Banking

Cloud-based services have been driving efficiency and cost reduction across industries for quite some time now.

Alternative data sources vary significantly in their ability to accurately assess one’s creditworthiness/predict the likelihood of someone defaulting.

KYC practices may vary by country based on unique identification sources and the maturity of digital infrastructure to automate operationally heavy processes.

With transaction banking, business enterprises can improve liquidity management, fund cash requirements appropriately, and make safe international money and securities transactions that comply with global financial frameworks.

There is always a chance of a fraudster lurking in the background, trying to grab the right opportunity to take over your digital accounts.

Canada is testing a new airport security and screening system that will allow travelers to digitize and share travel documents & biometric information.

Modern identity authentication methods such as Mobile Auth connect to mobile networks and leverage mobile data intelligence to ensure that the device used to access the service is indeed linked to the phone number being used for the service.

Exponential growth in digital transactions globally and increasing sophistication in fraud have highlighted the need for an algorithmic model that taps into multiple data sources and attributes in order to assess the trustworthiness of a transaction.

Here are some interesting examples of machine learning applications in banking.

Behavioral biometrics solutions are able to create a more precise picture of the user by examining a range of behavioral patterns.

This article from talks about Open Banking, which is one of the biggest moments in banking history that just went unnoticed.

SIM Swap, also known as SIM Splitting or SIM jacking is a fraudulent activity, where a fraudster takes complete control of users’ phone accounts by either porting or cloning their SIM without their knowledge.