Skip to content

AI Innovation

Both the financial and healthcare industries are undergoing an AI evolution. Review our vision for Artificial Neural Networks (ANN) and deep learning targeting these industries.

AI and Deep Learning-Based Check Processing

Check recognition & fraud detection are the most important components in today's check processing and omni-channel capture. Learn how OrboAnywhere using OrbNet AI technology reduces costs and mitigates risk for any check image capture workflow.

AI-Based Healthcare Electronification

OrboAccess, powered by OrbNet AI, provides electronification to remits and payments, enabling RCM companies to automate posting, improve research, and deliver business intelligence

About Us

Celebrating 25 years of innovation, OrboGraph has transformed into an AI company delivering targeted automation solutions to the banking and healthcare industries.

Resources

From news and events to case studies, trends, and videos, this section provides a range of information resources for payment automation in the banking and healthcare industries.

Blogs

OrboGraph produces four blog series on a weekly basis covering topics from check processing, fraud prevention, AI technologies, RCM, and healthcare electronification. Select one the blog to the right. We hope you enjoy!

Mastercard to Buy (Crypto) Digital-Currency Security Firm CipherTrace

  • Mastercard Inc. solidifies its participation in cryptocurrency
  • Crypto fraud has steadily increased
  • Banks will need to be aware of inevitable crossover fraud

Digital Transactions, true to its name, reported a literal digital transaction as Mastercard Inc. announced last week its acquisition of CipherTrace Inc., a 6-year-old company specializing in technology to combat money laundering and other crimes involving digital-currency transactions.

The deal, terms of which were not disclosed, comes as Mastercard readies a pilot to test converting crypto coins to stablecoins for direct acceptance of crypto-backed cards on its network. Mastercard’s pilot follows a similar move by Visa Inc., which late in March said its integration with San Francisco-based Anchorage Hold LLC, the first federally chartered digital-asset bank, allowed the network to process its first transaction involving direct settlement with a stablecoin, which is a digital currency linked to the dollar.

mastercard_hrz_pos_300px_2x
ciphertrace-logo-1200x630-cropped

Mastercard now expects its CipherTrace acquisition will help monitor and interpret moves in the crypto market that could indicate transaction risk. The unit will also help support regulatory compliance.

Crypto Fraud on the Rise

A year ago, there were already reports of steep increases in fraud; Digital Transactions reported that such attacks soared 90% in money services and cryptocurrency between the second half of 2018 and the same period in 2019. Experts correctly predicted that, as stay-at-home users crowded e-commerce channels during the pandemic, online fraud in general rose markedly across sectors.

The problem of crypto-related fraud has grown in recent years. “U.S. exchanges as a whole received $8.4 million worth of bitcoin directly from criminal addresses and sent $41.2 million worth of bitcoin directly to criminally associated addresses,” CipherTrace says in a report on activity in 2020.

Blockchain reduced

“With the rapid growth of the digital asset ecosystem comes the need to ensure it is trusted and safe,” said Ajay Bhalla, president of cyber & intelligence at Mastercard, in a statement. “Our aim is to build upon the complementary capabilities of Mastercard and CipherTrace to do just this.”

AI and Machine Learning for Crypto Fraud

Given the steady escalation of crypto-fraud, we can expect that cross-platform theft will result as fraudsters tie-in to banking systems. Banks will, as a matter of course, need to be more aware of crypto fraud, using AI and machine learning systems to analyze transactions.

A perfect example is the largest US-based digital wallet and cryptocurrency exchange platform -- Coinbase. On the AWS website, Soups Ranjan, Director of Data Science at Coinbase, discusses the importance of AI and Machine Learning for fighting fraud.

Machine,Learning,Technology,Diagram,With,Artificial,Intelligence,(ai),neural,Network,automation,data,Mining

Like all financial services companies, Coinbase needs to provide a seamless experience for consumers while taking steps to secure the environment in which they operate. For this, the company relies on artificial intelligence (AI) using machine learning tools from Amazon Web Services (AWS).

“AI has been in the DNA of the company from the very beginning,” says Soups Ranjan, director of data science at Coinbase. “One of the biggest risk factors that a cryptocurrency exchange must get right is fraud, and machine learning forms the linchpin of our anti-fraud system.”

Using Amazon SageMaker, a tool to easily build, train and deploy machine learning models, engineers at Coinbase developed a machine learning-driven system that recognizes mismatches and anomalies in sources of user identification, allowing them to quickly take action against potential sources of fraud.

Banks will need to implement the necessary technologies like AI and machine learning to protect themselves and their customers from fraud. As we have seen in the check processing arena, these technologies have already proven their effectiveness, detecting 95% on targeted use cases. As the industry adopts new payments channels, fraudsters will look to exploit any and all weaknesses, and, consequently, banks need to take a proactive approach by partnering with the right vendors to deploy the right solutions to stop fraud.

Leave a Comment





Review your needs with an OrboGraph expert.

Sign up below for your complimentary assessment or to request
estimated solution pricing from OrboGraph.