Should lenders turn borrower data into images for AI?

A 1.34-million-loan benchmark found a convolutional-neural-network and random-forest hybrid improved default discrimination, but much of its power came from LendingClub's existing risk grades and it was never tested in live lending.

Will the UK's new robot hubs change your work?

Eight new Robotics Adoption Hubs, backed by £40 million, aim to help organisations test and adopt robots. The immediate change is access to advice and demonstrations; better jobs, faster recovery and productivity gains still need evidence.

What changed: Updated 10 October 2026, 10:57 BST: expanded the original brief into a substantive report, clarified what the £40 million announcement does and does not fund, and added task selection, procurement, workforce and evaluation questions. The 9 October source date and original publication time are unchanged.

Do retailers need deep learning to forecast demand?

Not in this benchmark. XGBoost matched or beat five linear and neural-network alternatives on 913,000 historical sales records, while training faster than every neural model. The study does not prove the same choice will work in a live retailer.

Does complex AI improve microloan decisions?

Not in this study. On 2,500 resolved MENA microloans, CatBoost and regularised logistic regression had statistically indistinguishable discrimination. Alternative data added little measurable lift, while a headline fairness screen missed a substantial rural–urban error-rate gap.

Does human oversight improve perceived AI-audit outcomes?

A survey of 150 ESG-audit professionals linked automation and human oversight with higher self-rated efficiency, accountability and transparency. It measured perceptions—not audit speed, accuracy or detected greenwashing—and cannot establish cause.