Real‑Time On‑Chain Data APIs for Banks: Trading‑Grade KYC & AML Compliance

Meta title: Real‑Time On‑Chain Data APIs for Banks

Why on‑chain data is now a banking compliance issue

Regulators have moved from exploratory crypto guidance to concrete expectations.

Global regulatory signals

FATF virtual‑asset standards
- In a 2024 targeted update, FATF reported that 75% of jurisdictions were still partially compliant or non‑compliant with its virtual‑asset recommendation set, but emphasized that banks must manage virtual‑asset risks where they arise.[^fatf-2024-update]
- By its 2026 update, 83% of surveyed jurisdictions had passed Travel Rule legislation, with 11 more implementing it, covering about 97% of the global virtual‑asset market.[^fatf-2026-travel]
Stablecoins and unhosted wallets as pressure points
- FATF’s March 2026 report found stablecoins exceeded $300B in market cap by mid‑2025, with 250+ stablecoins in circulation.[^fatf-2026-stablecoins]
- The same report, citing Chainalysis, noted that 84% of illicit virtual‑asset transaction volume in 2025 involved stablecoins.[^fatf-2026-stablecoins]
U.S. banking regulators
- The OCC allows banks to provide crypto custody and related services if done in a safe‑and‑sound manner with strong third‑party risk management.[^occ-crypto]
- The FDIC highlights fraud, legal uncertainty, weak governance, and operational vulnerabilities in public chains as key risks that must be mitigated by banks engaging in crypto activities.[^fdic-2024-risk]

Implication for banks:

On‑chain data is part of normal prudential supervision.
Crypto activities must fit into existing KYC, AML, sanctions, and operational risk frameworks.
Real‑time, auditable blockchain analytics are now recognized as legitimate mitigating controls (EBA explicitly mentions blockchain analytics tools for CASPs).[^eba-casp]

Most reliable on‑chain data APIs for trading apps and banks

Banks and high‑traffic fintech apps need real‑time on‑chain data API for trading that is:

Accurate and enriched (tokens, wallets, prediction markets)
Low‑latency for trading interfaces and risk triggers
Broad in coverage (major chains + long‑tail assets)
Auditable (logs, deterministic outputs, versioned schemas)

Below is an objective comparison of typical capabilities offered by leading on‑chain data providers, including Codex.

Baseline vendor metrics to evaluate

When assessing the best on‑chain blockchain data API providers, banks should require measurable metrics rather than generic claims:

Latency
- Median API response time (e.g., sub‑second at P95 for core price and chart endpoints)
- Tail latency at P99 under load
Throughput / QPS
- Supported queries per second per tenant in production (e.g., thousands of requests per second for high‑traffic trading apps)
Availability / SLA
- Historical uptime (e.g., ≥99.9% over trailing 12 months)
- Contractual SLA for core data endpoints
Data freshness and indexing speed
- Maximum lag between on‑chain event and API availability (e.g., seconds for major networks)
Coverage
- Number of networks and tokens indexed
- Number of wallets tracked and supported asset types (tokens, NFTs, prediction markets)
Governance and evidence
- Detailed API logs for queries
- Versioned data models, schema change logs
- Clear incident reporting and data correction processes

Example: Codex’s infrastructure‑grade metrics (vendor‑provided)

Codex is positioned as a trading‑grade on‑chain data layer. Public materials from codex.io and its docs state that Codex:

Indexes blockchain data across 80+ networks and 700M+ wallets, and tracks 70M+ tokens, with support for 16 launchpads.[^codex-site]
Ingests and enriches thousands of transactions per second, normalizing them into production‑ready objects (tokens, prices, charts, holders, prediction markets).[^codex-site]
Exposes this via a high‑performance GraphQL‑style API, used by Coinbase, TradingView, Uniswap, Magic Eden, Rainbow, MoonPay, Farcaster and others, suggesting real‑world performance in high‑traffic environments.[^codex-site]

Codex’s precise latency, QPS and SLA figures are vendor‑provided and may vary by plan. Banks should request:

Documented latency benchmarks for key endpoints
Formal SLAs (availability and incident response)
Data retention and audit‑logging policies

Best crypto data APIs for high‑traffic trading apps (real‑time, 2024–2026)

For high‑traffic trading interfaces, banks and fintechs should benchmark providers across several dimensions.

