Risk Assessment Consultant - MCA/Alternative Lending

Role Overview

Design an advanced risk assessment models and logic for merchant cash advance platform. Develop quantitative frameworks for underwriting decisions, portfolio management, and default prediction using machine learning and statistical methods.

Key Responsibilities

• Risk Model Development: Create probability of default (PD) and loss given default (LGD) models

• Underwriting Logic: Design automated decision trees and scoring algorithms

• Performance Metrics: Establish vintage analysis and portfolio monitoring frameworks

• Variable Selection: Identify and validate predictive risk factors from multiple data sources

• Model Validation: Implement backtesting and performance monitoring systems

• Documentation: Create comprehensive model documentation and risk management policies

Technical Requirements

Risk Variables and Data Analysis:

• Bank statement velocity and volatility analysis

• Revenue trend analysis (12-24 months historical)

• Cash flow pattern recognition and scoring

• Industry vertical risk profiling and scoring

• NSF frequency analysis and default correlation

Required Qualifications

• 5+ years MCA, small business lending, or commercial credit risk experience

• Hands-on experience with alternative lending risk models

• Advanced statistical analysis and machine learning implementation

• Experience with bank statement analysis and cash flow underwriting

• Proficiency in Python/R and SQL for model development

• Experience with credit bureau data and alternative data sources

• Knowledge of MCA industry metrics and default patterns

Preferred Experience

• Direct MCA underwriting or portfolio management experience

• Experience with real-time underwriting systems

• Familiarity with small business credit risk factors

• Alternative data integration (payment processor data, social signals)

• Regulatory compliance in commercial lending

• Experience with PostgreSQL and open-source analytics tools

Technical Stack Familiarity

• Languages: Python/R for statistical modeling

• Databases: PostgreSQL for transaction processing

• Analytics: scikit-learn, pandas, Apache Spark

• Monitoring: Grafana/Prometheus for model performance

• Platform: Experience with open-source ML frameworks

Key Deliverables

• Risk assessment algorithm and decision logic

• Model documentation and validation reports

• Performance monitoring and alerting systems

• Underwriting guidelines and approval matrices

• Portfolio risk management framework

• Early warning system implementation

Success Metrics

• Target default rate: <12%

• Model accuracy and predictive performance

• Automated underwriting rate: >80%

• Risk-adjusted pricing optimization

• Portfolio vintage performance tracking

Application Process

Submit resume with specific examples of MCA or small business lending risk models developed. Portfolio should include model performance results and business impact metrics.

Online assessment includes:

• Risk model design scenarios

• Bank statement analysis exercises

• Statistical modeling case studies

• MCA industry knowledge evaluation