Industry Prediction: Best Practices

Practical Applications by Use Case Lending

Block prohibited industries before credit pull Adjust pricing (construction gets different rates than SaaS) Set appropriate loan terms based on industry-specific cash flow patterns Monitor for industry changes that might affect repayment ability

Payment Processing

Assign correct MCC for interchange fees Screen high-risk MCCs that violate your risk appetite Monitor transaction patterns against industry norms (e.g., a "consulting" business processing $500K in retail transactions is suspicious)

Embedded Finance / Marketplace Lending

Auto-approve low-risk industries with minimal friction Route high-risk industries to manual review Customize credit limits by industry (restaurants might get lower limits due to volatility)

Compliance / Risk Management

Maintain prohibited industry lists (gambling, adult content, etc.) Enhanced due diligence for high-risk industries (money services, crypto) Regular industry verification to detect business model changes

Common Industry-Based Risk Patterns High fraud risk industries: Telemarketing, travel agencies, adult entertainment, "business opportunity" companies High default risk industries: Restaurants, retail (especially apparel), construction Seasonal cash flow industries: Landscaping, tax preparation, holiday retail Regulatory complexity industries: Cannabis, cryptocurrency, healthcare, financial services Transaction monitoring outliers: If a business's transaction patterns don't match their stated industry, investigate for:

Money laundering (using legitimate business as front) Fraud (stolen accounts being used for unrelated purchases) Business model shift (started as consulting, now running e-commerce side hustle)