principal component analysis - right choice & interpretation

Hi everyone,

I'm kinda stuck with a problem. I am building a scoring model with 14 different factors. Here my first question: as it's not a regression, can I use a principal component analysis to narrow that down?

If I can, I am also struggling with interpreting the results. I have 4 factors with an eigenvalue >4, but with only 43% of squared loadings (is that very bad?).
However, my 14 factors go well on the rotated component matrix (only one is on two factors) - now my noob question:
What are these factors? They denominated 1-4 - but they are not my first 4 initial factors?

I really hope you can help me - thanks a lot!!!!!!