Technological advancements have led to the widespread adoption of algorithms to automate decision-making tasks in critical domains like credit risk assessment. While algorithms can easily automate decision-making, erroneous outcomes can have severe consequences. Hence, enhancing algorithmic transparency via explanations is crucial. However, effectively designing and communicating algorithmic explanations has remained a challenging task till today. Incorporating end-users perspectives is essential for developing practical, human-friendly explanations in practice. While technical implementations of explainability techniques abound in academic literature, understanding end-users’ perceptions of these techniques in the form of visual and non-visual explanations and their value in communicating explanations has remained underexplored. This paper reports on a study exploring individuals’ perceptions of visual and non-visual explanations in the context of loan approval. Focus group discussions were conducted to examine lay peoples’ perceptions of different types of visual and non-visual explanations. Findings from the thematic analysis showed that visual explanations were appealing and more quickly comprehended than non-visual explanations. The importance of employing all possible avenues and modes of communicating explanations to ensure inclusivity was emphasized. For visual and non-visual explanations, interactive features were preferred for deeper engagement and understanding of the decision-making process. These findings convey significant implications for policy, research, and practice regarding the design of explanations, particularly in contexts of loan approval.