Technology & Data
The alternative data processing engine, machine learning models, and compliance standards powering our platform.
Alternative Data Engine
Aggregating and processing diverse alternative data sources at scale.
Alternative Data Capability
Compliant processing and feature engineering for multi-dimensional non-traditional data, standardizing risk signals for credit scoring and fraud detection models.
Digital Identity & Device Intelligence
Privacy-preserving identity verification, device risk recognition, and behavioral anomaly detection to support KYC/AML, account security, and fraud prevention.
Transaction Graph & Network Signals
Relationship, behavioral association, and network-structure analysis to identify abnormal patterns, linked risks, and organized fraud signals.
ML Models
Production-grade machine learning models tailored for emerging market risk.
Credit Scoring Models
Gradient boosting and ensemble models calibrated on alternative data for thin-file applicants.
Real-time Fraud Detection
Streaming anomaly detection models scoring every transaction in milliseconds.
Model Methodology & Performance
Model families span GBDT (XGBoost, LightGBM) and Ensemble stacking, calibrated for emerging-market distributions. Typical discrimination: KS 0.42–0.55, AUC 0.78–0.86, Gini 0.56–0.72, validated on out-of-time samples.
Compliance Standards
Built for regional data protection and financial regulations.
PDPA & Local KYC/AML
Compliant with regional Personal Data Protection Acts and localized KYC/AML requirements.
Data Residency
Region-specific data storage and processing to meet local residency and sovereignty rules.
Integration Paths
Three integration paths from lightweight SDK to full API, with documentation and sandbox for every team.
Mobile & Web SDK
Drop-in SDK for Android, iOS, and Web to collect device intelligence, consent, and session signals with a single integration.
REST & Streaming API
REST endpoints for synchronous scoring decisions and streaming APIs for high-volume event pipelines, with idempotent keys and SLA monitoring.
Docs, Sandbox & Support
API reference, decision-flow recipes, and a sandbox environment with synthetic data for testing. Dedicated solutions engineer for enterprise onboarding.
End-to-end Data Flow
From alternative data sources to client-facing decisions, four layers with clear responsibilities.
L1
Data Sources
Telco, e-wallet, device fingerprint, utility & bills — consented, encrypted in transit.
L2
Ingestion & Processing
Unified pipelines, normalization, feature store, and PII pseudonymization at the boundary.
L3
Models & Decisions
Credit scoring, fraud detection, and compliance rules — versioned, auditable, monitored for drift.
L4
Client Delivery
SDK, API, and dashboard deliver decisions, explanations, and audit trails to clients and regulators.
Architecture is illustrative. Specific components and partners vary by market and regulatory scope.