Statement Analysis
Analyze Bank Transactions with Contextual Insight
Process and interpret customer bank statements in JSON, CSV, or PDF formats. Extract key financial metrics, detect inflows/outflows, categorize spending, and surface behavioral insights.
Key Use Cases:
Verify Salary Earners: Confirm income consistency, identify employer names, and detect salary patterns.
Assess Financial Health: Analyze income-to-expense ratios, recurring obligations, and financial stability.
Detect Risk Indicators: Identify early warning signs such as bounced transactions, high-frequency gambling activity, or suspicious fund movements—like frequent account sweeping—to proactively assess credit risk.
Automated Decisioning
Configure Rules and Build Scorecards for Instant Credit Decisions
Create and manage decisioning logic that automates the approval or rejection of loan applications. With Decide, you can define objective, data-driven criteria based on financial behavior, income consistency, spending habits, and more—ensuring a fast, consistent, and transparent credit evaluation process.
Scorecard Types:
Rule-Based Scorecards
A binary evaluation model that checks whether an applicant passes or fails predefined rules. Ideal for quick eligibility screening.Weighted Scorecards
A scoring model that assigns weights to multiple financial and behavioral factors to generate a composite score—similar to a credit score. Useful for more nuanced credit decisions.
Use Case Highlights:
Automate credit decisions using rule-based or weighted scorecards
Tailor logic to specific product types or customer segments
Run scorecards programmatically via API or directly from the dashboard
Spool Data & Alternative Data Sources
Pull Rich Financial & Behavioral Data Instantly
Access traditional and alternative data sources to deepen your customer understanding and improve credit assessments.
Available Data Streams:
Bank Statement Data (via consented open banking)
Credit Bureau Data: Existing obligations, repayment history, credit scores
Use Case Highlights:
Combine multiple data types for a 360° customer view
Enhance scoring models with credit bureau data
Identify fraud or data inconsistencies across channels