Zilch extends partnership with AWS

Previously, by leveraging AWS, Zilch decreased its development times, enabling it to include approximately twice the amount of data into its models whilst also reducing build time. Through its AI engine, the company currently utilises the technology to deliver tailored affordability limits for each customer more efficiently and accurately. Additionally, Zilch leverages AI for fraud detection and to have a better understanding of buyer intent, having several models in use for cases such as tracking popular retailers and consumer demand. The move is also supported by Zilch’s position which allows the company to leverage AWS’s AI and ML services due to the volume of data held within its data lake, which is developed on AWS.

Furthermore, the two companies expect a positive commercial impact of the use of AI and ML services, with them predicting that Zilch can accelerate sales by 2026 and enhance its customer experience and lending decisions. Also, by obtaining deeper insights into underwriting and visibility in fraud detection, the company is set to generate an improvement of nearly 10% in near-time model performance. According to Zilch’s officials, the merger between the company’s data sets and AWS’s AI and ML services is set to provide it with an enhanced position. Zilch aims to leverage AI to invest in increasing the productivity of its team, accelerating unit economics, and developing more value for customers. Representatives from AWS underlined that its SageMaker and Bedrock solutions can enable Zilch to deliver more accurate and faster lending decisions, while also expanding its offer to more consumers across the UK and into additional geographies and markets.

Shortly before the current announcement, Zilch partnered with Checkout.com, intending to focus on the UK and US markets and maintain its reputation for fast and reliable payments for its growing customer base. The move was anticipated to positively impact the two companies’ technology stack and payment infrastructure.

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