Toward Inclusive and Transparent Mortgage Solutions: Cloud Computing and Explainable Machine Learning with Sign Language Interfaces
DOI:
https://doi.org/10.15662/IJRAI.2022.0505004Keywords:
Explainable Machine Learning (XML), Cloud Computing, Mortgage Risk Assessment, Sign Language Interfaces (SLI), Inclusive Financial Technology, Sustainable IT, AI Transparency, Ethical Software EngineeringAbstract
The rapid evolution of digital finance has created an urgent need for transparent, inclusive, and intelligent mortgage platforms capable of ensuring fairness, accessibility, and trust. This paper proposes a cloud-based architecture that integrates Explainable Machine Learning (XML) and Sign Language Interfaces (SLI) to redefine user experience and decision transparency in mortgage processing. The framework leverages interpretable AI models—such as SHAP and LIME—for credit scoring and risk assessment, enabling mortgage decisions that are both data-driven and auditable. These explainability mechanisms empower users and financial analysts to understand model rationale, identify potential bias, and comply with regulatory requirements for fairness and accountability.
To enhance accessibility, the system incorporates large-scale sign language recognition and translation modules based on transformer-driven vision–language models, ensuring seamless interaction for hearing-impaired users. The platform is deployed on a scalable cloud infrastructure utilizing containerized microservices, API-driven communication, and elastic resource management to deliver real-time mortgage analytics while minimizing operational costs and energy consumption. Sustainability is achieved through carbon-aware scheduling, optimized data pipelines, and federated learning techniques to reduce data transfer and enhance privacy.
Empirical results demonstrate improved interpretability (+31%), accessibility (+43%), and energy efficiency (+25%) over traditional mortgage platforms. The proposed framework offers a pathway toward ethical, cloud-native, and socially inclusive financial ecosystems where transparency, sustainability, and accessibility converge to define the next generation of intelligent mortgage technologies.
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