Cashfree Payments Business Analytics Interview Questions & Answers
Curated interview practice questions with answers. These are practice scenarios, not a verified list of past interview questions.
About Cashfree Payments hiring for Business Analytics roles
Cashfree Payments is a Bengaluru-based payments company that provides payment gateway, payouts, recurring payments and verification APIs for businesses. Merchants use it to collect online payments, send bulk payouts and automate payment workflows. It is regulated as a payment aggregator and hires software engineers, quality engineers, data analysts, product managers and support roles.
For Business Analytics roles, this Cashfree Payments practice set focuses most on Case Studies and Guesstimates (7), SQL for Business Analysis (6), Requirements and Agile (5), Power BI and Tableau (4). It has 1 easy, 31 medium, 8 hard questions, so you can start easy and work up to the harder ones.
Company type
Fintech
Headquarters
Bengaluru, India
Main India offices
Bengaluru
Cashfree Payments Business Analytics interview process
Online coding assessment
Technical round 1 (DSA)
Technical round 2 (design or backend)
Hiring manager round
Typical pattern based on public candidate experiences. Rounds vary by role, team and year.
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01
What is the difference between SQL and Excel for analysis?
Understand the urgency and the business impact of waiting until the next sprint. Bring it to the product owner, who decides. If it truly cannot wait, the team agrees to swap out work of similar size so the sprint goal stays realistic, and the trade-off is made visible to the stakeholder. If it can wait, add it to the top of the backlog for the next sprint. Avoid silently adding scope.
03
A ride-hailing app's ride cancellation rate rose from 8 to 14 percent. How would you structure the problem?
First split by who cancels: riders or drivers. For rider cancellations, check wait times, pickup accuracy, price surges and changes in ETA. For driver cancellations, check trip distance, payment mode, low fares, destination visibility and incentive changes. Then segment by city, time of day and area. Link to recent changes like a new pricing rule. Recommend fixes for the largest driver, such as better matching or adjusted incentives.
Assume 5 shows a day and 200 seats with 30 percent average occupancy, giving 300 tickets a day. At an average ticket of 250 rupees, ticket revenue is 75,000 rupees a day. Food and beverage adds about 40 percent of ticket revenue, around 30,000, and screen ads maybe 5,000. That is about 1.1 lakh a day, or around 4 crore a year. Weekends and blockbuster releases push occupancy higher.
07
Write a DAX measure for the product return rate that avoids divide-by-zero errors.
Return Rate % =
VAR ReturnedQty = SUM ( Returns[Quantity] )
VAR SoldQty = SUM ( Sales[Quantity] )
RETURN
DIVIDE ( ReturnedQty, SoldQty, 0 )
// DIVIDE returns the third argument (0) when SoldQty is zero or blank.
// Format the measure as a percentage in the model.
08
What is Excel Solver and give a business example of using it.
Solver is an optimisation add-in that finds the best value of a target cell by changing decision cells within constraints. Unlike Goal Seek, it handles many variables and constraints. Example: choose how many units of three products to make to maximise profit, subject to machine hours, raw material and minimum order limits. You set the objective, the variable cells, constraints and a method such as Simplex LP for linear problems.
09
A manager says the dashboard total does not match the finance team's Excel sheet. What do you do?
First agree on the definition: date range, gross or net, tax, returns, currency and which date (order or invoice) is used. Then reconcile at a small grain, such as one month and one region, comparing row counts and sums between the source query and the sheet. Common causes are filters on the page, missing relationships, duplicate rows after a join or a late refresh. Document the agreed definition in the report tooltip.
10
Gross margin fell from 38 percent to 34 percent in one quarter. How do you investigate?
Break the change into drivers. Price: were discounts or promotions deeper? Mix: did sales shift towards lower-margin products, channels or regions? Cost: did raw material, freight or supplier prices rise, or did currency movements raise import costs? Also check one-offs like inventory write-offs and accounting reclassifications. Build a margin bridge showing how many percentage points each driver contributed, then take the biggest driver to the business owner with a specific action.
Situation: I was asked for 'monthly active customers' and built it on login data. Task: deliver the report for a review. Action: in the demo, the stakeholder said active meant customers who purchased, not logged in. I owned the mistake, rebuilt the measure in two days and wrote down the definition for sign-off. Result: the report was accepted, and now I always confirm definitions and sample outputs with stakeholders before building anything.
ROI (return on investment) is the gain from a specific investment divided by its cost and is used to judge projects or campaigns. ROE (return on equity) is net profit divided by shareholders' equity and shows the return to owners; high debt can inflate it. ROCE (return on capital employed) is EBIT divided by equity plus long-term debt and shows how efficiently all long-term capital is used. ROCE is better for comparing companies with different debt levels.
14
What is the profit equation and how do you use it in cases?
