Increase revenue. Stay compliant. Build responsibly.

Today, financial services companies leave money on the table by restricting themselves to simple underwriting models. With AI models, businesses can save millions of dollars by reducing the number of bad loans, finding new customers, and increasing revenue. Explainable AI is the way forward: with visibility and insights into the ‘why’ behind underwriting decisions, teams ensure underwriting models produce responsible results.

Deploy efficiently

Deploy efficiently and produce human-readable explanations accessible to users, regulators and risk managers.

Save money

Reduce bad loans. Save millions of dollars by increasing the accuracy of models
using explainability.

Build trust and loyalty

Use explanations to make end-user recommendations on how to change their
loan outcomes.

Explain Blackbox AI

Use of advanced AI is limited due to the black-box nature of AI models. This results in bias and unfairness risks.

Model Risk Managers have limited tools to review AI models and effectively assess the risks - why are there errors?

Limited transparency for end users on corrective actions. How can we enable more people to get loans?

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