Podcast: The hidden math behind credit risk

The conversation covers why traditional machine learning models are missing critical components for accurate risk assessment and how adverse selection has dramatically impacted loan quality in recent vintages. Then Joe makes a bold prediction that software user interfaces are on the verge of a transformation that will render them unrecognizable from previous versions Curious? All is revealed in this fascinating conversation.

In this podcast you will learn:

• How he got started with Deep Future Analytics
• The state of credit risk management in banking today.
• What is missing, even with fintech lenders, who are using machine learning.
• What lenders get wrong when they focus on credit score.
• Why loans booked since 2022 are lower quality than even 2006-07.
• What kind of lift lenders or investors can see with DFA’s models.
• What Joe sees in the pool of borrowers today.
• Why DFA moved into AI monitoring and governance.
• Who is using these new AI models they have developed.
• Why a “human in the loop” is not an effective monitoring method.
• What their new Strategic Recommendation Agent (SyRA) does.
• How they incorporate Large Language Models to ensure zero hallucinations.
• Why the future of software is dashboards on demand and analytics on demand.
• How Deep Future Analytics is different to others in the market.
• What it is going to take before software moves to a chat-based interface.

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