Featurespace Launches TallierLTM™ For The Financial Services And Payments Industry

Featurespace, the world leader in enterprise grade technology that prevents fraud and financial crime, has launched TallierLTM™ – the world’s first 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.

“What OpenAI’s LLMs have done for language, TallierLTM™ will do for payments,” said David Excell, founder of Featurespace. “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.

“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,” said Dr. David Sutton, Featurespace’s chief innovation officer. “By adding TallierLTM™’s feature vectors to the inputs of an industry-standard fraud model, we’ve seen improvements of up to 71% in fraud value detection. This will accelerate data science teams’ ability to level up their model performance and realize the value of machine learning investments more quickly.”

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

“TSYS and Featurespace have a long track record of co-innovating to deliver industry-leading technologies and solutions that help financial institutions provide secure, seamless experiences at scale,” said Dondi Black, executive vice president and chief product officer for TSYS. “TallierLTM™ is the next transformative step, allowing us to unlock new insights and power new experiences for our clients around the world, further differentiating our capabilities with this new groundbreaking solution.”

A new peer-reviewed scientific paper detailing the advances that enabled the development of TallierLTM™ has been accepted to appear at the 2023 ACM (Association for Computing Machinery) International Conference on AI in Finance.

Companies interested in learning more about TallierLTM™ can register at www.featurespace.com/tallierltm/.