | 1800 | |
| 2021-06-08 | Retirement Plans | 1300 |
Example Input:
| day | platform | product | clicks |
|---|---|---|---|
| 2021-06-07 | Life Insurance | 150 | |
| 2021-06-07 | Retirement Plans | 200 | |
| 2021-06-07 | Retirement Plans | 90 | |
| 2021-06-08 | Life Insurance | 170 | |
| 2021-06-08 | Retirement Plans | 100 |
Answer:
This PostgreSQL query joins and tables using the , , and fields. Then for each day, platform, and product, it calculates the Click Through Rate (CTR) by dividing the number of clicks by the number of impressions. To avoid division by zero, we use function which replaces zero with NULL. If 0 is encountered during the division, PostgreSQL will return NULL instead of throwing an error. The resulting CTR values are sorted by , , and in ascending order.
To practice a similar problem about calculating rates, solve this TikTok SQL question on DataLemur's interactive coding environment:
SQL Question 10: Can you explain the purpose of the constraint and give an example of when you might use it?
The CHECK constraint is used to set a rule for the data in a column. If a row is inserted or updated and the data in the column does not follow the rule specified by the CHECK constraint, the operation will be unsuccessful.The CHECK constraint is often used in conjunction with other constraints, such as NOT NULL or UNIQUE.
You might consider implementing the CHECK constraint in your database if you want to ensure that certain data meets specific conditions. This can be helpful for maintaining the quality and reliability of your data.
For example, you might use a CHECK constraint to ensure that a column contains only positive numbers, or that a date is within a certain range.
SQL Question 11: Find the Average Policy Value per Client by Year
Securian Financial provides a wide variety of financial products, one of which is an insurance policy. Given a table of policyholders where each row represents a policy issued by Securian Financial, calculate the average policy value for each client by year.
Example Input:
| policy_id | client_id | issue_date | policy_value |
|---|---|---|---|
| 101 | 0547 | 01/01/2021 | 15000 |
| 102 | 0547 | 06/05/2021 | 20000 |
| 103 | 0862 | 05/10/2021 | 18000 |
| 104 | 0862 | 12/22/2021 | 22000 |
| 105 | 0862 | 07/15/2022 | 25000 |
Example Output:
| year | client_id | avg_policy_value |
|---|---|---|
| 2021 | 0547 | 17500 |
| 2021 | 0862 | 20000 |
| 2022 | 0862 | 25000 |
Answer:
Here's the PostgreSQL query to solve the problem:
This query first extracts the year from the column using the function, and then groups the data by year and client_id. The function calculates the average policy value for each of these groups. The clause is used to sort the result in ascending order by year and client_id.
Securian Financial SQL Interview Tips
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews. In addition to solving the above Securian Financial SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Meta, Google and insurance companies like Securian Financial.
Each SQL question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and most importantly, there is an online SQL coding environment so you can easily right in the browser your query and have it graded.
To prep for the Securian Financial SQL interview it is also helpful to practice SQL problems from other insurance companies like:
- American Financial Group SQL questions
- Hanover Insurance SQL questions
- Genworth SQL questions
- Gallagher US SQL questions
Explore how Securian Financial is harnessing the power of emerging tech to revolutionize the insurance sector!
In case your SQL foundations are weak, don't worry about diving straight into solving questions – go learn SQL with this SQL interview tutorial.
This tutorial covers SQL concepts such as removing NULLs and Union vs. UNION ALL – both of these pop up often during SQL job interviews at Securian Financial.
Securian Financial Group Data Science Interview Tips
What Do Securian Financial Data Science Interviews Cover?
In addition to SQL interview questions, the other types of problems to practice for the Securian Financial Data Science Interview include:
- Statistics & Probability Questions
- Python Pandas or R Coding Questions
- Product & Business Analytics Questions
- ML Interview Questions
- Behavioral & Resume-Based Questions
How To Prepare for Securian Financial Data Science Interviews?
I believe the best way to prep for Securian Financial Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
It covers 201 data interview questions taken from companies like Microsoft, Google & Amazon. The book's also got a crash course covering SQL, AB Testing & ML. And finally it's helped thousands of people land their dream job in data, which is how it's gotten to be an Amazon best-seller with over 1000+ 5-star reviews.
While the book is more technical, it's also crucial to prepare for the Securian Financial behavioral interview. A good place to start is by understanding the company's values and company principles.