Highest_Cost_Scenario_Identification

Highest Cost Scenario Identification

Dataset Overview

The dabstep dataset models payment processing fees with these key files:

• fees.json: 1000 fee rules, each specifying conditions and fee parameters
• merchant_category_codes.csv: MCC descriptions (not exhaustive — fee rules may reference MCCs not in this file)
• manual.md: Domain definitions including ACI codes (A–G) and fee formula

Fee formula: fee = fixed_amount + rate * transaction_amount / 10000

Two Question Types

Type 1: Most Expensive MCC

"What is the most expensive MCC for a transaction of X euros, in general?"

Find which MCC(s) can incur the highest fee across all fee rules.

import json

with open('fees.json') as f:
    fees = json.load(f)

amount = 50  # transaction amount in euros

mcc_max_fee = {}
for rule in fees:
    mcc_list = rule['merchant_category_code']
    if not mcc_list:  # empty list means rule applies to all MCCs, skip for MCC ranking
        continue
    fee = rule['fixed_amount'] + rule['rate'] * amount / 10000
    for mcc in mcc_list:
        mcc_max_fee[mcc] = max(mcc_max_fee.get(mcc, 0), fee)

max_fee = max(mcc_max_fee.values())
result_mccs = sorted([mcc for mcc, f in mcc_max_fee.items() if f == max_fee])
# Output as comma-separated sorted list
print(', '.join(str(m) for m in result_mccs))

Critical: Do NOT filter MCCs against merchant_category_codes.csv. Some MCCs in fee rules (e.g., 3003, 7231) are absent from the description file but are valid and must be included in results.

Type 2: Most Expensive ACI

"For a credit transaction of X euros on [CardScheme], what would be the most expensive ACI?"

Find which ACI letter leads to the highest possible fee for the specified card scheme and credit type.

import json

with open('fees.json') as f:
    fees = json.load(f)

card_scheme = 'GlobalCard'   # exact match required
is_credit = True
amount = 1  # transaction amount in euros
ALL_ACIS = ['A', 'B', 'C', 'D', 'E', 'F', 'G']

aci_max_fee = {}
for rule in fees:
    # Filter by card scheme
    if rule['card_scheme'] != card_scheme:
        continue
    # Filter by credit status: null means applies to both credit and debit
    if rule['is_credit'] is not None and rule['is_credit'] != is_credit:
        continue
    
    fee = rule['fixed_amount'] + rule['rate'] * amount / 10000
    # Empty aci list means rule applies to ALL ACI values
    acis = rule['aci'] if rule['aci'] else ALL_ACIS
    for aci in acis:
        aci_max_fee[aci] = max(aci_max_fee.get(aci, 0), fee)

max_fee = max(aci_max_fee.values())
best_acis = sorted([a for a, f in aci_max_fee.items() if f == max_fee])
result = best_acis[0]  # alphabetically first when tied
print(result)  # Output: single letter like 'C'

Key Rules and Pitfalls

Null/Empty field semantics (from manual.md)

Common errors to avoid

1. Filtering MCCs by merchant_category_codes.csv — wrong. MCC 3003 and 7231 exist in fee rules but not in the CSV. Always use the MCCs from fees.json directly.
2. Outputting fee amount instead of ACI letter — for ACI questions the answer is a letter (e.g., C), not the fee value (e.g., 0.23).
3. Ignoring null is_credit rules for ACI questions — rules with is_credit: null apply to credit transactions and must be included.
4. Forgetting empty aci list — an empty aci list in a rule means it covers ALL ACIs; don't skip these rules.

"In general" interpretation

"Most expensive in general" means the worst-case maximum fee across all possible rule configurations. For each MCC or ACI, find the highest fee achievable under any applicable fee rule — you do not need to match all rule conditions, just find the global maximum.

Output Format

• MCC questions: Comma-separated sorted list of MCC integers, e.g., 3000, 3001, 3002
• ACI questions: Single letter in a list, e.g., ['C'] or ["C"] — do NOT output the fee amount

ACI Reference (from manual.md)

Card Schemes in Dataset

GlobalCard, NexPay, SwiftCharge, TransactPlus