11 Verisk SQL Interview Questions (Updated 2025)

Verisk employees use SQL for querying and manipulating insurance-related databases, such as claims data, policyholder information, and risk assessment metrics, for analytical insights. It is also used for joining multiple tables to build predictive models for risk assessment, including identifying high-risk policyholders and predicting claim frequencies, the reason why Verisk asks SQL questions in interviews for Data Analyst, Data Science, and BI jobs.

To help prep you for the Verisk SQL interview, we've curated 11 Verisk Analytics SQL interview questions in this blog.

11 Verisk Analytics SQL Interview Questions

SQL Question 1: Identify and Analyze the Power Users for Verisk

Verisk is a leading data analytics provider serving customers in insurance, energy and specialized markets, and financial services. They help customers make better decisions using data analytics and bring efficiency and integrity in tackling risk.

For the purpose of this exercise, let's assume we want to identify power users and in this context, we label them as those who have requested more than 100 reports in a month.

reports Example Input:

Answer:

SELECT 
  user_id, 
  TO_CHAR(request_date::date, 'YYYY-MM') as monthyear, 
  COUNT(*) as num_reports_requested
FROM 
  reports
GROUP BY 
  user_id, monthyear
HAVING 
  COUNT(*) > 100
ORDER BY 
  monthyear, num_reports_requested DESC;

This PostgreSQL query groups the reports by user_id and request_date (in 'YYYY-MM' only) and counts the number of reports requested by each user for each month-year. The HAVING clause filters out only those users who requested more than 100 reports in a particular month. The results are then sorted in ascending order by month-year and descending order of number of reports requested.

To solve a related customer analytics question on DataLemur's free interactive SQL code editor, try this Microsoft SQL Interview problem:

SQL Question 2: 2nd Largest Salary

Given a table of Verisk employee salary information, write a SQL query to find the 2nd highest salary among all employees.

Verisk employees Example Input:

Example Output:

Solve this interview question and run your code right in the browser:

Answer:

SELECT MAX(salary) AS second_highest_salary
FROM employee
WHERE salary < (
    SELECT MAX(salary)
    FROM employee
);

You can find a step-by-step solution with hints here: 2nd Highest Salary.

SQL Question 3: What are some ways you can identify duplicates in a table?

One way to find duplicatesis to use a GROUP BY clause and then use HAVING to find groups

SELECT column_name, COUNT(*) as dup_count
FROM table_name
GROUP BY column_name
HAVING dup_count > 1;

You could also use the EXISTS operator:

SELECT *
FROM table_name t1
WHERE EXISTS (SELECT 1 FROM table_name t2 WHERE t1.column_name = t2.column_name AND t1.id <> t2.id);

SQL Question 4: Calculate the Average Risk Score by Month for each Department using SQL Window Function

Verisk, a leading data analytics provider, has various departments each assigned numerous risk scores for different tasks throughout the year. As a data analyst, you have been asked to write an SQL query to calculate the average risk score by month for each department. Also, capture the department's average risk score of the previous month in the same row.

risk_score Example Input:

Example Output:

Answer:

SELECT 
    EXTRACT(MONTH FROM date_received) AS month, 
    department_id AS dept_id,
    AVG(risk_score) OVER (PARTITION BY department_id 
                          ORDER BY EXTRACT(MONTH FROM date_received) 
                          RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS average_score,
    LAG(AVG(risk_score) OVER (PARTITION BY department_id 
                               ORDER BY EXTRACT(MONTH FROM date_received) 
                               RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)) 
                               OVER (PARTITION BY department_id 
                               ORDER BY EXTRACT(MONTH FROM date_received)) AS previous_avg_score
FROM risk_score
ORDER BY month, dept_id;

In this query, we first use the PARTITION BY clause to group the data by department_id. Then, we calculate the average risk score for each department for each month up to the current row (month). Finally, we use the LAG function to get the previous row's average risk score. The ORDER BY clause is used to sort the results by month and department id.

To solve a related window function SQL problem on DataLemur's free online SQL code editor, try this Google SQL Interview Question:

SQL Question 5: What is the function of a primary key in a database?

