Prediction markets reached $9B (Polymarket) and $11B (Kalshi) valuations at the end of 2025, yet 0% of this capital can be borrowed against, creating DeFi's most extreme utilization gap.

The bank said rising volumes, tighter market structure and early institutional engagement are pushing prediction markets beyond their gambling roots toward a new asset class.

While some industries have been slower to explore how they might use AI in their operations, the financial services sector ...

To his credit, Kasy is a realist here. He doesn’t presume that any of these proposals will be easy to implement. Or that it will happen overnight, or even in the near future. The troubling question at ...

Abstract: The precise prediction of loan defaults is very important for banks and other financial institutions to mitigate their risk. This study evaluates the performance of three different machine ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

BDO USA reports that generative AI helps retailers forecast demand by analyzing real-time data trends, improving inventory accuracy and decision-making.

Abstract: The financial sector of any nation is the key factor in elevating the economy of nation. The biggest issue that finances departments are facing is to approve loans for valid candidates only.

Scalable ETL pipeline and Machine Learning model to predict mortgage defaults using Freddie Mac’s Single-Family Loan-Level Dataset. Migrated from a Pandas-based legacy system to a distributed PySpark ...

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...

Gestational diabetes mellitus (GDM), a prevalent metabolic disorder associated with pregnancy, which often postpones intervention until after metabolic complications have developed. This study seeks ...