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Read about the latest use cases and real-world applications of Causal AI

How to Connect Business Teams and Data Scientists

Increase the relevance of data science to the business! Causal AI models are premised on business insight, and directly enhance […]

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Explaining the News: Why Capital Markets Need Causal AI

Nearly all players in capital markets believe that AI is critical to their future success. However, AI adoption also poses serious, even existential, risks for enterprises that misapply the technology.

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How Financial Institutions Can Reduce AI Regulation Risk

Regulations, proposals and guidance on the use of artificial intelligence (AI) for financial institutions are arriving thick and fast.

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How Human-Machine Teams Can Out-Think Fraudsters

Causal AI, a new form of human-centered AI, gives banks an extra layer of intelligence in the fight against payment scams and novel fraud tactics.

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Certifying AI Fairness

causaLens’ research sets out an actionable framework that enables businesses and regulators to test AI systems for bias and discrimination.

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The Next Chapter in AI for Marketing

Legacy Machine learning (ML) is designed to make predictions. It finds correlations and projects them into the future.

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AI that Actually Works for Real Estate

Real estate investors have been slow to adopt AI, and understandably so. Machine learning algorithms can’t function with small datasets that are ubiquitous in real estate, and they can’t incorporate investors’ deep domain knowledge. Causal AI solves these challenges

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Why data providers need Causal AI

To compete in a crowded market, data providers must be able to move up the data value chain, delivering not just raw data but signals and solutions.

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Causal Portfolio Optimization: Modern Portfolio Theory 2.0

Leading portfolio managers are leveraging Causal AI to boost risk-adjusted returns. Find out how.

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