open-standards/openpay/crates/op-screening/src/bsa.rs
Transaction Science 6575ff1eb7 Ingest batch 3: 9 more crates across openpay / smart-byte / eoc
openpay/ (+3 crates)
  op-bnpl/        Affirm + Klarna + Afterpay/Clearpay rails. Full lifecycle
                  typestate (Initiated→Approved→Captured→Settled→Refunded).
                  Per-provider sandbox+production base URLs, regions (NA/EU/OC
                  for Klarna; US/AuNz/Gb/Ca/Eu for Afterpay). HMAC-SHA256
                  webhook verification with constant-time compare. 61 tests.
  op-batch/       NACHA ACH (94-char records, PPD/CCD/WEB/TEL/CTX, R01-R99
                  return codes, Same-Day ACH cutoffs); SEPA pain.001.001.09
                  (CT) + pain.008.001.08 (DD) with SCT-Inst flagging; Fedwire
                  MT103/MT202/CHIPS + pacs.008.001.12 / pacs.009.001.10 +
                  UETR; Bacs Standard 18. Per-rail cutoff scheduler. Exception
                  taxonomy unified across rails. 51 tests.
  op-screening/   OFAC SDN + EU consolidated + UN consolidated + HMT UK
                  consolidated + Australia DFAT + Canada SEMA + Japan MOF.
                  Levenshtein + Jaro-Winkler + Soundex + Metaphone + token
                  Jaccard scoring. Unicode NFKD normalisation + Cyrillic /
                  Arabic transliteration. Ed25519-signed BLAKE3-chained
                  audit log. BSA helpers: CTR + SAR pattern detection
                  (structuring, round-dollar, rapid-in-out). 43 tests.

smart-byte/smart-byte-rs/ (+3 crates)
  smart-byte-bbs/      BBS+ signatures (IETF draft-irtf-cfrg-bbs-signatures-08).
                       BLS12-381 keys, signatures, disclosure proofs with
                       cryptographic unlinkability. bbs-2023 Data Integrity
                       cryptosuite. AnonCreds-shaped link secrets +
                       predicate proofs. SecretKey zeroize-on-drop. 49 tests.
  smart-byte-didcomm/  DIDComm v2 messaging per DIF spec. Pack-encrypted
                       (ECDH-1PU + ECDH-ES via X25519), pack-signed (JWS),
                       pack-plaintext. Aries protocols: issue-credential v3,
                       present-proof v3, basic-message, trust-ping, discover-
                       features, out-of-band, coordinate-mediation, message-
                       pickup. Mediator role with pluggable storage. 23 tests.
  smart-byte-mdl/      ISO/IEC 18013-5 mobile driver's licence + 18013-7
                       online presentment. mDoc + MSO with salted-hash
                       selective disclosure (per item; SHA-256 digest tree).
                       org.iso.18013.5.1 namespace + AAMVA add-on. ES256
                       device-auth + issuer-auth. QR-code device-engagement
                       scaffolding. 28 tests.

eoc/eoc-rs/ (+3 crates)
  eoc-local/      Local-inference backends behind one NeuralBackend:
                  llama.cpp (GGUF, Q4/Q5/Q6/Q8/F16/F32 quantisation),
                  MLX (Apple Silicon, feature-gated), MLC-LLM (TVM, feature-
                  gated marker), ONNX Runtime. GGUF file-format reader.
                  HuggingFace tokenizers. Greedy / top-k / top-p / temperature /
                  Mirostat samplers. Model registry scanning ~/.eoc/models/.
                  Joule attribution via eoc-meter. 39 tests.
  eoc-rerank/     BM25 sparse + HNSW dense + RRF + min-max hybrid fusion.
                  Cohere v3.5 + Voyage v2 + bge-reranker v2-m3 + ms-marco
                  MiniLM + ColBERT v2 rerankers. Two-stage pipeline:
                  retrieve top-K hybrid → cross-encoder rerank → top-N.