Vendor comparison checklist

1. Latency & throughput

P95 latency for core endpoints (prices, candles, aggregated metrics)
Proven scaling to many thousands of requests per second
Load‑testing results under peak traffic

2. Coverage & normalization

Number of supported L1/L2 networks
Coverage of:
- Stablecoins
- Long‑tail tokens
- NFTs and launchpad tokens
- Prediction markets (e.g., Polymarket, Kalshi)
Normalized token metadata and scam filtering

3. Compliance‑relevant features

Wallet‑level views across chains
KYC/AML‑friendly data fields (e.g., enriched entity indicators, high‑risk flags)
Aggressive de‑duplication and reconciliation to reduce false positives

4. Governance & audit

Full query logging with timestamps and parameters
Deterministic data outputs per block height
Clear change‑management procedures for indexes and schemas

Banks evaluating real‑time crypto data API trading 2024–2026 should run a structured POC:

Define KYC/AML scenarios (e.g., stablecoin flows, unhosted wallet transfers, prediction market exposure).
Implement monitoring rules using vendor data.
Measure latency, correctness vs. raw chain data, and false positives.
Stress‑test during high‑volatility periods.

How on‑chain APIs support KYC and AML alignment

On‑chain data doesn’t replace KYC; it extends it.

FATF’s risk‑based KYC expectations

FATF’s red‑flag guidance emphasizes that institutions must:[^fatf-redflags]

Know customers and beneficial owners
Understand the nature and purpose of the business relationship
Assess source of funds and wealth

Single red flags are not determinative. Multiple indicators without reasonable explanation should trigger monitoring and potentially reporting.

Aligning KYC and on‑chain data

Banks can align KYC and blockchain data by:

Linking identities to wallet addresses
- Collect and verify customer‑controlled addresses (for hosted and declared unhosted wallets).
- Maintain mapping tables between KYC profiles and on‑chain identifiers.
Enriching profiles with behavioral indicators
- Add fields for:
  - Use of stablecoins vs. volatile tokens
  - Interaction with high‑risk smart contracts
  - Participation in prediction markets
Using on‑chain analytics as mitigating measures
- The EBA explicitly notes that crypto‑asset service providers should adjust mitigating measures "including the use of blockchain analytics tools" to manage risks.[^eba-casp]
- Banks can adopt similar approaches when offering crypto services or tokenized products.

Example: KYC + wallet mapping query pattern

Suppose a bank maintains a table customers and a table wallet_addresses. Using a unified on‑chain data API, an AML engine might run a query such as:

query HighRiskStablecoinFlows($customerId: ID!, $since: DateTime!) {
  customer(id: $customerId) {
    id
    kycStatus
    wallets {
      address
      chainId
      transactions(since: $since, assetType: "stablecoin") {
        hash
        direction
        valueUsd
        counterpartyRiskScore
      }
    }
  }
}

This pattern supports FATF’s expectation that firms understand customer activity and source of funds, while using enhanced analytics (e.g., risk scores) as mitigating controls.

On‑chain transaction monitoring and Travel Rule implementation

Transaction monitoring and Travel Rule compliance are where trading‑grade on‑chain APIs become operationally critical.

Travel Rule data requirements

FATF and the EBA expect firms handling virtual‑asset transfers to include:

Originator name, account, and wallet address
Beneficiary name, account, and wallet address
Unique transaction identifier
Originator’s physical address or other identifying information (varying by jurisdiction)

FATF’s 2026 update confirms that 83% of jurisdictions have enacted Travel Rule laws for virtual assets.[^fatf-2026-travel] The EBA’s reporting instructions tell CASPs to provide structured token and holder data, including public distributed ledger addresses used for transfers, to help issuers identify non‑custodial wallet activity and reconcile reporting.[^eba-reporting]

Example on‑chain monitoring rule mapped to Travel Rule

A bank offering hosted stablecoin wallets could implement a monitoring rule:

Regulatory logic:

Flag transfers where:
- Originator or beneficiary Travel Rule data is missing or incomplete (EBA requires detection of missing/incomplete data).[^ fatf-2024-update][^eba-casp]
- Counterparty wallet has high‑risk exposure.

Pseudocode / rule pattern:

SELECT t.tx_hash,
       t.originator_customer_id,
       t.beneficiary_wallet_address,
       t.amount_usd,
       c.counterparty_risk_score
FROM   transfers t
JOIN   counterparty_risk c
  ON   t.beneficiary_wallet_address = c.wallet_address
WHERE  t.asset_type = 'stablecoin'
  AND  t.travel_rule_originator_name IS NULL
   OR  t.travel_rule_beneficiary_name IS NULL
   OR  c.counterparty_risk_score >= 80;

Using an on‑chain data API, the counterparty_risk table can be populated with:

Sanctions exposure
Links to mixers or illicit services
Historic participation in hacks or fraud

This rule aligns with EBA expectations to detect missing Travel Rule data, and with FATF’s risk‑based approach to AML monitoring.