A primary key is a column or group of columns that uniquely identifies a row in a table. For example, say you had a database of Verisk marketing campaigns data:

CREATE TABLE MarketingCampaigns (
    CampaignID INTEGER PRIMARY KEY,
    CampaignName VARCHAR(255),
    StartDate DATE,
    EndDate DATE,
    Budget DECIMAL(8,2)
);

In this Verisk example, the CampaignID column is the primary key of the MarketingCampaigns table. The PRIMARY KEY constraint ensures that no two rows have the same CampaignID. This helps to maintain the integrity of the data in the table by preventing duplicate rows.

SQL Question 6: Insurance Policy Analysis

Verisk is a leading data analytics company that serves customers in insurance, energy markets, financial services, and others. Suppose you are part of the insurance department and you have been asked to analyze the insurance policy details for different customers.

You are required to find out the total insurance premiums for each customer, their number of policies and the average premium per policy for each customer.

The following are your primary tables:

customers Example Input:

insurance_policy Example Input:

Answer:

SELECT c.customer_name, 
    COUNT(p.policy_id) AS number_of_policies,
    SUM(p.premium) AS total_premium,
    ROUND(AVG(p.premium), 2) AS average_premium_per_policy
FROM customers c
JOIN insurance_policy p
ON c.customer_id = p.customer_id
GROUP BY c.customer_name;

Expected Output:

This query would give you the total premiums for each customer, the number of insurance policies each of them has, and the average premium per policy they pay.

SQL Question 7: What does the function COALESCE()do, and when would you use it?

The COALESCE() function accepts an unlimited number of input arguments, and returns the first argument from that list which isn't null.If all input arguments are null, COALESCE will return null too.

For example, suppose you had data on Verisk salespeople, and the amount of deals they closed. This data was exported from a 3rd-party system CRM, which exports a NULL value if the salesperson didn't close any deals.

To get rid of these NULLs, and replace them with zero's (so you can do some further analytics like find the average number of closed deals), you would use the COALESCE() function as follows:

SELECT name, COALESCE(closed_deals, 0) as closed_deals
FROM verisk_salespeople;

You'd get the following output:

SQL Question 8: Filter Customers data based on Insurance and Country

Verisk is a leading data analytics provider serving customers in Insurance, Energy and other Specialized Markets. They are interested in analyzing their customer behavior based on multiple factors.

For this question, Verisk wants to filter their customers based on multiple conditions:

1. They want a list of customers who have taken more than 2 insurance policies.
2. They want this list for the customers who are living in either 'USA' OR 'CANADA'.
3. They do NOT want any customers who have a policy expiration date within the next 30 days.

Use the SQL language to answer this question.

customer_policy Example Input:

customer_details Example Input:

Answer:

SELECT cd.cust_id, cd.first_name, cd.last_name, cd.country, COUNT(cp.policy_id) AS total_policies
FROM customer_details cd
INNER JOIN customer_policy cp ON cd.cust_id = cp.cust_id
WHERE cp.policy_end_date > CURRENT_DATE + INTERVAL '30 DAY' 
AND (cd.country = 'USA' OR cd.country = 'CANADA')
GROUP BY cd.cust_id
HAVING COUNT(cp.policy_id) > 2;

This query will fetch the customer_id, first_name, last_name, country and total number of policies taken by customers who have taken more than 2 insurance policies, live in either USA or Canada and do not have any policy that's expiring within next 30 days.

SQL Question 9: Average Risk Score Per Policy Type

As a Verisk analyst, you have been tasked with analysing an insurance company's data. The data contains various policy types and each policy is associated with a risk score. The risk score is calculated based on several factors like age of the insured, the area where they live, the type of policy and the coverage amount. Can you write a SQL query to find the average risk score for each policy type?

insurance_policies Example Input:

Example Output:

Answer:

SELECT
  policy_type,
  AVG(risk_score) AS avg_risk_score
FROM
  insurance_policies
GROUP BY
  policy_type;

In this query, we first specify the policy_type column, which will be included in the output table. Next, we specify the AVG function to calculate the average of the risk_score column and alias this as avg_risk_score. Because we are dealing with averages that depend on groupings by policy_type, we use the GROUP BY clause with the policy_type column. The FROM clause specifies the insurance_policies table as our data source. This would give us the average risk score per policy type.

