Keeping your sensitive data safe if your phone is stolen
CategoriesSustainable News

Keeping your sensitive data safe if your phone is stolen

Spotted: Mobile phone theft has become so common, occurring approximately every six minutes in London, that phone companies and the city mayor met in late 2023 to explore collaborative means of reducing such robberies. And, with smartphone capabilities having grown rapidly in recent years, the problem goes beyond the loss of a handset; a stolen smartphone now opens up the potential for criminals to access important personal data, including bank accounts and crucial passwords.

UK fintech startup Nuke From Orbit has created an app to help prevent the loss of such valuable data. The Nuke app allows users with an account to list other devices and a network of contacts as backups. Should the worst happen, and someone is locked out of their various accounts because their phone has been stolen, the user logs in via another device or listed contact to securely access their Nuke account.

Nuke From Orbit’s recent research found that 51 per cent of mobile owners use a digital wallet, which means that an unlocked phone poses great danger to the user if someone else is in possession of the handset. To alleviate that threat, Nuke From Orbit’s first-of-its-kind digital panic button allows account holders to block access to bank accounts, SIM numbers, web accounts, and more, as well as cancel bank cards. Users can then begin the onerous process of resetting passwords and ordering new bankcards but without the added stress of having lost money.

Nuke offers a free version of the app that provides protection for web accounts only. To protect bank accounts and payment cards, users must sign up for a monthly or yearly subscription. Nuke requires a minimal amount of personal data to set up an account, along with a relatively complex password, and there is no limit to the number of accounts that can be listed in the Nuke app.

As more of the world’s financial interactions move online and offline communities begin connecting to the internet, data security grows in importance. Innovations in Springwise’s library, like an offline banking platform and the use of blockchain in tracing supply chains, highlight some of the ways financial and digital transactions are being kept secure.

Written By: Keely Khoury

Reference

AI provides insights for industries sensitive to weather
CategoriesSustainable News

AI provides insights for industries sensitive to weather

Spotted: Traditional weather platforms tend to offer raw data but without much contextual interpretation. This can make it difficult for organisations to usefully act on the information. ClimaLinks was founded to bridge what the company refers to as the “final mile of innovation” and turn weather data into useful, actionable insights.

The ClimaLinks platform is powered by Generative AI and provides weather relations management (WRM) software and ‘Data-as-a-Service’ that enable companies in weather-sensitive industries, such as construction and agriculture, to operate more efficiently and safely. ClimaLinks connects weather insights with organisational planning tools, making it a part of decision-making processes.

The WRM platform includes both a standalone dashboard and an API that links to existing SaaS management tools. It is designed to be responsive to user’s needs and transform complex meteorological data into actionable insights, so that tasks are performed in optimal conditions. The platform includes a task monitor to help optimise operations, an asset monitor to conduct risk management, and a schedule tracker that can help organisations plan ahead and prepare for extreme and potentially dangerous weather.

ClimaLinks has seen recent investment from student-run venture fund S2S Ventures. The pre-seed funding is intended to accelerate development of the startup’s platform.

Climate change is making weather forecasting more important and Springwise has spotted innovations such as a platform that identifies environmental risk to utilities and a system that makes hyperlocal rain predictions.

Written By: Lisa Magloff

Reference