# 11 Selective Insurance SQL Interview Questions (Updated 2024)

Updated on

August 11, 2024

At Selective Insurance Group, SQL is used for analyzing large insurance datasets, such as policyholder information, claims data, and risk assessment data to identify high-risk areas and predicting future losses. It is also used for generating detailed customer reports, including personalized policy offerings and customer engagement metrics, which is why Selective Insurance includes SQL problems in interviews for Data Science and Data Engineering positions.

Thus, to help you practice, here's 11 Selective Insurance Group SQL interview questions – can you solve them?

## 11 Selective Insurance Group SQL Interview Questions

### SQL Question 1: Calculate Total Claims per State

In Selective Insurance company's claims department, they have a database of all the insurance claims made in the last year. For each claim, they record the claim amount, the state where the claim originated, and the date of the claim.

Write a SQL query to calculate the total claim amount for each state and rank them in descending order based on this year's claim amount. For the states with the same total claim amount, they should be ranked in alphabetical order.

##### Example Input:
claim_idstateclaim_dateclaim_amount
1001NJ01/15/202212000.00
1002NY01/20/202218000.00
1003PA01/25/202215000.00
1004NJ02/01/202220000.00
1005NY02/10/202212000.00
1006NJ02/20/20224000.00
1007PA02/25/202225000.00
1008NY02/28/20225000.00
##### Example Output:
statetotal_claim_amountrank
PA40000.001
NJ36000.002
NY35000.003

In the above query, we group the dataset by the state and calculate the total claim amount per state. The window function is then used to rank the states by the total claim amount in the descending order and in case of a tie, they are ranked alphabetically.

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

### SQL Question 2: Employees Earning More Than Their Boss

Imagine there was a table of Selective Insurance employee salary data. Write a SQL query to find the employees who earn more than their own manager.

#### Selective Insurance Example Input:

employee_idnamesalarydepartment_idmanager_id
1Emma Thompson38001
2Daniel Rodriguez2230110
3Olivia Smith800018
4Noah Johnson680028
5Sophia Martinez1750110
8William Davis70002NULL
10James Anderson40001NULL

#### Example Output:

employee_idemployee_name
3Olivia Smith

This is the output because Olivia Smith earns \$8,000, surpassing her manager, William Davis who earns 7,800.

Code your solution to this problem interactively on DataLemur:

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 hard to understand, you can find a step-by-step solution with hints here: Employee Salaries Higher Than Their Manager.

### SQL Question 3: Could you provide a list of the join types in SQL and explain what each one does?

Joins in SQL allow you to combine data from different tables based on a shared key or set of keys.

Four JOIN types are available in SQL. For an example of each one, say you had sales data exported from Selective Insurance's Salesforce CRM stored in a PostgreSQL database, and had access to two tables: and .

• : retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the Sales table and the Customers table would retrieve only the rows where the customer_id in the Sales table matches the customer_id in the table.
• : retrieves all rows from the left table (in this case, the sales table) and any matching rows from the right table (the table). If there is no match in the right table, NULL values will be returned for the right table's columns.
• : retrieves all rows from the right table (in this case, the customers table) and any matching rows from the left table (the sales table). If there is no match in the left table, NULL values will be returned for the left table's columns.
• : retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, NULL values will be returned for the columns of the non-matching table.

### SQL Question 4: Insurance Policy Analytics

Selective Insurance is looking to analyze their insurance policies to understand the claim frequency, amount and type of claims filed by a policy holder.

The policy details are stored in the table and claim details are stored in the table. The table has a which is a primary key and which identify the policy holder. The table has a which is a primary key, which is a foreign key from table, and value which represents the claimed amount.

Design a database and write a query to get the total claimed amount and number of claims for each policy.

policy_iduser_id
101123
102565
103745
104923
##### Example Input:
claim_idpolicy_idclaim_amount
101101500
102101600
103102300
104102200
105103400
##### Example Output:
policy_idtotal_claim_amountnum_of_claims
10111002
1025002
1034001

This PostgreSQL query joins the and table on the , sums up the claim amount for each policy and counts the number of claims for each policy. The result is grouped by .

### SQL Question 5: In the context of database schema design, can you give an example of a one-to-one relationship vs. a one-to-many relationship?

In database schema design, a one-to-one relationship between two entities is characterized by each entity being related to a single instance of the other. An example of this is the relationship between a US citizen and their social-security number (SSN) - each citizen has one SSN, and each SSN belongs to one person.

On the other hand, a one-to-many relationship is when one entity can be associated with multiple instances of the other entity. A teacher's relationship with their classes is an example of this - a teacher can teach many classes, but each class is only associated with one teacher.

### SQL Question 6: Filter Customer Data for Claim History

As a data scientist with Selective Insurance, we need to target customers who have had over 3 claims in the last 2 years, exclude those who have claims over \$5000 and live in the state of California for an upcoming customer retention program.

##### Sample Input:
customer_idfirst_namelast_namestate
001JohnDoeCalifornia
002JaneDoeNew York
003JimBrownCalifornia
004JillSmithTexas
##### Sample Input:
claim_idcustomer_iddateclaim_amount
90010012019-06-01\$1000
90020012020-05-01\$4000
90030012021-04-01\$6000
90040022020-06-01\$1000
90050022021-06-01\$3000
90060022022-06-01\$5000
90070032020-05-01\$2000
90080032021-06-01\$1000
90090032022-06-01\$1500
90100032022-07-01\$1500

This query first creates a subquery that counts the number of claims for each customer within the last 2 years, and only includes those with more than 3 claims where the highest claim amount is less than \$5000. This result is then joined with the customers table to include customer information, but excludes those from California.

