Net Element Launches Blade, Fully-Automated, Artificial Intelligence-Powered Underwriting Solution with Predictive Scoring

Net Element Launches Blade, Fully-Automated, Artificial Intelligence-Powered Underwriting Solution with Predictive Scoring

Net Element’s Blade unlocks the power of artificial intelligence

Net Element, Inc., a global technology and value-added solutions group that supports electronic payments acceptance in a multichannel environment including point-of-sale (POS), e-commerce and mobile devices, announces that it has launched Blade, its proprietary, fully-automated, artificial intelligence (“AI”)-powered underwriting solution with predictive scoring.

Blade is a software built for underwriting and on-boarding of new merchants, reducing potential risks and decision-making time while improving the customer experience. The system works by compiling and analyzing data points that are automatically evaluated in accordance with the pre-set and dynamic parameters using proprietary algorithms.  Blade is a smart system, which continually adapts and improves the artificial intelligence as tens of thousands of datasets evolve to further enhance real time decisioning.

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Financial services companies will spend $11 billion on AI in 2020 according to an analysis by International Data Corporation (IDC), more than any other industry cited.  According to PwC estimates, financial services companies stand to make a nice return on their investment as well. In North America alone, AI is projected to increase the GDP of the financial and professional services industry as much as 10 percent by 2030, driven by increases in both productivity and consumption.

Intelligent data analysis and advanced machine learning algorithms provide actionable insights based on tens of thousands of datasets in order to reduce potential losses attributable to chargebacks or fraud, at a speed and scale unlike any other product in the market.  Blade’s AI-based scoring engine provides a faster, more accurate assessment of risk during the on-boarding process, at less cost, and accounts for a wider variety of factors which leads to better, data-backed decision making. The continuous updates from the system enrich the AI-powered decision-making process. This information can then be used in predicting outcomes to improve customer support, risk management, client retention and collections.

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An average account review takes 15 minutes in a semi-automated environment.  This standard review includes KYC, AML, OFAC and many other requirements designed for full regulatory compliance and to mitigate losses.  Blade completes this review in less than a minute. If the account fails, it provides a detailed description of the problem and suggested solutions.  It filters, categorizes and classifies approvals for post underwriting merchant reviews resulting in risk mitigation and a better customer experience for the merchant.

“AI and machine learning are quickly becoming valuable tools for decision making in the payments ecosystem, particularly in securing e-commerce transactions,” commented Shawn Brown, Vice President of Risk for Net Element. “As we continue to grow, we will rely more on AI-powered technologies to assist us with day to day departmental functions and decision making.”

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