On its path to building a global payments ecosystem, TerraPay - a leading global payments infrastructure company, today announced its partnership with cutting-edge machine learning (ML) company, Scribble Data. The partnership is part of TerraPay’s investment into its data science and analytics function, to improve the scale and quality of decisioning logic, build thought leadership, and enable new product development.

Scribble Data's Enrich Feature Apps platform is at the core of the TerraPay Intelligence Platform (TIP). TIP is designed to drive large scale data preparation, modeling, and custom data workflows. TerraPay has already deployed ten distinct use cases in TIP, covering AML (anti-money laundering), benchmarking & metrics, and settlements.

TIP's AML engine de-duplicates underlying data (a complex exercise, considering the numerous sender and receiver partner organizations, each with varying KYC data fields, fuzzy logic and other proprietary filters), and implements a number of logic models to identify high-risk transaction activities and patterns. This has increased the efficiency of the AML staff, enabled scaling of the workflows, and reduced errors.

Commenting on the partnership, Akbar Hussain, Co-founder and Chief Legal and Compliance Officer noted, “Scribble Data’s engineering platform allowed us to translate our transaction overwatch ambitions into a self-improving data product. As a transaction-size-agnostic platform, our ability to foster financial inclusion rests directly on our ability to scale compliance outcomes. TIP pinpoints AML/CTF analysis., allowing us to spin up widgets for datasets, thereby making previously unsolvable problems solvable.”

Speaking about the partnership, Dr Venkata Pingali, CEO – Scribble Data, said “We're glad to be partnering with TerraPay - they are growing at a rapid pace, but doing so robustly. The curiosity and rigour they bring to the work they do complements our own in how we've engineered our feature apps platform. Their use cases, both ML and sub-ML, including analytical work that needs productionized and auditable datasets, is a fertile ground for the deepening of our own experience and technology roadmap as we start to offer more fintech-focused solutions atop Enrich.”