Fintech Featurespace Launches Large Transaction Model Using Generative AI for Financial Services

Featurespace, the enterprise grade technology that prevents fraud and financial crime, has launched TallierLTM– the Large Transaction Model (LTM).

TallierLTM, a foundation AI technology for the payment and financial services industry, “is a large-scale, self-supervised, pre-trained model designed to power the next generation of AI applications for the financial protection of consumers.”

TallierLTM has shown improvements of “up to 71% in fraud value detection when compared to industry standard models operating at an industry-typical 5:1 False Positive Ratio.”

TallierLTM gives fraud and financial crime professionals “access to the industry’s first generative Large Transaction Model providing a significant improvement when it comes to differentiating between genuine consumers and bad actors.”

70% of financial institutions in North America “consider financial criminal attacks to be getting worse as they become more sophisticated with exponentially increasing losses.”

According to the Nilson Report, global losses “from card fraud are expected to total $397.4 billion over the next 10 years, with $165.1 billion of those losses happening in the U.S.”

David Excell, founder of Featurespace, said:

“What OpenAI’s LLMs have done for language, TallierLTM will do for payments. There is widespread concern about how deep-fakes and generative AI have been used to deceive consumers and our financial systems. We plan to reverse this trend by utilizing the power of generative AI algorithms to create solutions that protect consumers and make the world a safer place to transact.”

TallierLTM has been pre-trained “across jurisdictions and market segments using a self- supervised approach, making it highly accurate and representative of real-world consumer transactions.”

By analyzing billions of transactions, TallierLTM “identifies hidden transactional patterns undiscoverable using current industry methods, enabling it to generate likely future consumer transactions.”

Insights are based on time sequencing, “such as unusual spending patterns over a short period of time and patterns of behavior between a consumer and a merchant.”

These are, for data scientists, “a critical task when differentiating between genuine and criminal activity.”

Financial institutions will be able “to interact with TallierLTM via its embedding API, which is a data science accelerator that enables a consumer’s transaction history to be converted to a machine-readable feature vector.”

It creates a unique ‘behavioral bar code,’ providing “a comprehensive representation of a consumer’s transactional behavior without revealing any personally identifiable information.”

Dr. David Sutton, Featurespace’s chief innovation officer, said:

“We know that smarter technology helps financial institutions better understand their consumers. We have taken this to the next level by pairing cutting-edge generative AI algorithms with huge volumes of data, enabling a machine to efficiently comprehend the relationships between different customer transactions.”

Featurespace plans to introduce the TallierLTM service “with its longstanding partner TSYS, a Global Payments (NYSE: GPN) company.”

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