Chain analytics and risk assessment

1) What is chain analytics in the context of iGaming

• recognize risky patterns (sanctions, mixers, phishing, ranochein mules);
• estimate the proximity/taint% of the origin of funds;
• make RBA decisions on deposits/withdrawals without loss of conversion;
• document the evidence base for audits, banks and regulators.

2) Pipeline architecture (reference)

Collection → Normalization → Graph → Tags/Scoring → Solutions → Reporting

1. Data collection

Nodes/RPC over key networks (TRON, EVM L1/L2, BTC/UTXO, Solana, XRP/XLM, etc.).
Webhooks/mempool wiretaps (where appropriate), periodic backtill for completeness.

2. Normalization

Cast to unified schema: 'tx', 'address', 'entity', 'label', 'edge (from→to, amount, ts, chain)'.
Parsing specifics (memo/tag, UTXO inputs/outputs, internal tx).

3. Entity graph

Clustering of addresses in entity (co-spend/change/temporal heuristics, provider clusters).
Storing multi-chain links (bridge/mint/burn).

4. Attribution and labels

Import of provider labels (exchanges/VASP, mixers, dark markets, scam, sanctions).
Own attribution (service pool addresses, payment providers, internal wallets).

5. Scoring and solutions

Counting risk score 0-100 for address/tx/chain, RBA matrix (allow/limit/hold/reject).

6. Reporting and auditing

Solution logs, tag versions, chain snapshots, artifacts for SAR/STR and controversial cases.

3) Data model and graphs

Key entities

'Address' (over the network), 'Entity' (cluster of addresses), 'Tx', 'Edge', 'Label', 'Case'.
Атрибуты: `chain`, `ts`, `amount`, `counterparty_type` (VASP, mixer, bridge, DEX, P2P, gambling), `risk_vector`.

Indexes and storage

Graph database (or column storage + edge tables).
Indexes on 'address', 'entity _ id', 'label', 'ts', 'chain' for quick traces.

4) Path metrics: proximity and taint

Proximity (hop distance): minimum number of transitions to the risk mark/cluster.
Taint% (share of pollution): the share of funds in transit, originating from "dirty" sources, taking into account branches.
Path score: function of distance, taint and event freshness (time-decay).
Entity confidence: confidence in clustering (heuristics/sources).

5) Feature set for risk assessment

A. Graph

Fan-in/fan-out, medium degree, centrality (betweeness, pagerank).
Share of inputs from exchanges/VASP vs anonymous clusters, bridges.
Density of links with high-risk labels.

B. Behavioral

Periodicity and rhythm of translations, "even" amounts, burst patterns.
Speed-chain: speed through intermediate wallets.
Rapid in → out.

C. Content/Context

Tags: sanctions, mixers, dark market, phishing, ransom, high-risk P2P.
Geo/regional flags (indirectly through exchanges/time zones).
Counterparty type (DEX/bridge vs VASP).

D. Transactional

Networks/fees/confirmation, memos/tags correctness.
Address/wallet age, cluster survivability.

6) Risk rate and calibration (0-100)

score = w1LabelRisk + w2Proximity + w3Taint% + w4Behavior + w5Counterparty + w6TimeDecay

Порог T1 (allow), T2 (hold/verify), T3 (reject/escalate).
Separate profiles by network/asset (UTXO vs EVM vs tag-network).

Calibration

PR/ROC with value weights (false reject vs fraud loss).
Brier score for probability calibration.
Backtesting on historical cases (TP/FP/FN).

7) Matrix of RBA solutions (sketch)

8) Integration with KYT, Travel Rule and KYC/KYB

KYT: complements its own graph (industrial labels, attribution, reports). Log the version of the database and the source of the labels.
Travel Rule: Link IVMS101 messages to 'tx/case'. Pre-KYT before data exchange.
KYC/KYB: associate graph anomalies with the customer/partner profile (PEP, adverse media, geo).

9) UX and operations (minimum friction)

Transparent hold reasons: "You need to confirm the source of funds "/" Confirm ownership of the address."

Whitelist addresses with TTL and KYT thresholds.
Partial release with a partially clean path.
Automatic ETA based on scan time and network.

10) Privacy, data and compliance

PII minimization: separate the online graph from personal data (PII Vault).
Encryption "at rest" and "in transit," RBAC/SoD, signed webhooks.
Artifact versioning: chain snapshots, KYT reports, tag versions at the time of solution.
Retention: storage of case materials according to the rules of jurisdiction (often 5 + years).

11) Observability and dashboards

Operations

Approval Rate of the post-filter, Time-to-Decision p50/p95, Hold %/Reject%.
Peaks by network/asset, RPC degradation/fee.

Risk/quality

KYT hit% by label type, SAR-conversion.
False Positive %, Precision/Recall для High-risk.
Share of proximity≤N and taint% in flows.

Economics

Cost per Approved (all-in),% of manual cases, cost of investigations.

12) Case playbooks (L1/L2/L3)

L1 (triage): checking labels, proximity/taint, matching with client, fast allow/hold.
L2 (investment): in-depth tracing, SoF/SoW, Travel Rule-answer, solution: partial release/decline.
L3 (escalation): sanctions/stolen funds/public incidents, preparation of SAR/STR and regulatory communication.

SLA landmarks: auto-triage 5-15 with p95, L2 up to 4 hours for High, standard ≤ 24 hours.

13) Anti-patterns

Blind faith in "blacklists" excluding chain and taint%.
Same thresholds for all networks/assets and geo.
No versioning of labels/sources → unprotected solutions.
Bridge/L2 and multi-chain transition ignored.
"Deaf" locks without partial release and intelligible communication.
No idempotency in webhooks/solutions → hold/unlock doubles.

14) Implementation checklist (short)

• Nodes/RPC over networks, unified data schema, edge model.
• Clustered and confidence-valued entity graph.
• Import KYT labels + native attribution, versions/sources.
• Attributes: graph/behavior/content/tx; scoring 0-100 s T1/T2/T3.
• RBA matrix and playbooks (allow/limit/hold/reject/escalate).
• Travel Rule (IVMS101) and unhosted policy.
• Dashboards: AR, Time-to-Decision, FP%, SAR, taint/proximity.
• PII Vault, RBAC/SoD, encryption, retention, and auditing.
• Idempotency, anti-takes, backoff + jitter; signed webhooks.
• Regular calibration of thresholds, retrospective of lost cases.

15) Summary

Chain analytics is not just "transaction viewing," but a system of graph, labels and solutions built into payment transactions. Connect a complete proximity/taint with KYT/Travel Rule and RBA matrices, draw up evidence and quality metrics, keep privacy under control - and you get fast, compliant and cost-effective payment processes in iGaming.