AI Articles and Analysis about Data analysis

The OECD.AI Policy Observatory is an inclusive platform that brings together resources and expertise from the OECD and its partners to facilitate dialogue and provide evidence-based policy analysis on the impact of AI. It is built upon the foundation of the OECD AI Principles, the first intergovernmental standard on AI adopted in 2019, endorsed by OECD countries and partner economies.

Implementing responsible AI in the financial sector is crucial for ethical practices, fairness, and transparency. Financial institutions must prioritize data privacy, address biases, ensure explainability, and practice ongoing monitoring. By doing so, they build trust, mitigate risks, and foster sustainable growth. 

In the era of big data, companies need help navigating through an overwhelming volume of unstructured data to uncover meaningful insights. The topic search process presents unique challenges in deciphering data signals and identifying critical information before problems escalate.

As AI becomes increasingly interwoven in the fabric of our everyday lives, the insurance sector is finding new business challenges and opportunities in all of the ways these emerging technologies bring increased risk - and security - to our lives.

As a business practice, model development aims to create a dataset, tailored through machine learning, that can accurately predict outcomes or classify data based on input variables. By following a structured approach, developers can ensure that the model development process is efficient, effective, and reproducible.

Market surveillance refers to activity authorities conduct to ensure that products available to consumers adhere to applicable laws and regulations. Additionally, market surveillance in banking and finance takes a somewhat specific form.

MetLife is a leading global insurance company headquartered in New York City. It provides its customers various insurance and financial services, including life insurance, health insurance, retirement plans, and investment management.

Although not often regarded as a technological first-mover, the insurance industry has recently seen robust, even rapid, adoption and deployment of AI capabilities, particularly in those related to natural language processing (NLP).