Fraud & Risk Intelligence
See the exposure screening can’t.
Sanctions and watchlist screening catches entities that are on a list. Arango catches the ones connected to them — through ownership, control, or family ties — by computing transitive risk across the graph in a single query, with the exact path as auditable evidence.
Value Drivers
What Arango risk intelligence delivers
01
See indirect exposure others miss
Screening flags entities on a list. Arango surfaces counterparties connected to sanctioned entities through ownership, control, or family — the risk that lives in the path.
Catch the “Shell Game”
02
Risk as a single query
One AQL traversal walks 1–3 hops, multiplies propagation weights, and sums exposure per sanctioned terminal — no separate scoring service.
Answers in tens of ms
03
Auditable by design
Every score returns the exact, named path that produced it — the chain of evidence a regulator or SAR filing will ask for.
Explainable · reproducible
04
One engine, one source of truth
Documents, graph, and ontology share one query context. Change a policy weight with one line — no redeploy, no stale copies, no wrong answers.
Policy = data, not code
Based on Arango’s open-source risk-intelligence system (Sentries) using the OFAC SDN list (~18,500 entities); illustrative.
The Opportunity
Why it matters
Sanctions screening checks ~18,500 OFAC SDN records — and clears any counterparty that isn’t itself on the list. Arango’s risk-intelligence approach computes transitive risk across ownership, control, and family ties in a single AQL traversal — surfacing the sanctioned entity three hops away, in tens of milliseconds, with the exact path as auditable evidence. The same engine powers DoD vendor vetting, AML/KYC ultimate-beneficial-owner roll-ups, and supply-chain risk.
3 hops
hidden exposure surfaced
tens of ms
per-counterparty risk query
1 query
documents + graph + ontology
Every path
auditable by name
The takeaway: a sanctions list tells you who’s on it. A graph tells you who’s one degree away — and the underwriting decision lives in that gap.
How it Works
The Shell Game: risk lives in the path
A list-based screen sees four clean nodes and clears the counterparty. One AQL traversal multiplies the ownership weights and surfaces the sanctioned entity three hops away — and returns the exact path as evidence.
Inferred risk = 1.0 × 1.0 × 1.0 = 1.0 → DECLINE.
A list-based screen would clear this counterparty. The path is the auditable evidence.
The Matrix
From risk challenge to measurable value
| Risk & fraud challenge | Arango Contextual Data Platform | Value · KPI / OKR |
|---|---|---|
| Watchlist screening only catches entities on the list | AQL traversal computes transitive risk across ownership, control & family ties | Surface indirect exposure · catch the Shell Game |
| The risk lives in the path, not in any single node | Path-product aggregation: multiply propagation weights along each path, sum per terminal | Inferred-risk score per counterparty |
| Split stacks (search + DB + graph + app) drift & hard-code weights | Documents, property graph & OWL ontology in one AQL query context | Correct risk · no stale copies |
| Regulators demand the chain of evidence (SAR / audit) | Every score returns the exact, named path that produced it | Auditable · reproducible |
| Policy changes mean redeploying scoring code | Propagation weights stored on edges as data — one-line AQL update | Policy = data · no redeploy |
| Analysts, auditors & AI agents use different tools | The 5-step toolset is stored in the database — same tools, same answers | One source of truth · agent-ready |
The Shift
Before and after Arango
Before
List-based Screening
After
Arango Risk Graph
Outcome
Catch hidden exposure
Explainable scores
No split-stack drift
Faster, defensible onboarding decisions
The risk isn’t on the list. It’s in the path.
Bring your counterparty data and watchlists — and trace transitive risk across ownership, control, and family ties, with every path auditable by name.