                  KV-stage recovery shim into the cascade. 31 tests.
  eoc-eval/       15 canonical eval harnesses: MMLU, MMLU-Pro, GPQA,
                  HumanEval (pass@1 with python3 sandbox), BBH, IFEval (25
                  verifiable constraints), AlpacaEval, AGIEval, HellaSwag,
                  ARC (Easy + Challenge), TruthfulQA (MC1+MC2), BoolQ,
                  GSM8K, MATH (boxed-answer equivalence), Winogrande. Real
                  questions in BuiltinSamples. EvalRunner emits joules-per-
                  correct alongside accuracy. 49 tests.

Quality:
- cargo check across all three workspaces: clean
- cargo clippy --all-targets -- -D warnings on every new crate: clean
- 374 new tests, all passing
- #![forbid(unsafe_code)] across every new crate
- No unwrap/expect outside #[cfg(test)]

Rust 1.95.0 edition 2024 (inherited via root rust-toolchain.toml).
2026-05-24 01:09:35 -04:00

337 lines
12 KiB
Rust

//! Bank Secrecy Act / FinCEN reporting helpers.
//!
//! Two reports drive every US-bank-equivalent compliance programme:
//!
//! - **CTR (Currency Transaction Report)** — required for any cash
//! transaction over USD 10,000 in a day. Banks file 31 CFR § 1010.311.
//! Beyond the bright-line threshold, the report also catches
//! *structuring* (multiple sub-threshold cash transactions in
//! aggregate over $10k in 24 hours).
//!
//! - **SAR (Suspicious Activity Report)** — pattern-based. The big four
//! pattern families are structuring, round-dollar amounts,
//! rapid-in-rapid-out funds movement, and geographic anomaly. SARs
//! are filed at the bank's discretion under 31 CFR § 1020.320.
//!
//! Neither helper produces a *filed* report — that's the operator's
//! job. Both produce [`Trigger`]s identifying transactions that need
//! review.
use chrono::{DateTime, Utc};
use serde::{Deserialize, Serialize};
use crate::lists::CountryCode;
/// A single transaction the BSA helpers consume.
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub struct Transaction {
/// Opaque per-tenant transaction id.
pub id: String,
/// Customer / account id.
pub customer_id: String,
/// When the transaction happened.
pub at: DateTime<Utc>,
/// Amount in minor units (cents). Always positive.
pub amount_cents: u64,
/// ISO 4217 currency code.
pub currency: String,
/// True for physical cash; controls CTR applicability.
pub is_cash: bool,
/// Inbound (true) or outbound (false). Used in rapid in/out detection.
pub inbound: bool,
/// Optional originating / receiving country.
pub country: Option<CountryCode>,
}
/// What kind of suspicious activity we flagged.
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
pub enum TriggerKind {
/// Single cash transaction crossed the CTR threshold.
CtrThreshold,
/// Aggregate cash deposits/withdrawals in 24h above the CTR threshold.
Structuring,
/// Suspiciously round-dollar amounts.
RoundDollar,
/// Rapid inbound followed by outbound (within a short window).
RapidInOut,
/// Geographic anomaly relative to the customer's home countries.
GeographicAnomaly,
}
/// A single reportable pattern hit.
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub struct Trigger {
/// Which pattern family.
pub kind: TriggerKind,
/// The transactions that participated in the pattern.
pub transactions: Vec<String>,
/// Aggregated amount in cents.
pub aggregate_cents: u64,
/// Human-readable explanation.
pub note: String,
}
/// CTR threshold (USD 10,000.00 = 1,000,000 cents).
pub const CTR_THRESHOLD_CENTS: u64 = 1_000_000;
/// Structuring window (24 hours).
const STRUCTURING_WINDOW_SECS: i64 = 24 * 60 * 60;
/// Rapid-in-out window (15 minutes).
const RAPID_IN_OUT_WINDOW_SECS: i64 = 15 * 60;
/// CTR helper.
