What is a custom credit risk model for a credit union?
A custom credit risk model estimates each member's probability of default using your credit union's own data, such as bureau, application and internal loan performance records. Because it is trained on your members and outcomes rather than a national average, it can separate risk more precisely where your lending decisions happen. Carrington Labs builds and maintains the model as a service and delivers its outputs into your existing systems.
When should a credit union consider a custom credit risk model?
Consider one when generic scores are not separating risk well for your members, when you want to serve more members while staying within your risk appetite, or when rising delinquencies call for a sharper view of risk. It is especially relevant for credit unions with meaningful consumer lending volume and no in-house modeling team to build and maintain models themselves.
Do we need a data science or modeling team?
No. Carrington Labs provides custom credit risk models as a service. Our team handles model development, testing and ongoing monitoring, and shares the results with your credit and risk teams for review. Your staff stay focused on lending policy and member decisions, while the model's outputs arrive in the decision engine or loan origination system you already use.
Does Carrington Labs replace our decision engine or LOS?
No. Carrington Labs is a credit risk analytics layer, not a lending platform or decision engine. Model outputs plug into your existing decision engine or loan origination system via API or batch. Your credit union keeps control of lending policy, cutoffs and every final decision, and can use the model alongside the bureau scores and rules you already rely on.
What data do we need to provide?
Models can be built from data credit unions typically already hold, including bureau data, application data and internal loan performance history. Member-permissioned transaction data can add useful signal where you have it, but it is not required. Carrington Labs works with your team to confirm which sources are available and appropriate before any build starts.
How quickly can we see results?
Once Carrington Labs has your data, a full proof of concept can be completed in 48 hours. It tests the model against your own historical outcomes, so your team can review performance before making any policy changes. The timeline for production integration depends on your systems, data and internal governance process.
How are model scores explained?
Every score comes with score drivers that show SHAP contributions and plain-English explanations of what moved the result. Your team can see why a member scored the way they did, review the drivers during underwriting, and use them within your own adverse action and compliance processes.
Can it help with rising delinquencies?
Yes, through Cashflow Servicing. It monitors loans after origination and flags rising repayment risk, so your team can detect deterioration before delinquency and prioritize member outreach. For each loan it returns a risk flag, a probability of paying the next installment and a suggested next best action. Your team decides what action to take and when.
.svg)
