AI Articles and Analysis about Business intelligence and analytics

Accurately projecting and communicating shipment details in freight and logistics is paramount for successful, safe delivery across the vast supply chain. 

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.

From work-from-home policies and digital-first communication with prospects – the COVID-19 pandemic dramatically accelerated many trends already in progress for businesses and consumers. Among sales teams, digitally enabling buyer journeys became a must-have almost overnight.

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.

Critical to the definition of robotic process automation (RPA) is the notion that the tasks a 'robotic' software automates are repetitive by nature, with exceptions in rare instances. While RPA cannot independently learn from and adapt to new contexts and workflow problems, it can if the RPA system is imbued with the correct AI capabilities.