AI-Powered Financial Intelligence.
Machine learning woven into every SpacePe module - not a bolt-on. Cash flow prediction, anomaly detection, smart bank routing, auto-categorization, invoice OCR, fraud scoring, and a conversational finance assistant.
Key Features
Cash Flow Prediction Engine
Ensemble ML model (XGBoost + LSTM) trained on your historical transactions predicts cash inflows/outflows at 7, 14, 30, and 90 day horizons. Factors: seasonality, payment day patterns, invoice aging curves, recurring obligations, and upcoming payables. Accuracy improves with each month of data. Confidence intervals on every prediction.
Real-Time Anomaly Detection
Isolation Forest + statistical models detect unusual patterns in real-time: unexpected large transactions (3σ+ deviation), new beneficiary receiving bulk transfers, off-hours activity (late night payment initiation), velocity spikes (10x normal txn count), geographic impossibility, and amount round-number patterns. Auto-alert + configurable auto-hold.
Smart Bank Routing (AI-Optimized)
Multi-armed bandit algorithm selects optimal bank and payment rail per transaction. Factors: real-time cost per rail (₹0.5-₹7), estimated processing speed, rolling 1-hour success rate per bank, current bank queue depth, and your routing preferences. Saves 15-25% on payment processing costs at scale.
Transaction Auto-Categorization
BERT-based NLP model achieves 95%+ accuracy categorizing transactions: vendor payments, salary, tax (GST/TDS/advance tax), utilities, rent, subscriptions, reimbursements, inter-company transfers. Learns from your corrections. Supports custom categories. Processes 10K+ txns/second.
Invoice Intelligence (OCR + NLP)
Computer vision + NLP pipeline extracts from any invoice format (PDF, image, email): vendor name, GSTIN, line items, amounts, tax breakdowns, due date, bank details, and PO reference. Auto-match to purchase orders. Flag discrepancies (amount mismatch, duplicate invoice number, expired GSTIN). 98% extraction accuracy.
Fraud Scoring Engine
Real-time fraud score (0-100) on every transaction. Features: beneficiary risk profile, transaction velocity, device fingerprint, IP geolocation, time-of-day pattern, amount deviation, and network graph analysis (connected beneficiaries). Scoring latency <50ms. Configurable thresholds per transaction type.
Vendor Intelligence
ML profiles your vendor relationships: payment reliability (on-time vs late), price trend analysis (are they increasing rates?), spend concentration risk (too dependent on one vendor?), duplicate vendor detection (same bank account, different names), and optimal payment timing recommendations.
Budget vs Actual Forecasting
Compare budget allocations against AI-predicted actuals. Early warning when a department is trending to overspend. Scenario modeling: 'What if revenue drops 20%?' or 'What if we delay vendor payments by 15 days?' Cashflow impact simulation.
Conversational Finance Assistant
Ask SpacePe in plain English: 'What's my cash position across all banks?', 'Show overdue invoices above ₹1L', 'Compare this month's expenses to last month', 'Which vendors are we overpaying?'. Natural language → SQL → visualization. Available via dashboard, Slack, and WhatsApp.
Custom ML Model Training
For enterprise clients: train custom models on your data for specific use cases - credit risk scoring, churn prediction, revenue forecasting, or industry-specific categorization. Models deployed on SpacePe's inference infrastructure. DPDP-compliant data handling.
[ Integrated with India's Leading Banks ]
★ Deep Integration Partners - Direct API connectivity
How It Works
Financial data flows through SpacePe
12 ML models analyze in parallel
Cash flow predictions updated daily
Anomalies flagged in real-time (<1 sec)
Bank routing optimized per transaction
Transactions auto-categorized (95%+)
Invoices auto-parsed via OCR/NLP
Fraud scored in <50ms
Insights surfaced in dashboard + Slack
Assistant answers natural language queries