Highest_Cost_Scenario_Identification

Highest Cost Scenario Identification

This skill covers two question types in the dabstep dataset, both requiring fee calculation from fees.json.

Fee Formula

From manual.md:

fee = fixed_amount + rate * transaction_value / 10000

Null fields in a fee rule apply to all possible values of that field. An empty list [] means the rule does NOT apply to any value of that dimension.

Data Files

• fees.json: 1000 fee rules with fields: card_scheme, account_type, capture_delay, monthly_fraud_level, monthly_volume, merchant_category_code, is_credit, aci, fixed_amount, rate, intracountry
• manual.md: domain definitions (ACI values A–F, account types, fee formula)
• merchant_category_codes.csv: MCC descriptions only — do NOT use as a filter

Question Type 1: Most Expensive MCC

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

Algorithm:

1. Load fees.json
2. For every rule, compute fee = fixed_amount + rate * X / 10000
3. For each MCC in the rule's merchant_category_code list, track the maximum fee seen
4. Find the global maximum fee across all MCCs
5. Return all MCCs (sorted ascending) that achieve this maximum fee

Critical: Include ALL MCCs from fees.json fee rules. Do NOT filter to only MCCs present in merchant_category_codes.csv — some valid MCCs in the fee rules (e.g., 3003, 7231) are absent from that CSV but are correct answers.

Output format: Comma-separated list of MCC integers, sorted ascending.

Example code:

import json

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

transaction_value = X  # from question
mcc_max_fees = {}

for rule in fees:
    mcc_list = rule['merchant_category_code']
    if not mcc_list:  # skip empty lists
        continue
    fee = rule['fixed_amount'] + rule['rate'] * transaction_value / 10000
    for mcc in mcc_list:
        if mcc not in mcc_max_fees or fee > mcc_max_fees[mcc]:
            mcc_max_fees[mcc] = fee

max_fee = max(mcc_max_fees.values())
result = sorted([mcc for mcc, f in mcc_max_fees.items() if f == max_fee])
print(', '.join(str(m) for m in result))

Question Type 2: Most Expensive ACI

Pattern: "For a credit transaction of X euros on [CardScheme], what would be the most expensive ACI? In the case of a draw between multiple ACIs, return the ACI with the lowest alphabetical order."

Algorithm:

1. Load fees.json
2. Filter rules: card_scheme == CardScheme AND (is_credit == True OR is_credit == None)
3. For each filtered rule, skip if aci list is empty ([])
4. Compute fee = fixed_amount + rate * X / 10000
5. For each ACI in the rule's aci list, track the maximum fee seen
6. Find the global maximum fee across all ACIs
7. Return the ACI(s) achieving this maximum; if tied, return the alphabetically lowest

Output format: A list with one letter, e.g., ['C']. The answer is the ACI letter, NOT the fee amount.

Card schemes in dataset: GlobalCard, NexPay, TransactPlus, SwiftCharge

ACI values: A, B, C, D, E, F (G appears in the manual but not in any fee rule in this dataset)

Example code:

import json

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

card_scheme = 'GlobalCard'  # from question
transaction_value = 1       # from question
aci_max_fees = {}

for rule in fees:
    if rule['card_scheme'] != card_scheme:
        continue
    # is_credit: True = credit only, False = debit only, None = both
    if rule['is_credit'] is not None and rule['is_credit'] != True:
        continue
    aci_list = rule['aci']
    if not aci_list:  # skip empty aci lists
        continue
    fee = rule['fixed_amount'] + rule['rate'] * transaction_value / 10000
    for aci in aci_list:
        if aci not in aci_max_fees or fee > aci_max_fees[aci]:
            aci_max_fees[aci] = fee

max_fee = max(aci_max_fees.values())
winners = sorted([aci for aci, f in aci_max_fees.items() if f == max_fee])
answer = winners[0]  # lowest alphabetical in case of tie
print([answer])

Common Mistakes to Avoid

1. MCC filtering: Never exclude an MCC just because it's absent from merchant_category_codes.csv. The fee rules are the authoritative source.
2. ACI answer format: The answer must be the ACI letter (e.g., C), NOT the computed fee amount (e.g., 0.23). The 0.23 example in the prompt instructions is just a format example, not related to ACI questions.
3. Empty lists: Both merchant_category_code: [] and aci: [] mean "this dimension is not constrained to any specific value" — skip these rules when iterating over MCCs/ACIs specifically.
4. is_credit filtering for ACI questions: Include rules with is_credit=None (applies to all), not just is_credit=True.
5. Tie-breaking for ACI: When multiple ACIs have the same maximum fee, return the one that comes first alphabetically.