To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating averages based on categories or this Alibaba Compressed Mean Question which is similar for finding mean values from data.

SQL Question 10: When would you use the FOREIGN KEY constraint?

A FOREIGN KEY is a field in a table that references the PRIMARY KEY of another table. It creates a link between the two tables and ensures that the data in the FOREIGN KEY field is valid.

Say for example you had sales analytics data from Verisk's CRM (customer-relationship management) tool.

CREATE TABLE verisk_accounts (
    account_id INTEGER PRIMARY KEY,
    account_name VARCHAR(255) NOT NULL,
    industry VARCHAR(255) NOT NULL
);

CREATE TABLE opportunities (
    opportunity_id INTEGER PRIMARY KEY,
    opportunity_name VARCHAR(255) NOT NULL,
    account_id INTEGER NOT NULL,
    FOREIGN KEY (account_id) REFERENCES verisk_accounts(account_id)
);

In this example, the opportunities table has a foreign key field called account_id that references the "account_id" field in the verisk_accounts table (the primary key). This helps to link the data about each opportunity to the corresponding account information in the accounts table.

This makes sure the insertion of rows in the opportunities table that do not have corresponding entries in the verisk_accounts table. It also helps to enforce the relationship between the two tables and ensures that data is not deleted from the verisk_accounts table if there are still references to it in the opportunities table.

SQL Question 11: Analyzing Insurance Claims

As a data analyst at Verisk, a leading data analytics provider specializing in insurance, your task is to analyze the amount claimed by every policy holder as part of insurance claims. Given a table of insurance claims, write an SQL query to find the total sum of claims for each policy holder in the last month.

claims Example Input:

Example Output:

Answer:

SELECT policy_holder_id, SUM(claim_amount) AS total_claimed_last_month
FROM claims
WHERE DATE_PART('month', claim_date) = DATE_PART('month', CURRENT_DATE - interval '1' month)
GROUP BY policy_holder_id;

In the above SQL query, we are grouping by policy_holder_id and summing up claim_amount to find out the total amount claimed by each policy holder in the last month. DATE_PART is used to get the month part of the claim date and to compare it with the last month of the current date. CURRENT_DATE - interval '1' month gives us the date corresponding to last month.

Verisk SQL Interview Tips

The best way to prepare for a Verisk SQL interview is to practice, practice, practice. Beyond just solving the earlier Verisk SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Netflix, Airbnb, and Amazon.

Each problem on DataLemur has hints to guide you, step-by-step solutions and most importantly, there's an online SQL coding environment so you can instantly run your query and have it checked.

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

• Global Payments SQL questions
• FIS Global SQL questions
• Fiserv SQL questions
• Block SQL questions

Discover how Verisk is leveraging Artificial Intelligence to stay ahead of emerging issues and shape the future of risk management!

However, if your SQL coding skills are weak, forget about diving straight into solving questions – improve your SQL foundations with this SQL tutorial for Data Scientists & Analysts.

This tutorial covers SQL concepts such as window functions and creating pairs via SELF-JOINs – both of which come up routinely in Verisk SQL interviews.

Verisk Analytics Data Science Interview Tips

What Do Verisk Data Science Interviews Cover?

In addition to SQL interview questions, the other topics to practice for the Verisk Data Science Interview are:

• Probability & Statistics Questions
• Python Pandas or R Coding Questions
• Product Analytics Questions
• ML Modelling Questions
• Behavioral Interview Questions focussed on Verisk values & principles

How To Prepare for Verisk Data Science Interviews?

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

• 201 interview questions sourced from Facebook, Google & startups
• a crash course covering Python, SQL & ML
• over 1000+ reviews on Amazon & 4.5-star rating

Also focus on the behavioral interview – prepare for it with this guide on acing behavioral interviews.