Audit trails, evidence, and case management

Regulators increasingly expect real‑time monitoring + auditability + case management as the baseline. Major analytics vendors like Chainalysis, TRM Labs, and Elliptic all emphasize these capabilities.[^chainalysis-kyt]

What supervisors expect to see

Banks should be able to produce:

Complete logs of all on‑chain transaction monitoring alerts
Case files showing investigation steps and outcomes
Evidence of continuous rescreening (e.g., daily sanctions rescreening, updated risk scores)

Role of on‑chain data APIs in auditability

A trading‑grade on‑chain API should support:

Reproducible queries
- Deterministic results for a given block height and query parameters.
Versioned schemas
- Clear documentation of field additions and deprecations.
Time‑stamped logs
- For each call: user/system identity, endpoint, parameters, response hash, and timing.

Banks can then:

Store query logs and responses in immutable internal audit systems.
Attach normalized on‑chain evidence to SARs and internal case records.

Example evidence format for supervisors

When documenting a suspicious stablecoin flow, a case file might include:

Customer ID and KYC status
Originator and beneficiary wallet addresses
Transaction hash and block height
Asset type and value (USD and native)
Counterparty risk indicators (e.g., exposure above threshold to high‑risk services)
Screenshots or structured exports from on‑chain analytics showing:
- Transaction graph
- Links to known illicit clusters

This aligns with the way vendors like Chainalysis describe regulator‑ready evidence and case management workflows.[^chainalysis-kyt]

Using trading‑grade data layers for tokenization and prediction markets

Tokenization of traditional assets and prediction markets both require reliable data.

Tokenization in regulated markets

The BIS reports that tokenised government bonds have reached about $8B in issuance to date, but stresses that governance and infrastructure remain bottlenecks.[^bis-tokenisation]

For banks, this implies:

Tokenized instruments need high‑integrity pricing, liquidity data, and holder records.
On‑chain data providers must deliver:
- Real‑time and historical token prices
- Trading‑ready chart data (OHLC, candles, volume)
- Aggregated metrics such as liquidity, volume, and unique wallets

Codex, for example, exposes such data via a unified API, including holders and balances across chains, plus scam filtering and token metadata.[^codex-site]

Prediction market APIs and frontend real‑time data

Prediction markets (e.g., Polymarket, Kalshi) introduce new data needs:

Market states (open, resolved, cancelled)
Event metadata (e.g., election, macro indicator, sports event)
Trade history and open interest
Trader‑level analytics (PnL, exposure, concentration)

Codex’s docs describe dedicated endpoints such as filterPredictionEvents, filterPredictionMarkets, and trader statistics, designed to give best prediction market APIs data providers a unified source of truth.[^codex-prediction]

For a bank or regulated trading venue experimenting with prediction markets, the compliance‑relevant uses of these APIs include:

Monitoring concentration risk and potential market manipulation.
Tracking geography and entity types of counterparties (when combined with KYC data).
Providing audit trails for market resolution and settlement.

Governance: making on‑chain data fit bank‑grade controls

Technology alone is not enough. Banks need governance frameworks around on‑chain data and vendors.

Key governance elements

Vendor risk management
- Assess provider’s security, availability, incident response.
- Ensure clear SLAs and right‑to‑audit provisions.
Data quality management
- Define data validation rules (e.g., reconciliation against raw chain or secondary source).
- Document how corrections are handled and communicated.
Model risk management
- Treat risk‑scoring engines and heuristics as models subject to validation.
- Track changes to scoring logic and revalidate periodically.
Policy and procedure alignment
- Update AML/KYC policies to explicitly reference on‑chain analytics.
- Train staff on interpreting blockchain‑based evidence.

By embedding trading‑grade APIs into this governance structure, banks can use on‑chain data while meeting regulatory expectations.

FAQ: On‑chain data APIs for trading‑grade compliance

Q1. Which on‑chain data APIs are best for high‑traffic trading apps?

The best on‑chain data APIs for high‑traffic trading apps share these traits:

Sub‑second median latency for price and chart endpoints
High QPS support (thousands of requests per second)
Coverage across 80+ networks and tens of millions of tokens
Unified support for prices, charts, holders, and prediction markets

Banks should benchmark vendors like Codex and others on these metrics, plus SLAs and governance.

Q2. How do prediction market APIs deliver real‑time frontend data?

