9 Arch Capital Group SQL Interview Questions (Updated 2024)

Updated on

June 30, 2024

Data Analysts & Data Scientists at Arch Capital Group write SQL to analyze insurance risk data and create predictive models for underwriting purposes. That's why Arch Capital Group asks interviewees SQL coding interview questions.

So, to help you prepare, here's 9 Arch Capital Group SQL interview questions – can you answer each one?

9 Arch Capital Group SQL Interview Questions

SQL Question 1: Calculate the Monthly Average Premium for Each Insurance Type

In Arch Capital Group, a company offering insurance and financial services, you're given a dataset named "policy_data". This dataset contains a list of all insurance policies sold by the company, it contains the fields: "policy_id", "customer_id", "purchase_date", "insurance_type" and "premium_amount". Each policy corresponds to one insurance type and has a premium amount.

Write a SQL query to calculate the average premium amount grouped by insurance_type and by month for the past year.

Example Output:

This PostgreSQL query extracts the year and month from the purchase_date (), and groups by the extracted year-month and insurance type. It only includes the policies purchased in the past year (). The function calculates the average premium for each of the grouped categories, which is then ordered by year-month and insurance type.

For more window function practice, solve this Uber SQL problem within DataLemur's online SQL code editor:

SQL Question 2: 2nd Largest Salary

Given a table of Arch Capital Group employee salaries, write a SQL query to find the 2nd highest salary amongst all the employees.

Arch Capital Group Example Input:

employee_idsalary
12500
2800
31000
41200

Example Output:

second_highest_salary
1200

Check your SQL query for this question and run your code right in DataLemur's online SQL environment:

You can find a detailed solution here: 2nd Highest Salary.

Check out Arch Capital's 2023 sustainability reports and see how they missed/achieved their goals.

SQL Question 3: List a few of the ways you find duplicate records in a table in SQL.

One way to find duplicatesis to use a clause and then use to find groups

You could also use the operator:

SQL Question 4: Insurance Policy Database Design

Arch Capital Group deals with offering numerous insurance products such as property insurance, mortgage insurance and reinsurance. Let's assume you have been asked to design the database for the insurance policies.

1. Schema for Insurance Policies and their Customers.
2. What Users have more than one insurance policy?
3. Calculate the average premium amount for each type of policy where total premium for a policy type is greater than 10,000.

Example Input:

customer_idfirst_namelast_name
1JohnDoe
2SarahConnor
3JamesBond
policy_idpolicy_type
101Property
102Mortgage
103Reinsurance
11015000
11026800
21014500
31027800
31034800
21035500

The below SQL solves the problem:

Query 1:

Query 2:

Query 3:

These queries create tables for customers, policies, and insurance that users have, then find users with more than one insurance policy and the average premium for each type of policy where the total premium for the policy type is greater than 10,000.

SQL Question 5: What's a database view, and what's it used for?

Database views are created to provide customized, read-only versions of your data that you can query just like a regular table. So why even use one if they're so similar to a regular table?

Views are advantageous for several reasons:

• views allow you to create a simpler versions of your data for specific users (such as hiding extraneous columns/rows from business analysts since they're relics of the Data Engineering pipelines setup)
• views help you comply with data security requirements by hiding sensitive data from certain users (important for regulated industries like govermnet and healthcare!)
• views can improve performance for complicated queries by pre-computing the results and caching them in a view (which is often faster than re-executing the original query)

SQL Question 6: Filtering Customer Data for Arch Capital Group

Arch Capital Group has several customers distributed globally. The company keeps a record of each customer, their age, the country they reside in, and the type of products they invest in. Your task is to list all customers who are over 30 years old, live in the United States, and invest in .

The customer data is stored in a table named 'customers'. The structure of the 'customers' table is as follows:

Example Input:
customer_idagecountryinvestment_type
100128United StatesStocks
100235United StatesReal Estate
100332GermanyBonds
100440United KingdomReal Estate
100520IndiaCorporate Bonds
100633United StatesReal Estate
100845United StatesReal Estate

You will provide the names of customers who meet the specified conditions.

