Model Risk Management Intern

Customers Bank•Malvern, PA

18h

About The Position

Customers Bank is a high-performing, digital-forward financial institution committed to innovation, collaboration, and community impact. With a culture rooted in entrepreneurship and continuous learning, we invest deeply in developing the next generation of leaders who will shape the future of banking. Our internship program is a cornerstone of our early-career talent strategy, offering students hands-on experience, executive exposure, and the opportunity to solve real business challenges — including our signature AI Capstone Project. We get you further, faster. You’re known by name. You’re trusted as a builder, advisor, and innovator. We start from a place of possibility. We embrace innovation and challenge convention to create meaningful, lasting impact. We act decisively. We pursue opportunities with urgency and agility, bringing ideas to life quickly and effectively — always with a focus on high-impact outcomes. We own our results. Through effort, resilience, and relentless accountability, we drive measurable success for our clients, communities, and company. We measure what matters. We set high standards, track progress, and hold ourselves accountable to outcomes that truly matter. During this 10-week program, you’ll be embedded within a specific business area — such as banking, risk, operations, finance, or technology — working on projects that support real team objectives. You’ll also collaborate with fellow interns on an AI-focused capstone project, participate in professional development programming, and engage with leaders across the organization. In addition to participating in the broader internship program, you’ll gain hands-on experience supporting the Model Risk Management team in the validation of models across interest rate risk, liquidity risk, CECL, fraud, and BSA/AML domains. Under supervision, the intern will: Review model documentation to identify gaps, inconsistencies, and deviations from internal policy and regulatory expectations Perform data quality, data lineage, and data reconciliation testing Reproduce selected model outputs to support process verification Develop or enhance benchmark (challenger) models for validation purposes Assist in back-testing and outcome analysis Draft sections of model validation reports in accordance with MRM standards Support the preparation of materials for Financial and Model Risk Management Committee (FMRC) and other governance forums Track and follow up on remediation actions related to model findings and conditions

Requirements

Rising senior (Class of 2027) pursuing a bachelor’s degree
Interest in banking, financial services, business, technology, or analytics
Strong communication, collaboration, and problem-solving skills
Curiosity and a willingness to learn in a fast-moving environment
Ability to work full-time for the 10-week summer program
Must be legally eligible to work in the United States without sponsorship, current or future, to be considered.

Responsibilities

Contribute to department assignments aligned to business needs
Analyze data, support process improvements, and assist with research
Participate in weekly development workshops and executive speaker sessions
Work with your intern team to tackle an AI-driven business challenge
Present your final project and insights to senior leadership
Build meaningful relationships across the bank through networking and team activities
Review model documentation to identify gaps, inconsistencies, and deviations from internal policy and regulatory expectations
Perform data quality, data lineage, and data reconciliation testing
Reproduce selected model outputs to support process verification
Develop or enhance benchmark (challenger) models for validation purposes
Assist in back-testing and outcome analysis
Draft sections of model validation reports in accordance with MRM standards
Support the preparation of materials for Financial and Model Risk Management Committee (FMRC) and other governance forums
Track and follow up on remediation actions related to model findings and conditions