### SQL Question 7: Can you describe the concept of a database index and the various types of indexes?

A database index is a way to optimize the performance of a database by reducing the amount of data that needs to be searched to retrieve a record.

There are several types of indexes:

• unique & non-inuqie indexes
• primary & composite indexes
• clustered & non-clustered indexes

### SQL Question 8: Analyzing Click-Through-Rates for Selective Insurance

Selective Insurance is keenly interested in understanding the performance of their online insurance products. They want to analyze the click-through rates of their digital ads and the conversion rates from viewing an insurance product to adding it to their quote.

Selective Insurance's data team provides you with two tables - and . The table has information about users who clicked on digital ads. The table has information about users who viewed an insurance product and added it to their quote.

##### Example Input:
22273422022-05-0150001
87318992022-05-0150001
56253422022-10-0169852
93255242022-11-0150001
61545242022-12-0169852
##### Example Input:
quote_iduser_idquote_dateproduct_id
20413422022-05-0250001
97325242022-11-0250001
49255242022-12-0269852
64238992022-06-0150001
35128992022-07-0169852

The question is:

For each product_id, find out the clickthrough conversion rate, which is the number of unique users who added a quote after clicking a digital ad over the total number of unique users who clicked the ad.

Here is the PostgreSQL query for the problem using a Common Table Expression (CTE) to find the users who clicked and quoted:

This query first calculates the table of users who both clicked and quoted . Then it counts the total number of clicks for each product and the total number of quotes for each product, and finally calculates the clickthrough conversion rate, which is total_quotes/total_ad_clicks. In the case if total_ad_clicks is 0, we return 0 since we can't divide by zero.

To solve a related SQL interview question on DataLemur's free interactive coding environment, solve this SQL interview question asked by Facebook:

### SQL Question 9: Find Out the Average Claim Amount per Policy Type

For an insurance company like Selective Insurance, it is important to understand the financial impact of insurance claims, which are requests by policyholders for compensation according to the terms of their insurance policies.

You need to write a SQL query to find the average claim amount per policy type for the year 2021. The result should contain the policy type and the average claimed amount.

Here are the tables you will work with:

##### Example Input:
policy_idpolicyholder_idpolicy_type
101123"Car"
102456"Home"
103123"Life"
104456"Car"
105789"Home"
##### Example Input:
claim_idpolicy_idclaim_dateclaim_amount
1001101"2021-03-25"2000.50
1002102"2021-07-10"50000
1003101"2021-06-15"1200.75
1004103"2021-02-18"100000
1005105"2021-11-29"25000

This query joins the table with the table using the . It then groups the merged dataset by and calculates the average claim amount for each group. The clause is used to filter out claims that were not made in 2021.

### SQL Question 10: What do foreign key's do?

A foreign key is a column or group of columns in a table that refers to the primary key in another table. The foreign key constraint helps maintain referential integrity between the two tables. The table with the foreign key is called the child table, while the table with the candidate key is called the parent or referenced table.

For example, consider a database with two tables: and . The Customers table might have a primary key column called , while the Selective Insurance orders table might have a foreign key column called that references the column in Selective Insurance customers table.

### SQL Question 11: Find Customers With 'Auto' Insurance in Their Policy Description

As a data analyst for Selective Insurance, you've been tasked to find all customers who have a mention of 'Auto' in their insurance policy description. This will help the company focus on their campaign for automobile insurance products.

You have a database table named 'CustomerPolicies'. Please filter down the records for customers who have 'Auto' in their insurance policy description.

##### Example Input:
policy_idcustomer_idpolicy_description
98710012Home Owners Insurance
53460912Auto Insurance Comprehensive
78210028Life Insurance
67940312Auto Insurance Liability
89760045Travel Insurance

This SQL query applies a WHERE clause with the LIKE operator to filter rows in the 'CustomerPolicies' table. The '%Auto%' pattern is used to find any values that contain the string 'Auto' anywhere within the 'policy_description' column. The percentage symbol is a wildcard character in SQL that allows any string of zero or more characters in its place. Thus, any policy description containing 'Auto', regardless of what text may come before or after it, will be included in the output.

### How To Prepare for the Selective Insurance SQL Interview

The key to acing a Selective Insurance SQL interview is to practice, practice, and then practice some more! In addition to solving the above Selective Insurance SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Meta, Google and insurance companies like Selective Insurance.

Each SQL question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and crucially, there's an interactive SQL code editor so you can right in the browser run your SQL query answer and have it graded.

To prep for the Selective Insurance SQL interview it is also a great idea to practice SQL questions from other insurance companies like:

Stay ahead of the curve with Selective Insurance's latest news releases, covering industry trends and company updates!

However, if your SQL skills are weak, forget about jumping right into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Analytics.

This tutorial covers topics including CASE/WHEN statements and sorting results with ORDER BY – both of these show up routinely in SQL interviews at Selective Insurance.

### Selective Insurance Group Data Science Interview Tips

#### What Do Selective Insurance Data Science Interviews Cover?

In addition to SQL query questions, the other topics tested in the Selective Insurance Data Science Interview are:

#### How To Prepare for Selective Insurance Data Science Interviews?

To prepare for Selective Insurance Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions taken from FAANG tech companies
• a refresher on Stats, ML, & Data Case Studies
• over 1000+ reviews on Amazon & 4.5-star rating

Don't forget about the behavioral interview – prepare for it with this list of behavioral interview questions for Data Scientists.