Project Summary

Credit contracts are crucial for consumers to access necessary funds, but their complexity often causes misunderstandings, stress, and anxiety, particularly among financially insecure or disadvantaged individuals. This can lead to poor financial decisions and negatively impact overall well-being and financial inclusion. 

Research shows that simplification of documents improves comprehension and performance¹. Amplifi, an online tool by Amplified Global, measures and simplifies written communications through guided suggestions and intelligibility metrics. Amplifi assesses various factors like word complexity and provides a detailed audit trail of changes made to enhance document clarity. 

This study identifies and categorises confusing and stressful elements specifically in credit contracts that would provide Amplifi a novel user case in real financial services.  We collect real data based on coherent human-focused experiments and select suitable machine learning methods that detect complex and confusing contents and produce mapping with cognitive responses and actions. These will collect intelligence on the key points of consumers when dealing with credit contracts, enabling the development of optimal strategies, services and products to assist consumers.   The outcomes will be integrated into Amplifi’s AI Model that can be applied to multiple segments of the financial services industry, all of which will benefit from these improvements.

Project team