At Neurelic Labs, our Data Science & Predictive Modeling service enables fintech platforms, brokerages, and trading firms to transform raw datasets into actionable foresight. From customer behavior insights to real-time trade analytics, we help you extract clarity from complexity using advanced machine learning, time-series modeling, and domain-specific AI logic.
Whether you’re forecasting market volatility, scoring credit risk, or optimizing user engagement — we design scalable, regulatory-aligned models that plug directly into your analytics stack or trading workflows.
Our Predictive Modeling solutions are purpose-built for financial and trading ecosystems. We begin by auditing your available data, identifying patterns, and building custom ML models that are explainable, secure, and outcome-oriented.
From fraud detection to revenue projection, churn analysis to demand forecasting, we make data science accessible — and truly impactful.
Time-series market modeling
Churn & behavior prediction
Cross-sell & upsell scoring
Algorithmic risk stratification
Real-time ML for order execution
It’s the process of applying historical and real-time data to forecast future events — such as trade activity, fraud, or user behavior. We train supervised/unsupervised models tailored to your goals.
We co-architect pipelines for data ingestion → feature engineering → model training → deployment (dashboard/API). Each model is tested for accuracy and monitored post-deployment.
We use SHAP, LIME, and internal review frameworks to ensure models are interpretable and audit-ready — crucial for regulated fintech environments.
Both. Startups can begin with Essentials tier to validate use cases. Larger clients can scale across business units, supported by our MLOps stack and cloud-native deployments.
