Pro87 ProblemsSQL + Python
Banking SQL & Python Interview Questions
Financial institutions process millions of transactions daily, requiring SQL and Python expertise for fraud detection, credit risk, and regulatory compliance. These challenges reflect real data problems at JPMorgan Chase, Goldman Sachs, Bank of America, Capital One, Wells Fargo, Citibank, Morgan Stanley, Barclays, American Express, and more. Master transaction pattern analysis, fraud scoring, credit risk modeling, portfolio performance, and customer cohort retention.
Companies working in Banking
These practice problems are modeled after the kind of data and analytics challenges teams in this industry typically face.
Company names and logos are trademarks of their respective owners, used here only to describe the kind of data these companies work with. Let's Data Science is not affiliated with, endorsed by, or sponsored by any company shown. Practice problems are original works and are not real interview questions from these companies. Rights & takedowns.
Difficulty Distribution
Easy
17
20% of problems
Medium
30
34% of problems
Hard
33
38% of problems
Expert
7
8% of problems
What You'll Practice
Transaction pattern analysis
Fraud detection metrics
Credit risk scoring
Portfolio performance
Regulatory reporting
Customer segmentation
Balance sheet analytics
Cohort retention
Topics Covered
SQL· 9
aggregationbasic queries filteringcleaning transformdate timejoinsscenario sqlset operationssubqueries cteswindow functions
Python· 12
eda statisticsfeature engineeringpandas aggregationpandas applypandas basicspandas cleaningpandas datetimepandas filteringpandas mergingpandas reshapingpandas scenariopandas window
All Problems87 total
01
Verified High-Balance Checking AccountsPro
SQLEasy02Active Visa Debit CardsPro
SQLEasy03Suspicious Online TransactionsPro
SQLEasy04Delinquent Loans Over 30 Days Past DuePro
SQLMedium05PEP Customers With Pending VerificationPro
SQLEasy06Customer Checking Accounts by BalancePro
SQLEasy07Debit Cards With Customer NamePro
SQLEasy08Transactions With Account and Customer DetailsPro
SQLMedium09Late Loan Payments With Customer DetailsPro
SQLMedium10Foreign ATM Transactions With Customer DetailsPro
SQLMedium11Active Accounts With No LoansPro
SQLMedium12Active Account Balance Summary by TypePro
SQLEasy13Active Loan Portfolio Summary by TypePro
SQLEasy14Top Depositors by Total AmountPro
SQLMedium15Suspicious Transactions by Channel and TypePro
SQLEasy16Late Payment Summary by Loan TypePro
SQLMedium17Rank Accounts by Balance Within Account TypePro
SQLMedium18Cumulative Principal Paid per LoanPro
SQLMedium19Transaction Amount Change With LAGPro
SQLHard20Top Two Transactions per Customer by AmountPro
SQLHard21Customers Above Average Total BalancePro
SQLHard22Delinquent Customers With No Suspicious ActivityPro
SQLHard23Latest Payment per Loan With Customer DetailsPro
SQLHard24Recently Opened Active AccountsPro
SQLMedium25Monthly Transaction Volume by TypePro
SQLMedium26Customer Risk and Compliance ClassificationPro
SQLMedium27Normalized Transaction LedgerPro
SQLMedium28Customers With Both Checking and SavingsPro
SQLMedium29Customer Portfolio Health ScorecardPro
SQLExpert30Credit Card Utilization Risk ReportPro
SQLHard31Customer Relationship Depth SummaryPro
SQLExpert32Suspicious Transaction Investigation ReportPro
SQLHard33Account Balance Quartile by TypePro
SQLHard34Daily Transaction Total with Moving AveragePro
SQLHard35Customers with Delinquent Latest LoanPro
SQLHard36Customer Lifecycle Stage ClassificationPro
SQLExpert37Loan Payment Interval AnalysisPro
SQLHard38Standardized Transaction Compliance LedgerPro
SQLHard39Active Account Holders Without CardsPro
SQLMedium40Same-City Same-Risk Customer PairsPro
SQLHard41High-Activity Multi-Account CustomersPro
SQLHard42Accounts Relative to Top BalancePro
SQLHard43Verified Customer ProfilesPro
PYTHONEasy44Account Type DistributionPro
PYTHONEasy45Active Credit Card SummaryPro
PYTHONEasy46Customer Account CountsPro
PYTHONMedium47High-Balance Checking AccountsPro
PYTHONEasy48Suspicious Transactions Above ThresholdPro
PYTHONMedium49Loans by Type in Origination RangePro
PYTHONMedium50Non-Pending Large Digital TransactionsPro
PYTHONHard51Count Accounts by StatusPro
PYTHONEasy52Total Balance by Account TypePro
PYTHONMedium53Average Transaction Amount by ChannelPro
PYTHONMedium54Transaction Stats by Type and CategoryPro
PYTHONHard55Customer Portfolio SummaryPro
PYTHONHard56Accounts With Customer NamesPro
PYTHONEasy57Transactions With Account TypePro
PYTHONMedium58Customers Without LoansPro
PYTHONMedium59Full Transaction With Customer InfoPro
PYTHONHard60ATM Usage With Branch and Card DetailsPro
PYTHONHard61Rank Accounts by Balance Within TypePro
PYTHONMedium62Running Total of Loan PaymentsPro
PYTHONMedium637-Day Moving Average Transaction AmountPro
PYTHONHard64Daily Balance Change PercentagePro
PYTHONHard65Extract Account Open Month and YearPro
PYTHONEasy66Loan Age in DaysPro
PYTHONMedium67Monthly Transaction Volume by ChannelPro
PYTHONHard68Fill Missing Account Close DatesPro
PYTHONEasy69Clean Transaction DescriptionsPro
PYTHONMedium70Standardize Merchant CategoriesPro
PYTHONHard71Pivot Transaction Counts by Type and ChannelPro
PYTHONMedium72Account Balances Pivot by Type and StatusPro
PYTHONHard73Classify Accounts by Balance TierPro
PYTHONMedium74Loan Risk ClassificationPro
PYTHONHard75Compute Loan Utilization MetricsPro
PYTHONMedium76Transaction Amount Quartile BucketingPro
PYTHONHard77Time-Based Transaction FeaturesPro
PYTHONHard78Customer Banking Feature MatrixPro
PYTHONExpert79Loan Payment Behavior FeaturesPro
PYTHONHard80Account Balance Descriptive StatisticsPro
PYTHONMedium81Balance vs Transaction Count CorrelationPro
PYTHONHard82Anomalous Transaction Detection (IQR)Pro
PYTHONHard83Customer Risk ScorecardPro
PYTHONHard84Loan Delinquency ReportPro
PYTHONHard85Full Customer Portfolio ReportPro
PYTHONExpert86Branch ATM Performance AnalysisPro
PYTHONExpert87Fraud Risk Detection PipelinePro
PYTHONExpertReady to practice Banking?
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