Thank you for information, what you could try is income to taking loan relation for rows that had no fd, no mortgage, no demat account, no net banking before categorizing the column in yes and no for rows without null values. Then do the same analysis with null values.
With this you will know how much difference is it making to your data
then with the null values and categorisation of 0 and 1, make data correlation first between income and age to taking loan.
Then income, age, experience to taking loan
you can also try income, age, education to taking loan
while doing these analysis, check if there is more better chances of taking loan with people having fd and net banking
You surely will have lot of understanding about your data spread then
Based on these findings which ever gives a better correlative analysis, try using those features into your creative model.
Regards
DP