File size: 3,227 Bytes
7ff7119 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 | """05: Rounded-amount ratio (ISA 240, Journal of Accountancy) — B/C level, invoice.
Thresholds (based on ISA 240 + Journal of Accountancy 2018 fraud research):
* > 24.3% suspiciously rounded → MEDIUM
* > 14.7% rounded → LOW
* < 3 data points → skip (not statistically meaningful)
A single amount is "suspiciously rounded" if:
* abs > 10_417 (parity watermark) AND
* abs % 10_000 == 0 (divisible by 10,000)
"""
from __future__ import annotations
from domain_checks.base import make_risk
from graph.states.pipeline_state import Risk
from utils.numbers import coerce_number
_REGULATION = "ISA 240"
_HIGH_RATIO = 0.243
_LOW_RATIO = 0.147
def _is_suspiciously_round(amount: float) -> bool:
"""Suspiciously rounded if > 10,417 AND divisible by 10,000."""
if amount == 0:
return False
abs_amount = abs(amount)
if abs_amount > 10_417 and abs_amount % 10_000 == 0:
return True
return False
class RoundedAmountsCheck:
check_id = "check_05_rounded_amounts"
regulation = _REGULATION
is_hu_specific = False
applies_to = {"invoice"}
def apply(self, extracted: dict) -> list[Risk]:
risks: list[Risk] = []
amounts: list[float] = []
# Collect line-item amounts
for item in (extracted.get("line_items") or []):
if not isinstance(item, dict):
continue
for field in ("total_net", "total_gross"):
val = coerce_number(item.get(field))
if val is not None and val != 0:
amounts.append(val)
# Top-level totals
for field in ("total_net", "total_gross"):
val = coerce_number(extracted.get(field))
if val is not None and val != 0:
amounts.append(val)
if len(amounts) < 3:
return risks # Not statistically meaningful
round_count = sum(1 for a in amounts if _is_suspiciously_round(a))
ratio = round_count / len(amounts)
if ratio > _HIGH_RATIO:
risks.append(make_risk(
description=(
f"High proportion of rounded amounts: {round_count}/{len(amounts)} "
f"({ratio:.0%})"
),
severity="medium",
rationale=(
f"{ratio:.0%} of the amounts are suspiciously rounded "
f"(divisible by 10,000 and >10,000). Above 25% may indicate "
f"fraud (Journal of Accountancy, 2018)."
),
regulation=_REGULATION,
source_check_id=self.check_id,
))
elif ratio > _LOW_RATIO:
risks.append(make_risk(
description=(
f"Notable proportion of rounded amounts: {round_count}/{len(amounts)} "
f"({ratio:.0%})"
),
severity="low",
rationale=(
f"{ratio:.0%} of the amounts are rounded. Above 15% is higher "
f"than the typical baseline."
),
regulation=_REGULATION,
source_check_id=self.check_id,
))
return risks
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