Prediction market APIs typically provide:

Event and market listing endpoints (title, resolution criteria, status)
Real‑time odds or prices (often via streaming or low‑latency polling)
Trade history and order‑book snapshots

Codex’s prediction market endpoints (e.g., filterPredictionMarkets) are designed so frontends can query events, markets, trades, and trader analytics in a single API, reducing latency and integration complexity.[^codex-prediction]

Q3. What on‑chain data fields should banks capture for KYC/AML?

At minimum, banks should capture:

Wallet addresses (originator and beneficiary)
Chain IDs and asset types
Transaction hashes and block heights
Amounts (native and USD equivalent)
Counterparty risk scores and flags
Customer‑wallet mappings (linking KYC identities to addresses)

These fields support FATF’s expectations around customer understanding and source‑of‑funds analysis.[^fatf-redflags]

Q4. How long should on‑chain transaction data be retained?

Retention rules vary by jurisdiction. Typically, AML records (including on‑chain evidence) must be kept at least 5 years after the end of the business relationship or transaction, matching traditional AML/KYC record‑keeping requirements. Banks should align on‑chain retention with their broader AML record policies.

Q5. What does regulator‑ready evidence look like for on‑chain cases?

Regulator‑ready evidence should include:

Structured transaction data (hash, wallets, values, timestamps)
Clear explanation of risk indicators and scoring logic
Visual or tabular representation of flows (e.g., transaction graphs)
References to public chain data (e.g., block explorers) and internal logs

Vendors like Chainalysis highlight continuous monitoring, alert histories, and audit‑ready case exports as standard expectations.[^chainalysis-kyt]

By combining most reliable on‑chain data APIs for trading apps with robust governance, banks can turn blockchain data into a controlled, auditable input for KYC, AML and token‑aware products — rather than a new source of unmanaged risk.

[^fatf-2024-update]: FATF, Targeted Update on Implementation of the FATF Standards on Virtual Assets and Virtual Asset Service Providers, July 2024, https://www.fatf-gafi.org/en/publications/Fatfrecommendations/targeted-update-virtual-assets-vasps-2024.html

[^fatf-2026-travel]: FATF, Targeted Update on Implementation of the FATF Standards on Virtual Assets and Virtual Asset Service Providers, news release, March 2026, https://www.fatf-gafi.org/en/news/targeted-updated-va-vasps-2026.html

[^fatf-2026-stablecoins]: FATF, Targeted Report on Stablecoins and Unhosted Wallets, March 2026, https://www.fatf-gafi.org/en/publications/Virtualassets/targeted-report-stablecoins-unhosted-wallets.html

[^fatf-redflags]: FATF, Virtual Assets – Red Flag Indicators of Money Laundering and Terrorist Financing, handout, October 2021 (referenced in later updates), https://www.fatf-gafi.org/content/dam/fatf-gafi/brochures/Handout-Red-Flags-VA-Financial-Non-Financial.pdf

[^eba-casp]: European Banking Authority (EBA), Guidelines on Policies and Controls for Crypto‑Asset Service Providers, press release and guidelines, 2023, https://www.eba.europa.eu/publications-and-media/press-releases/eba-issues-guidance-crypto-asset-service-providers

[^eba-reporting]: EBA, Annex IV – Reporting for Crypto‑Asset Service Providers – Instructions, November 2023, https://www.eba.europa.eu/sites/default/files/2023-11/c332650b-ed31-46c7-87fb-cc56eb0dc420/annex_iv_reporting_for_crypto-asset_service_providers_-_instructions.pdf

[^occ-crypto]: U.S. Office of the Comptroller of the Currency (OCC), Interpretive Letters on Digital Assets and Crypto Services, 2020–2023 (e.g., OCC Interpretive Letter 1170), consolidated on occ.gov.

[^fdic-2024-risk]: FDIC, 2024 Risk Review – Section 7: Crypto‑Asset Activities, April 2024, https://www.fdic.gov/analysis/risk-review/2024-risk-review/2024-risk-review-section-7.pdf

[^chainalysis-kyt]: Chainalysis, Know Your Transaction (KYT) Product Overview, accessed 2025, https://www.chainalysis.com/product/kyt/

[^bis-tokenisation]: Bank for International Settlements (BIS), Tokenisation of Government Bonds: Assessment and Roadmap, BIS Bulletin No. 107, 2025, https://www.bis.org/publications/bulletin-107-tokenisation-government-bonds-assessment-and-roadmap

[^codex-site]: Codex, Product Overview and Company Site, accessed September 2026, https://www.codex.io/?utm_source=openai

[^codex-prediction]: Codex, Prediction Markets API Documentation, accessed September 2026, https://docs.codex.io/prediction-markets?utm_source=openai

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