meilynx

Glossary

Model risk

The risk of loss from decisions based on incorrect or misused models.

Model risk is the potential for adverse outcomes (financial loss, poor decisions, or reputational and regulatory harm) arising from errors in a model or from using a model incorrectly. Managing it is the subject of SR 26-2.

Generative AI introduces model risk in new forms: non-determinism, prompt sensitivity, and shadow usage. Bringing LLMs into a model inventory with monitoring and documentation is how firms keep that risk governed.

See it in practice

From definition to evidence.

See how Meilynx turns this into an examination-ready audit trail.

Regulatory updates

When a regulator changes what an AI examination asks for, hear about it first.

Short notes on SR 26-2, NYDFS 500, FINRA, the NAIC bulletin, the EU AI Act, and the employment-AI statutes, plus what we ship. A few emails a month.