Everyone, everywhere: Powering an inclusive digital economy with Fast, Custom ML solutions

By Dr Leslie Kanthan, CEO and Co-founder of TurinTech.

  • 5 months ago Posted in

The payments industry has been one of the pioneers in adopting and scaling machine learning (ML) and AI. From fraud detection to facilitating seamless transactions and democratising access to banking, its influence is becoming ever apparent in our daily lives.

In the midst of the Generative AI wave, numerous companies are engaged in a frantic race to integrate artificial intelligence into their products and features. This urgency stems from the recognition that traditional ML development processes are often slow, sometimes taking months to complete. Additionally, the quality of the model code is not always guaranteed, leading to potential issues such as failed production, sluggish predictions, and costly computational requirements.

As a result, Mastercard, a global technology company in the payments industry, is partnering with TurinTech’s evoML platform to accelerate the creation of customised ML models. It’s all part of its overarching mission to connect and power an inclusive digital economy that benefits everyone, everywhere, by making transactions safe, simple, smart and accessible.

Driving the mission with evoML

By leveraging the cutting-edge evoML platform in conjunction with the deep and extensive expertise in AI and ML from its professional services area, Mastercard aims to streamline and accelerate the customisation and deployment of ML models on-premises, saving significant time and effort compared to traditional labour-intensive methods.

The versatility of the evoML platform empowers companies to generate ML code directly from raw data, but its benefits go beyond that. It can also be utilised to optimise the performance of existing models, enhancing speed, efficiency, and cost-effectiveness. By saving substantial time, domain experts can redirect their focus towards value-adding strategic tasks, fuelling innovation and driving business growth.

A standout advantage of the evoML platform is its commitment to genuine code ownership. Mastercard's clients will have the exclusive ability to download the model source code, granting them the freedom to tailor the models to their unique business needs through customisation and experimentation. This unprecedented level of flexibility opens up a world of exciting possibilities, enabling Mastercard to deliver unparalleled levels of business value to their clients.

Accelerate Key Use Cases with Pre-Trained Models

The combination of Mastercard’s expertise and TurinTech’s evoML platform is giving clients bespoke ways to advance their ML projects. Clients can get custom ML projects up and running in production within weeks. To accelerate setup and implementation, we include 4 pre-trained AI models that address common client questions:

· Which cardholders will stop spending?

· Which cardholders run small businesses?

· Which cardholders are most likely to add their card to online services like subscription services, eCommerce sites, and digital wallets?

· How do cardholders spend in eCommerce?

Advantages of Pre-Trained Models

· Higher Accuracy: custom models are more sensitive to the nuances of client-specific data, leading to more accurate predictions.

· Efficiency at Scale: evoML automates much of the manual process involved in ML development, from feature engineering to hyperparameter tuning, allowing Mastercard to scale their solutions without sacrificing quality.

· Dynamic Learning: as clients’ data evolves, the models adapt, learning from new patterns and behaviours to maintain their predictive power.

By incorporating these pre-trained models into clients’ ML ecosystems, Mastercard is giving them a significant head starts in addressing these crucial use cases. This not only saves time but also reduces the complexity of model development and ensures a higher level of accuracy in predictions, benefiting both businesses and end-users.

Additionally, the evoML platform’s advanced features are designed to help Mastercard’s clients tackle one of the biggest challenges in AI: bias mitigation. With an ethical AI framework, the platform can help ensure that the AI models are not only accurate but also fair and transparent, which is particularly important in the financial sector. Mastercard’s commitment to ethical AI through this partnership showcases their dedication to responsible innovation.

By merging Mastercard’s expertise with Turintech’s cutting-edge technology, the partnership can continue to unlock new ML capabilities to help power an inclusive digital economy for everyone, everywhere.

By Dael Williamson, EMEA CTO at Databricks.
By Shadi Rostami, SVP of Engineering at Amplitude.
By Sam Bainborough, Director EMEA-Strategic Segment Colocation & Hyperscale at Vertiv.
By Gregg Ostrowski, CTO Advisor, Cisco Observability.
By Rosemary Thomas, Senior Technical Researcher, AI Labs, Version 1.
By Ian Wood, Senior SE Director at Commvault.
By Ram Chakravarti, chief technology officer, BMC Software.