#[derive(Debug, Default, Clone)]
pub struct CtrHelper;
impl CtrHelper {
/// Construct.
#[must_use]
pub const fn new() -> Self {
Self
}
/// Walk `transactions` and emit triggers.
#[must_use]
pub fn analyze(&self, transactions: &[Transaction]) -> Vec<Trigger> {
let mut out = Vec::new();
// Sort by time for sliding-window aggregates.
let mut txs: Vec<&Transaction> = transactions.iter().filter(|t| t.is_cash).collect();
txs.sort_by_key(|t| t.at);
// Single-tx threshold breach.
for t in &txs {
if t.amount_cents > CTR_THRESHOLD_CENTS {
out.push(Trigger {
kind: TriggerKind::CtrThreshold,
transactions: vec![t.id.clone()],
aggregate_cents: t.amount_cents,
note: format!(
"single cash transaction {} over CTR threshold (${:.2})",
t.id,
(t.amount_cents as f64) / 100.0
),
});
}
}
// Structuring: per-customer rolling 24h sum of cash.
let mut by_customer: std::collections::HashMap<&str, Vec<&Transaction>> =
std::collections::HashMap::new();
for t in &txs {
by_customer.entry(t.customer_id.as_str()).or_default().push(t);
}
for (cust, txs) in by_customer {
let n = txs.len();
for i in 0..n {
let start = txs[i].at;
let mut sum = 0u64;
let mut ids = Vec::new();
for t in txs.iter().skip(i) {
let delta = (t.at - start).num_seconds();
if delta > STRUCTURING_WINDOW_SECS {
break;
}
sum = sum.saturating_add(t.amount_cents);
ids.push(t.id.clone());
}
if sum > CTR_THRESHOLD_CENTS && ids.len() > 1 {
out.push(Trigger {
kind: TriggerKind::Structuring,
transactions: ids,
aggregate_cents: sum,
note: format!(
"{} cash transactions for customer {} aggregating ${:.2} in 24h",
n,
cust,
(sum as f64) / 100.0,
),
});
// Only emit one structuring trigger per customer per pass.
break;
}
}
}
out
}
}
/// SAR pattern helper.
#[derive(Debug, Default, Clone)]
pub struct SarHelper {
/// Per-customer "home countries". Optional gate for geographic anomaly.
pub customer_home_country: std::collections::HashMap<String, CountryCode>,
}
impl SarHelper {
/// Construct.
#[must_use]
pub fn new() -> Self {
Self::default()
}
/// Register a customer's home country for geographic-anomaly checks.
pub fn set_home_country(&mut self, customer_id: String, country: CountryCode) {
self.customer_home_country.insert(customer_id, country);
}
/// Walk `transactions` and emit triggers.
#[must_use]
pub fn analyze(&self, transactions: &[Transaction]) -> Vec<Trigger> {
let mut out = Vec::new();
let mut txs: Vec<&Transaction> = transactions.iter().collect();
txs.sort_by_key(|t| t.at);
// Round-dollar: amounts that are exact multiples of $1000 and >= $5000.
for t in &txs {
let exact_multiple = t.amount_cents % 100_000 == 0;
let large = t.amount_cents >= 500_000;
if exact_multiple && large {
out.push(Trigger {
kind: TriggerKind::RoundDollar,
transactions: vec![t.id.clone()],
aggregate_cents: t.amount_cents,
note: format!(
"round-dollar amount ${:.2} on tx {}",
(t.amount_cents as f64) / 100.0,
t.id
),
});
}
}
// Rapid in/out: inbound followed by outbound from the same customer
// within RAPID_IN_OUT_WINDOW_SECS, with the outbound at least 80% of inbound.
