[Private Access / Q1 2026]

Credit Layer for Web3

Transforming blockchain data into standardized risk metrics, credit scores, and behavioral insights for financial institutions.

0-1000 Credit Score Range

6+ API Endpoints

Real-time Data Processing

Risk: f(wallet) → [0, 1000] ⊂ ℜ.

Analysis: ∫ transactions → PnL ⊕ fraud ⊕ behavior.

API: λ wallet → {score, history, flags, metrics}.

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Our risk Intelligence engine.

Private Access / Q1 2026

Use Cases

Who benefits

Risk intelligence infrastructure designed for businesses that need to understand, quantify, and act on on-chain wallet behavior patterns.

Lending Protocols

Assess borrower creditworthiness based on historical on-chain behavior, trading performance, and risk patterns.

Online Gambling

Identify high-risk players, detect fraud patterns, and implement responsible gaming measures with behavioral analysis.

Exchanges

Enhanced KYC/AML with wallet reputation scoring, cluster analysis, and real-time risk monitoring.

Payment Processors

Risk-based transaction routing, fraud prevention, and merchant risk assessment using wallet history.

Token Issuers

Analyze holder distribution, identify whale clusters, and detect potential market manipulation patterns.

Insurance Protocols

Underwriting based on wallet risk profiles, claims fraud detection, and portfolio risk assessment.

Credit Scoring

Risk quantification

FICO-like credit scoring system adapted for on-chain behavior analysis, providing standardized risk assessment across all wallet types and trading patterns.

Score ranges

800-1000

Minimal risk

Excellent credit history with consistent positive behavior.

600-799

Low risk

Good track record with minor risk indicators.

400-599

Moderate risk

Average behavior with some concerning patterns.

200-399

High risk

Poor history with significant risk factors.

0-199

Critical risk

Very poor behavior or association with malicious activity.

Score components

Payment history 35%

Transaction consistency and reliability patterns.

Portfolio diversity 25%

Asset distribution and concentration risk.

Trading performance 20%

PnL, win rate, and risk-adjusted returns.

Risk management 15%

Position sizing and loss mitigation behavior.

Activity consistency 5%

Regular engagement and account age.

Architecture

Data model

Multi-layer architecture designed for flexibility, scalability, and real-time analytics, enabling seamless data flow from raw transactions to actionable risk scores.

Raw Data

Transaction History

Complete transaction history stored as the source of truth. Every swap, transfer, and interaction captured with full context for accurate metric computation.

Full transaction details Token transfers & swaps Program interactions Historical preservation

Computed Metrics

Aggregated Analytics

Pre-computed metrics using advanced time-series analytics. Continuous aggregation ensures instant access to complex calculations without query-time overhead.

PnL calculations Win rate & ROI Volume analytics Time-windowed stats

Risk Scores

Credit Intelligence

Standardized risk scores derived from behavioral patterns. Real-time materialized views enable instant score retrieval with automatic updates as new data arrives.

Credit score (0-1000) Risk categories Behavioral flags Confidence levels

Behavioral Patterns

Advanced Analysis

Deep behavioral analysis including cluster membership, trading patterns, and social graph connections. Identifies whales, smart money, and suspicious actors.

Cluster analysis Trading patterns Social graph Anomaly detection

Capabilities

Real-time intelligence

Advanced analytics infrastructure powering instant risk assessment with continuous data processing, pre-computed metrics, and sub-millisecond query response times.

Continuous Aggregation

Metrics computed incrementally as new transactions arrive. No batch processing delays—scores update in real-time.

Time-Series Analytics

Native support for time-bucketed analysis. Track behavior changes over hours, days, or months with optimized queries.

Materialized Views

Pre-computed results for complex queries. Sub-millisecond response times for credit score lookups.

Window Functions

Rolling averages, cumulative sums, and percentile rankings calculated efficiently across transaction history.

Compression & Retention

Automatic data compression for historical records. Configurable retention policies balance storage costs with analysis depth.

Hypertables

Automatic partitioning by time enables efficient queries across billions of transactions without manual sharding.

REST API

Integration

Simple, powerful REST API for seamless risk intelligence integration into your existing applications, workflows, and decision-making processes.

GET /wallets/{address}/score

Retrieve credit score and risk metrics.

Response

{
  "credit_score": 504,
  "risk_category": "moderate",
  "win_rate": 0.65,
  "total_realized_pnl_usd": 12500
}

GET /wallets/{address}/tokens

Token-level metrics and holdings.

Response

{
  "tokens_traded": 47,
  "active_positions": 12,
  "concentration_risk": 0.23
}

GET /wallets/{address}/activity

Historical activity timeline.

Response

{
  "days_active": 180,
  "first_transaction": "2024-01-15",
  "total_trades": 1250
}

POST /wallets/{address}/analyze

Trigger deep analysis for a wallet.

Response

{
  "analysis_id": "abc123",
  "status": "processing",
  "estimated_time": "30s"
}

GET /analysis/{id}

Check analysis status and results.

Response

{
  "status": "completed",
  "score": 687,
  "flags": [
    "whale",
    "smart_money"
  ]
}

GET /wallets/{address}/flags

Behavioral flags and warnings.

Response

{
  "flags": [
    "high_volume_trader"
  ],
  "warnings": [],
  "clusters": [
    "$ARITECT Top Holders"
  ]
}

Behavioral Flags

Risk indicators

Automated detection of behavioral patterns and risk signals, identifying whales, smart money, fraud indicators, and suspicious activity clusters.

Positive Indicators

whale

Large holder with significant portfolio.

smart_money

Consistent profitable trading patterns.

top_holder

Member of top holder clusters.

early_adopter

Early participation in successful projects.

Risk Indicators

phishing

Associated with known phishing addresses.

rugpull

Participation in rug pull schemes.

wash_trading

Artificial volume generation detected.

sybil

Part of coordinated wallet cluster.

Behavioral Patterns

high_frequency

Unusually high transaction frequency.

dormant

Extended period of inactivity.

concentrated

High concentration in single asset.

volatile

Erratic trading behavior.

Access

Get started

Multiple ways to access Akira risk intelligence infrastructure, from quick Telegram checks to full enterprise API integration with SLA guarantees.

Telegram Mini App

Q1 2026

Analyze any wallet directly in Telegram. Perfect for quick checks and individual assessments.

Private API

Q1 2026

Full API access for top 20 $AKIRA token holders. Enterprise-grade integration for your applications.

Enterprise

Q2 2026

Custom integration, dedicated support, and SLA guarantees for institutional clients.

Ready to quantify risk?

Join the waitlist for early access to Akira risk intelligence infrastructure.

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