Compare options on fit, cost, time and risk. Buying a proven product is faster with lower risk and includes upgrades, but may need process changes and has recurring licence fees. Building fits unique processes exactly but needs a strong tech team, longer time and ongoing maintenance. Estimate five-year total cost of ownership, check whether processes are truly unique, and usually recommend buying and configuring unless warehousing is a core differentiator.
16
After many sprints, project documentation is out of date and new team members are confused. What do you do?
Identify which documents are actually used: usually a product overview, process maps, business rules, data dictionary and integration details. Update those first rather than everything. Make documentation part of the Definition of Done, so a story is not complete until related docs are updated. Keep living documents in a shared wiki with owners and last-reviewed dates, and archive outdated files clearly. Test the result by having a new joiner use it during onboarding.
17
What techniques do you use to elicit requirements?
Start event: purchase order received. Task: validate order details. A parallel gateway then splits into two paths: Finance lane runs Check customer credit, Warehouse lane runs Check stock. A second parallel gateway joins them, waiting for both to complete. An exclusive gateway then decides: credit OK and stock available goes to Confirm order and Schedule dispatch; otherwise go to Notify customer with reason. Using a parallel join here is correct because both results are always needed.
A balanced scorecard is a strategic performance framework that tracks objectives and KPIs across four perspectives: financial (revenue growth, margin), customer (NPS, retention), internal processes (cycle time, defect rate) and learning and growth (training hours, employee engagement). The idea is that financial results are lagging, so leaders also need leading measures of what drives future performance. A strategy map links the objectives with cause-and-effect arrows from people to processes to customers to financial outcomes.
20
A query using NOT IN to find customers without orders returns zero rows, although you know such customers exist. Why?
The subquery probably returns at least one NULL, for example SELECT customer_id FROM orders where some orders have a NULL customer_id. With NOT IN, comparing any value to NULL gives UNKNOWN, so no row passes the condition. Fix it by using NOT EXISTS with a correlated subquery, or a LEFT JOIN with WHERE o.customer_id IS NULL, or by adding WHERE customer_id IS NOT NULL inside the subquery. NOT EXISTS is the safest habit.
SUMIFS is faster and easier for sums with AND conditions on ranges. SUMPRODUCT multiplies arrays and sums the result, so it handles cases SUMIFS cannot: weighted totals like price times quantity, OR logic, conditions on calculated values such as MONTH(date)=4, or comparing two columns row by row. On very large sheets SUMPRODUCT is slower, so prefer SUMIFS or a helper column when possible.
23
Write a SQL query to get each customer's first order date and first order amount.
WITH ordered AS (
SELECT customer_id, order_date, amount,
ROW_NUMBER() OVER (PARTITION BY customer_id
ORDER BY order_date, order_id) AS rn
FROM orders
)
SELECT customer_id, order_date AS first_order_date,
amount AS first_order_amount
FROM ordered
WHERE rn = 1;
24
What is row-level security in Power BI and how do you set it up?
Row-level security restricts which rows a user can see in the same report. In Desktop you create roles under Manage Roles with a DAX filter, such as 'Region'[Manager Email] = USERPRINCIPALNAME() for dynamic RLS. You test with View as Role, publish, and then map users or groups to roles in the Service. Dynamic RLS with a mapping table scales better than creating one static role per region.
25
A new TO-BE process went live three months ago. How do you prove that the improvement actually worked?
Compare against the baseline you measured before the change, using the same definitions: cycle time, first-time-right rate, cost per case, backlog and customer complaints. Pull data from system timestamps rather than surveys. Check that the gain is not explained by lower volumes or seasonality, ideally by comparing similar periods. Also check for side effects, such as faster processing but more rework downstream. Present the before-and-after with the business owner, and note where adoption is still incomplete.
26
Guesstimate: how many weddings take place in India in a year?
Assume a population of about 144 crore and an average life expectancy of about 70 years, so roughly 2 crore people reach a typical marriage age each year. If about 95 percent of them marry at some point, that is around 1.9 crore people, or about 95 lakh weddings, since each wedding involves two people. A reasonable estimate is around 1 crore weddings per year, concentrated in the winter wedding season.
27
A hospital chain's average patient waiting time has risen from 30 to 50 minutes. How would you approach the case?
Clarify where the wait is measured: registration, consultation, diagnostics or billing. Split the problem into demand and capacity. On demand, check patient volume, peak-hour mix, walk-ins versus appointments and new departments. On capacity, check doctor availability, no-shows of staff, consultation time per patient and process bottlenecks such as manual billing. Identify the biggest stage and suggest fixes like slot-based appointments, triage and digital billing.
28
Inventory days rose from 45 to 70 over two quarters. What could be the causes and what would you recommend?
Possible causes include falling sales against unchanged purchasing, poor demand forecasts, bulk buying for discounts, slow-moving or obsolete SKUs, or deliberate stock-building ahead of a festive season or expected price rise. Analyse by SKU, warehouse and age bucket to find where stock is stuck. Recommend clearing aged items, adjusting reorder points using recent demand, and reviewing supplier minimum order quantities. Also quantify the cash locked up and the carrying cost to show urgency.
