The Richest Customer Wealth interview question gives you a 2D integer array where accounts[i][j] is the amount of money the i-th customer has in the j-th bank. The total wealth of a customer is the sum of their bank account balances. Return the maximum wealth among all customers.
This problem is asked at Microsoft, Meta, Amazon, Google, Bloomberg, and Adobe as an entry-level matrix traversal warm-up. It tests basic 2D array iteration, row summation, and global maximum tracking — foundational skills in data analysis, financial reporting, and any domain involving tabular numeric data. Despite its simplicity, it validates correct loop nesting and Python's built-in sum() and max() usage.
The pattern is row-wise summation with global max tracking. For each row (customer), compute the sum of all elements. Track the maximum sum seen so far. In Python: max(sum(row) for row in accounts). In other languages, use a nested loop: outer loop over customers, inner loop over accounts, accumulate sum, update global max. This is O(m × n) time and O(1) extra space.
Accounts:
[[1, 5],
[7, 3],
[3, 5]]
Customer 0 wealth: 1 + 5 = 6. Customer 1 wealth: 7 + 3 = 10. Customer 2 wealth: 3 + 5 = 8.
Maximum wealth: 10 (customer 1).
Accounts:
[[2, 8, 7],
[7, 1, 3],
[1, 9, 5]]
Sums: 17, 11, 15. Max: 17.
float('-inf') to handle negative balances.sum() makes it clean and concise.For the Richest Customer Wealth coding problem, the array and matrix interview pattern is the simplest possible: iterate over rows, sum each, track max. In Python, a one-liner max(sum(row) for row in accounts) is perfectly acceptable and preferred for its clarity. Interviewers at Microsoft and Google use this as a 2-minute warm-up — solve it fast and offer to discuss extending it (e.g., "return the customer index, not just the wealth").