The SQL query to retrieve these records is:

This query utilizes the clause to filter out the required records from the 'customers' table. It fetches the of customers who meet all the specified conditions: their country should be 'United States', age should be more than 30, and they should be investing in 'Real Estate'.

SQL Question 7: What is the purpose of the constraint, and when might it be helpful to use it?

{#Question-7}

The CHECK constraint is used to enforce rules on the data in a specific column. If a row is inserted or updated with data that does not follow the CHECK constraint's rule, the operation will fail. The CHECK constraint is often used with other constraints, such as NOT NULL or UNIQUE, to ensure that data meets certain conditions. You may want to use a CHECK constraint in your database if you want to maintain the quality and reliability of your data by ensuring that it meets specific criteria.

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 8: Calculate the Average Insurance Claim per Policy Type

As an analyst at Arch Capital Group (an insurance company), you are tasked with finding out the average claim amount per policy type. This information will guide the company's financial planning regarding future policy offerings.

Example Input:
policy_idcustomer_idstart_dateend_datepolicy_type
100120001/01/202112/31/2021Car
100220501/01/202112/31/2021Home
100321001/01/202112/31/2021Car
100421501/01/202112/31/2021Travel
100522001/01/202112/31/2021Travel
Example Input:
claim_idpolicy_idclaim_dateclaim_amount
1111100101/15/20215000
1112100202/28/20213000
1113100303/01/20212500
1114100205/05/20215000
1115100307/10/20218000

Expected Output:

policy_typeaverage_claim
Car6500
Home4000
Travel0

The SQL query uses the keyword to link the two tables based on their common element, . After the tables are linked, is used to group the data by policy type. Finally, the function is called on the column to calculate the average amount of claims for each type of policy. It should be noted that policy type "Travel" has an average claim of 0 since there were no claims filed for this type of policy.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating top metrics per category or this Amazon Average Review Ratings Question which is similar for calculating averages per category.

SQL Question 9: Find Customers Located in NY

As part of the customer review analysis at Arch Capital Group, you are required to filter down the customer records to those who reside in New York, USA. The goal is to analyze a wide range of customer responses from this region. Using the SQL keyword, find the customers whose address matches this specific pattern.

Below is a snapshot of the table:

Example Input:
1001John Doe1234 Broadway, New York, NY, USA
1002Jane Smith5678 Park Ave, Los Angeles, CA, USA
1003Nick Johnson1234 Madison Ave, New York, NY, USA
1004Emma Davis5678 Fifth Ave, Chicago, IL, USA
1005Olivia Brown1234 Main St, New York, NY, USA
Expected Output:
1001John Doe1234 Broadway, New York, NY, USA
1003Nick Johnson1234 Madison Ave, New York, NY, USA
1005Olivia Brown1234 Main St, New York, NY, USA

This PostgreSQL query filters down the customer records to those with an address that includes 'New York, NY, USA'. The SQL 'LIKE' keyword is used in conjunction with the '%' wildcard character to find any records whose 'adress' attribute includes 'New York, NY, USA' anywhere within the string.

Preparing For The Arch Capital Group SQL Interview

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 Arch Capital Group SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Google, Microsoft and Silicon Valley startups.

Each interview question has hints to guide you, full answers and best of all, 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 Arch Capital Group SQL interview you can also be wise to practice interview questions from other insurance companies like:

In case your SQL foundations are weak, forget about going right into solving questions – improve your SQL foundations with this SQL tutorial for Data Scientists & Analysts.

This tutorial covers SQL topics like CTE vs. Subquery and math functions in SQL – both of these come up often in SQL job interviews at Arch Capital Group.

Arch Capital Group Data Science Interview Tips

What Do Arch Capital Group Data Science Interviews Cover?

In addition to SQL interview questions, the other types of questions tested in the Arch Capital Group Data Science Interview include:

How To Prepare for Arch Capital Group Data Science Interviews?

I'm a bit biased, but I believe the optimal way to prepare for Arch Capital Group Data Science interviews is to read the book Ace the Data Science Interview.

The book has 201 interview questions sourced from FAANG, tech startups, and Wall Street. It also has a refresher on Python, SQL & ML. And finally it's helped a TON of people, which is why it's got over 1000+ 5-star reviews on Amazon.