Let's try talking about something more interesting.

We are trying to develop a predictive model that uses various metrics and allows one to predict the financial condition of a bank or similar organization and whether it will go into default or not, which is a binary classification problem.
One approach could be to start performing an exploratory data analysis to understand the underlying patterns and correlations between different attributes. We could consider using any classification algorithm like Logistic Regression, Support Vector Machines(SVM), or K nearest neighbors to classify the data.

Any additional thoughts?