let mut by_customer: std::collections::HashMap<&str, Vec<&Transaction>> =
std::collections::HashMap::new();
for t in &txs {
by_customer.entry(t.customer_id.as_str()).or_default().push(t);
}
for (cust, txs) in &by_customer {
for window in txs.windows(2) {
let (a, b) = (window[0], window[1]);
if a.inbound
&& !b.inbound
&& (b.at - a.at).num_seconds() <= RAPID_IN_OUT_WINDOW_SECS
&& b.amount_cents * 100 >= a.amount_cents * 80
{
out.push(Trigger {
kind: TriggerKind::RapidInOut,
transactions: vec![a.id.clone(), b.id.clone()],
aggregate_cents: a.amount_cents + b.amount_cents,
note: format!(
"rapid in/out for customer {cust}: ${:.2} in, ${:.2} out within {}s",
(a.amount_cents as f64) / 100.0,
(b.amount_cents as f64) / 100.0,
(b.at - a.at).num_seconds(),
),
});
}
}
}
// Geographic anomaly: foreign-country transaction when we have a
// configured home country that disagrees.
for t in &txs {
let Some(home) = self.customer_home_country.get(&t.customer_id) else {
continue;
};
let Some(tx_country) = t.country.as_ref() else {
continue;
};
if tx_country != home {
out.push(Trigger {
kind: TriggerKind::GeographicAnomaly,
transactions: vec![t.id.clone()],
aggregate_cents: t.amount_cents,
note: format!(
"tx {} in {} for customer based in {}",
t.id, tx_country.0, home.0
),
});
}
}
out
}
}
#[cfg(test)]
mod tests {
use super::*;
use chrono::TimeZone;
fn tx(id: &str, cust: &str, secs: i64, amount: u64, cash: bool, inbound: bool) -> Transaction {
Transaction {
id: id.to_string(),
customer_id: cust.to_string(),
at: Utc.timestamp_opt(1_700_000_000 + secs, 0).single().expect("ts"),
amount_cents: amount,
currency: "USD".to_string(),
is_cash: cash,
inbound,
country: None,
}
}
#[test]
fn ctr_single_threshold() {
let txs = vec![tx("1", "c1", 0, 1_500_000, true, true)];
let triggers = CtrHelper::new().analyze(&txs);
assert!(triggers.iter().any(|t| t.kind == TriggerKind::CtrThreshold));
}
#[test]
fn ctr_structuring_11_deposits() {
// 11 cash deposits of $1000 each, evenly spaced over 24h, same customer.
let mut txs = Vec::new();
for i in 0..11 {
txs.push(tx(
&format!("d{i}"),
"c1",
i as i64 * 3600, // every hour
100_000, // $1000 in cents
true,
true,
));
}
let triggers = CtrHelper::new().analyze(&txs);
assert!(
triggers.iter().any(|t| t.kind == TriggerKind::Structuring),
"expected structuring trigger, got {triggers:#?}",
);
let s = triggers
.iter()
.find(|t| t.kind == TriggerKind::Structuring)
.expect("trigger");
assert!(s.aggregate_cents > CTR_THRESHOLD_CENTS);
}
#[test]
fn sar_round_dollar() {
let txs = vec![tx("1", "c1", 0, 1_000_000, false, true)]; // $10,000
let triggers = SarHelper::new().analyze(&txs);
assert!(triggers.iter().any(|t| t.kind == TriggerKind::RoundDollar));
}
#[test]
fn sar_rapid_in_out() {
let txs = vec![
tx("1", "c1", 0, 1_000_000, false, true),
tx("2", "c1", 60, 950_000, false, false),
];
let triggers = SarHelper::new().analyze(&txs);
assert!(triggers.iter().any(|t| t.kind == TriggerKind::RapidInOut));
}
#[test]
fn sar_geographic_anomaly() {
let mut sar = SarHelper::new();
sar.set_home_country("c1".to_string(), CountryCode("US".to_string()));
let mut t = tx("1", "c1", 0, 100_000, false, true);
t.country = Some(CountryCode("KP".to_string()));
let triggers = sar.analyze(&[t]);
assert!(triggers.iter().any(|t| t.kind == TriggerKind::GeographicAnomaly));
}
}