Prove Blog

68% of companies recognize that data quality issues are an obstacle to digital transformation (source: Experian), while companies with “high-quality data management” generated 66% more revenue than companies with insufficient data quality strategies (source: SiriusDecisions). For businesses, the negative impacts of poor data quality include productivity loss, operational expense, reputational damage, and missed marketing, sales or relationship-deepening opportunities. For customers, poor data quality often makes it difficult to complete processes designed for self-service.

Digital onboarding platform Instnt announced today that it has selected Prove as its identity authentication partner based on the company's modern way of authenticating identity based on the phone number.

Black Friday is right around the corner and while bargain hunters are preparing to find the best deals, fraudsters are making plans to prey on unsuspecting consumers. If your company uses multi-factor authentication (MFA) such as one-time SMS passwords (OTPs) to safeguard customer accounts, you might think you’re covered. But our recently published analysis of over 385,000 retroactive SMS & Voice OTP transactions, conducted using our Trust Score™ technology, unearthed 4 concerning multi-factor authentication vulnerabilities:

“Trust gap” is a term that has been trending since the start of the COVID pandemic – have you heard of it? It refers to the discrepancy between the percentage of customers that companies can trust and greenlight immediately in-person vs. how many they can trust online. With more and more consumers interacting online than ever before, and more fraudsters taking advantage of that surge, the trust gap is forcing companies to put more security hurdles in place, hindering the customer experience.

Customers can now have the option of fulfilling all their banking needs through an iPad.

With big banks denying the vast majority of small-business loan applications, the role of other lenders becomes increasingly important.

Here are some interesting examples of the applications of blockchain technology beyond financial services:

From digital currency to digital deposits, financial services organizations are having to divert from their old-school ways of closed, monolithic legacy applications.

Machine learning is a type of artificial intelligence that provides computers with the ability to learn without being explicitly programmed.

Voice-enabled assistants are estimated to reach 1.83 billion by 2025.

Initial perceptions of FinTech startups pegged them as standalone disruptors of the financial ecosystem. But the consensus within the financial sector is shifting.

It's important to understand what actually is the gig economy, where it would fit in the post-COVID-19 world, and what it means for FinTech.