Credit Risk Manager

About iBusiness Funding

iBusiness Funding is a leading provider of lending solutions for banks and lenders of all sizes, specializing in Small Business Lending including - Conventional, SBA and government-guaranteed lending programs. The company is dedicated to streamlining the business lending process and enabling lenders to efficiently deliver capital to small- and medium-sized businesses.

To date, we have processed more than $11 billion in SBA and non-SBA volume and handle more than 1,000 business loan applications daily through a tech enabled platform that provides a key advantage alongside our best-in-class team. Our team is driven by our core values of innovation, integrity, enjoyment, and family.

Join us and be part of a team that is transforming the finance industry and empowering businesses to thrive.

Position Description

The Credit Risk Manager will develop, implement, and monitor data-driven credit strategies that support iBusiness Funding's lending growth while maintaining credit performance within risk parameters established by the Risk team. This individual will analyze origination, pipeline, and portfolio data to identify opportunities to improve application intake, approval quality, and funding pull-through while continuously evaluating risk-adjusted returns.

The role will own and enhance business intelligence reporting for pipeline and credit performance, including dashboards built in Amazon QuickSight and other BI tools. Working closely with Credit Risk, Modeling, Analytics, Product, Operations, and Technology, the Credit Risk Manager will translate insights into credit policy, decision rules, model implementation, and ongoing monitoring.

This individual will also work directly with embedded lending partners to implement partner-specific credit models, support investors and warehouse lenders with credit performance reporting, and help launch new lending products and channels. The ideal candidate combines strong analytical and technical skills with sound credit judgment and a commercial approach to profitable growth.

Major Areas of Responsibility

Credit Strategy, Risk-Adjusted Growth, and Conversion Optimization

• Develop and refine credit strategies using application, offer, funding, and portfolio performance data to optimize growth within approved risk appetite and agreed-upon credit performance targets.

• Identify opportunities to improve application intake, approvals, offer acceptance, closing, and funded-loan pull-through by segment, channel, product, and lending partner.

• Continuously assess risk versus return, including expected credit losses, delinquency, defaults, pricing, profitability, and portfolio yield; recommend appropriate adjustments to credit policy and decisioning.

• Perform cohort, vintage, funnel, segmentation, and scenario analyses to test credit strategies, quantify tradeoffs, and measure results following implementation.

Business Intelligence, Pipeline Monitoring, and Portfolio Analytics

• Build, update, and maintain Amazon QuickSight dashboards and other BI reporting to support pipeline oversight, credit monitoring, executive decisions, and operating reviews.

• Track applications, approvals, declines, offers, closings, fundings, and subsequent credit outcomes by loan size, product, channel, partner, model, and credit segment.

• Monitor credit quality trends, vintage performance, delinquency, charge-offs, loss rates, and emerging risk indicators; investigate adverse movements and propose corrective actions.

• Partner with Data, Analytics, and Technology teams to improve data integrity, reporting definitions, dashboard automation, and accessibility of actionable risk insights.

Credit Model Development, Validation, and Implementation

• Support the Modeling team with new credit model development, validation, testing, rollout, and ongoing post-implementation performance monitoring from a credit strategy perspective.

• Translate business and credit objectives into model requirements, eligibility criteria, score cutoffs, decision rules, risk tiers, and approval strategies.

• Contribute credit expertise to model validation, back-testing, challenger testing, segmentation reviews, and assessments of model stability and predictive performance.

Embedded Lending Partnerships and Partner Model Integration

• Collaborate directly with embedded lending partners to establish and implement partner-specific credit models and decision strategies that align with each program's objectives and approved risk thresholds.

• Coordinate partner data requirements, model integration, testing, credit policy alignment, performance reporting, and launch readiness with internal and external teams.

• Monitor partner-level credit outcomes, conversion, concentrations, and risk-adjusted economics; recommend strategy refinements as performance and volume evolve.

Investor, Warehouse Lender, and Capital Markets Support

• Support investors and warehouse lenders with accurate credit performance analysis, portfolio trends, model performance, loss and vintage reporting, and responses to risk-related inquiries.

• Partner with Capital Markets and Finance on portfolio eligibility, risk concentrations, performance discussions, due diligence, and ongoing credit reporting requirements.

• Provide clear explanations of credit strategy, policy changes, underwriting performance, and risk mitigation efforts to internal leadership and external funding partners.

New Credit Products, Governance, and Cross-Functional Execution

• Support the design, testing, and rollout of new credit products, lending channels, partner programs, and growth initiatives, with appropriate performance guardrails and monitoring.

• Partner with Origination, Underwriting, Operations, Product, Risk, Compliance, and Technology to convert credit recommendations into effective policies, workflows, and decisioning logic.

• Maintain documentation of credit strategy decisions, testing, approvals, and performance; escalate material trends and help ensure adherence to Risk team parameters and applicable lending requirements.

Required Knowledge, Skills, and Abilities

• Minimum 5 years of experience in credit risk, credit strategy, lending analytics, portfolio management, or a related discipline, preferably in small business or commercial lending.

• Strong knowledge of lending funnels, underwriting decisioning, portfolio credit metrics, vintage analysis, loss performance, and risk-adjusted return measurement.

• Hands-on experience developing dashboards and reports using Amazon QuickSight or comparable BI platforms; ability to interpret large datasets and translate findings into credit action.

• Working knowledge of credit scoring and predictive models, model validation and monitoring, score cutoffs, policy rules, and implementation into lending workflows.

• Ability to collaborate effectively with Modeling, Data, Technology, Risk, Capital Markets, Operations, and external lending partners.

• Strong analytical problem-solving, attention to detail, written communication, and ability to present technical insights to business stakeholders.

• Bachelor's degree in Finance, Economics, Statistics, Mathematics, Data Analytics, Business, or a related field, or equivalent relevant experience.

Optional: Nice to Haves

• Experience with small business or commercial credit, embedded finance, partner-originated lending, or multi-lender platforms.

• Proficiency with BI Tools, Python, SQL and advanced Excel; familiarity with R or other analytical tools a plus.

• Experience supporting credit model development, independent validation activities, production implementation, and ongoing monitoring.

• Experience preparing portfolio credit performance reporting for institutional investors, warehouse lenders, or other capital providers.

• Demonstrated success improving origination conversion and funded volume while maintaining stable credit performance and attractive risk-adjusted returns.

Success Measures

• Measurable improvement in application intake, approval efficiency, and funded-loan pull-through within agreed-upon risk and credit performance targets.

• Timely, accurate, actionable QuickSight dashboards and ongoing pipeline, model, and portfolio credit monitoring.

• Successful model development support, validation coordination, controlled implementation, and post-launch tracking.

• Effective adoption and performance of partner-specific credit models across embedded lending programs.

• Successful credit support for new products and growth initiatives.