Do fintechs need BSA/AML model validation? Understanding expectations and benefits

As fintechs scale and deepen relationships with banking partners, scrutiny around risk management grows, especially when it comes to the systems that flag suspicious activity. One critical but sometimes misunderstood expectation in fintech compliance is whether Bank Secrecy Act/Anti-Money Laundering (BSA/AML) systems require model validation.

Short answer: Yes, but it depends on how complex the model is. If a fintech uses models for activities like credit risk assessment, fraud detection, AML, or any decision-making that impacts customers or financial risks, they may benefit from a model validation for the following reasons:

• Reduces risk of financial loss

• Safeguards compliance with regulations

• Builds trust with partners

• Improves model performance

• Supports scalability

Each of these benefits is explored in more detail below to help you assess whether a model validation is the right next step.

How Does a Model Validation Reduce Financial Risk?

Model validations help fintechs manage financial risk by confirming that models used in critical decisions are accurate, reliable, and robust. The validation can test for data quality issues, algorithm weaknesses, and incorrect assumptions that could lead to the misclassification of data. In addition, a flawed model can lead to costly penalties for noncompliance with regulatory guidelines that banking partners are subject to.

What Do Regulators Consider a “Model”?

As noted by the Federal Reserve Board (FRB), Office of the Comptroller of the Currency (OCC), Federal Deposit Insurance Corporation (FDIC), and the National Credit Union Administration (NCUA), a model is any quantitative method, system, or approach that processes data into estimates or decisions.

For BSA/AML, this might include:

• A third-party vendor’s suspicious activity monitoring system
• An internally developed application programing interface (API) workflow with customer behavior triggers

Your banking partner’s regulator will determine which model risk management (MRM) guidelines apply. The most commonly referenced supervisory guidance includes:

• FRB Supervisory Letter SR 11-7: Requires independent validation of high-risk models, including design, data integrity, testing, and ongoing performance review
• OCC Model Risk Handbook: Emphasizes sound development, governance, and independent validation
• FDIC Risk Manual: Covers third-party risk and the need for transparent documentation during audits
• NCUA Examiner’s Guide: Stresses the importance of model validation for credit union-fintech partnerships, especially regarding consumer protection and fair lending

How Does a Model Validation Build Trust with Partners?

Today there is a growing number of financial institutions that are implementing the use of machine learning or artificial intelligence (AI). While larger institutions are building their own systems, others find it easier and less costly to partner with fintechs.

Like banking systems, fintech models can be susceptible to risk and leave the financial institutions in an inconvenient situation, involving public scrutiny and regulatory penalties. Independent validation builds confidence that your models work as intended and meet expectations, signaling your fintech is a trusted, mature partner.

How Does a Model Validation Improve Performance and Support Scalability?

Model validation improves performance by identifying issues like overfitting, underfitting, and bias, helping your team align model behavior with business goals and fix problems early. As your fintech grows, models will need to handle larger datasets and increased workloads without performance degradation. Documented model validations support future improvements by providing a clear understanding of the model’s capabilities and limitations.

We Can Help

Regardless of complexity, fintechs operating BSA/AML models are expected to validate, document, and adjust their systems regularly to meet partnership expectations. Contact the Elliott Davis team today to discuss how your fintech can leverage a model validation and appropriately manage risks associated with the growing industry.

The information provided in this communication is of a general nature and should not be considered professional advice. You should not act upon the information provided without obtaining specific professional advice. The information above is subject to change.