ApplicationsCausal data science can help solve previously intractable problems in machine learning, enabling companies to build better AI products and services.
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Fairness in Finance
As regulators place increasing demands on the financial services industry to prove that their AI models are not discriminatory, more powerful mathematical techniques are needed. Causal AI techniques may provide the methods for building fair AI models and to provide the mathematical proofs needed to protect firms against anti-discrimination lawsuits.
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Alternative Data in Credit
Our patent-pending causal AI technology may help companies exploit mathematical flaws in how AI systems are being developed today, unlocking the full potential of alternative data to build more accurate and fair credit risk models. This may enable lenders to profitably extend credit to underserved communities without causing illegal discrimination.
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