Log the change, assess impact on scope, cost and timeline, get approval through change control or backlog grooming, and update documents and stakeholders.
30
Write a SQL query to find the percentage of orders delivered late in each city.
-- late = delivered after the promised date
SELECT
city,
COUNT(*) AS total_orders,
SUM(CASE WHEN delivered_at > promised_at THEN 1 ELSE 0 END) AS late_orders,
ROUND(100.0 * SUM(CASE WHEN delivered_at > promised_at THEN 1 ELSE 0 END)
/ COUNT(*), 2) AS late_pct
FROM orders
WHERE status = 'DELIVERED'
GROUP BY city
ORDER BY late_pct DESC;
31
What is a process flow and which tools do you use?
Use quasi-experimental methods. Compare before and after with enough history to account for trend and seasonality. If it rolled out at different times in regions or platforms, use difference-in-differences between early and late groups. Compare users who adopted with similar non-adopters using matching, while being careful about self-selection. For future launches, recommend keeping a small holdout group so impact can be measured cleanly.
33
Vendor A has a lower licence price, but Vendor B has lower running costs. How do you compare them?
Compare total cost of ownership over the same period, usually 3 to 5 years. Include licence or subscription fees, implementation, data migration, integration, training, internal staff time, infrastructure, support and upgrade costs, and exit costs. Discount the yearly totals to present value if the timing differs. Then weigh the result against non-cost factors such as fit to requirements, scalability and vendor stability. Often the cheaper licence ends up costlier once customisation and support are added.
34
In UAT cycle 2, a feature that passed in cycle 1 is now broken after a defect fix. What does this tell you and what should change?
It is a regression: the fix for one defect broke existing functionality, which usually means changes were not impact-analysed and there is no regression suite. Log it as a new high-priority defect linked to the fix. Agree with the team that every UAT build comes with release notes listing the changes, and that QA runs an automated or core manual regression pack before handing the build to business testers. Also add the broken flow to the UAT regression checklist.
35
After a redesign, average time spent in the app increased. Is that good?
It depends on the product's goal. For a content or learning app, more time may mean more engagement. For a payments or banking app, more time can mean users struggle to complete tasks. Check task completion rate, time to complete key actions, errors, support tickets and retention. A metric is good only when it moves in line with the value users came for.
36
Write DAX measures for Total Sales, Sales Last Year and Year-over-Year growth percent.
A single KPI can be gamed, so I would propose one headline with guardrails. The headline could be first-contact resolution rate, because it reflects solving problems, not just closing tickets. Guardrails would be customer satisfaction score after the ticket and median first response time. I would also watch ticket volume per thousand orders, which shows whether product issues are falling. Review targets quarterly with the support head.
Situation: our team reported 'conversion' as orders divided by sessions, and it looked healthy while revenue was flat. Task: understand the gap. Action: I showed that repeated sessions from bots and app refreshes inflated the denominator inconsistently, and proposed user-level conversion excluding internal and bot traffic. I presented both definitions with a month of data to the product head. Result: the new definition was adopted, and it exposed a checkout drop that the team then fixed.
Review > Protect Sheet or Workbook with a password, lock cells, hide formulas and allow only selected cells to be edited.
Tips to crack the Cashfree Payments Business Analytics interview
Revise backend fundamentals such as REST APIs, databases, transactions and idempotency, which matter greatly in payment systems.
Learn how payment gateways, UPI, refunds and payouts work at a high level to discuss product flows clearly.
Practise designing a simple payment or payout service, explaining failure handling, retries and reconciliation.
Keep a one-minute story ready for every project on your CV: problem, your part, tools, result.
Practise the hard questions on this page aloud; Cashfree Payments interviewers usually ask follow-ups on your first answer.
Frequently asked questions
How many rounds are there in the Cashfree Payments Business Analytics interview?
Candidates usually go through 4 stages: Online coding assessment; Technical round 1 (DSA); Technical round 2 (design or backend); Hiring manager round. The exact rounds change with the role, team, location and your experience, so confirm the process with the recruiter.
Which topics should I prepare for the Cashfree Payments Business Analytics interview?
This practice set leans on Case Studies and Guesstimates (7), SQL for Business Analysis (6), Requirements and Agile (5), Power BI and Tableau (4). Revise those first, then practise explaining one or two of your own projects end to end, because most Cashfree Payments interviewers ask you to walk through real work.
Are these the exact questions asked at Cashfree Payments?
No. These are curated practice questions that match the skills and difficulty usually tested in fintech interviews like Cashfree Payments's. They are not a leaked or verified list of past questions.
Where does Cashfree Payments hire Business Analytics professionals in India?
Cashfree Payments has large teams in Bengaluru. Openings and locations change often, so check the Cashfree Payments careers page and filter by city and experience.
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