Lending

Credit Assessment

Banking Data-Driven Credit Assessment API

Credit scores provide limited insight into actual financial behavior. Fiskil's credit assessment analyzes real banking transactions to evaluate creditworthiness based on income stability, spending patterns, and cash flow management.

Credit Scores Miss the Full Picture

Traditional credit scoring relies on past credit behavior but ignores current financial health and cash flow.

  • Credit scores don't reflect current income or employment

  • Thin credit files prevent assessment of creditworthy customers

  • No visibility into cash flow management and financial behavior

  • Can't assess gig workers or recent immigrants with limited credit history

  • Static scores don't capture recent financial improvements

Comprehensive Financial Behavior Analysis

Analyze real banking transactions to assess credit risk based on income, spending, savings, and financial management.

Cash Flow Analysis

Evaluate income vs expenses, savings rate, and cash flow stability over time.

Financial Behavior Scoring

Assess financial management through overdraft frequency, bill payment patterns, and savings behavior.

Income Stability Assessment

Evaluate income consistency, multiple income streams, and employment stability.

Alternative Credit Scoring

Generate credit scores for customers with thin or no traditional credit files.

How to Implement Credit Assessment

Integrate banking behavior analysis into your lending decision process.

1

Request Banking Access

Applicant connects their bank account through CDR consent during loan application.

2

Analyze Transaction History

API analyzes 3-12 months of transactions to evaluate financial behavior and cash flow.

3

Generate Credit Assessment

Receive comprehensive credit assessment including risk score, income analysis, and behavioral insights.

4

Make Lending Decision

Use assessment alongside traditional credit data for more informed lending decisions.

Key Features

Behavioral Risk Scoring

Proprietary risk models analyze banking behavior patterns to predict credit risk.

Overdraft Analysis

Track frequency and magnitude of overdrafts as risk indicators.

Bill Payment Patterns

Evaluate payment reliability through recurring bill payment analysis.

Savings Behavior

Assess financial resilience by analyzing savings patterns and emergency fund maintenance.

Debt Obligation Detection

Identify existing loans, BNPL commitments, and credit card payments from transactions.

Financial Trend Analysis

Detect improving or declining financial health through trend analysis.

Real-World Examples

Online Personal Lender

A digital lender uses banking behavior to approve loans for customers with thin credit files.

Result: Approved 25% more customers while maintaining default rate below 3%.

Buy Now Pay Later Provider

A BNPL service assesses credit risk using cash flow analysis at checkout.

Result: Reduced bad debt by 40% through better identification of risky customers.

Small Business Lender

A business lender analyzes cash flow to assess loan repayment capacity.

Result: Increased approval rate for startups by 35% with better risk assessment.

Technical Specifications

API Endpoints

  • POST /credit-assessment
  • GET /accounts/{accountId}/credit-analysis
  • GET /credit-assessment/{assessmentId}
  • POST /credit-score/generate

Data Types

  • Credit risk score

  • Income stability metrics

  • Cash flow analysis

  • Overdraft frequency

  • Savings rate

  • Debt obligations

Authentication

OAuth 2.0 / CDR consent

Real-Time Data

Yes

Frequently Asked Questions

Banking behavior analysis provides current financial health insights that complement credit scores, enabling better decisions especially for customers with limited credit history.

We recommend 6-12 months of transaction history for comprehensive assessment, though 3 months minimum can provide useful insights.

It's best used alongside traditional credit checks for comprehensive assessment, though it can enable lending to customers with thin credit files.

Banking behavior models achieve 85%+ accuracy in predicting default risk when combined with traditional credit data.

Yes, banking transaction analysis is an acceptable data source for responsible lending assessments under NCCP.

All access requires explicit CDR consent, and analysis is performed securely with data encrypted and access audited.

Yes, business banking transactions can be analyzed to assess business cash flow and credit risk.

Ready to Get Started?

Join hundreds of companies using Fiskil to power their lending applications. Get started today with our developer-friendly API.

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Banking Data-Driven Credit Assessment API | Fiskil | 2026