The main objective is exploring the benefit and weak points of the synergy of statistical and fuzzy logic approaches in mining and interpreting valuable information from the financial data. The synergy of correlation, linear regression, fuzzy functional dependencies and linguistic summaries has not been explored in depth, although it could explain the knowledge mined from the data considering the different perspectives. A support for decision making (either in financial institutions or public authorities) which is validated by diverse approaches is more reliable. Correlation reveals whether two attributes are related to each other and has the relatively low computation costs. On the other hand, fuzzy functional dependencies recognise direction of dependencies. and are very demanding considering computational cost. It might happen that there are parts of two domains with very strong correlation, while for other parts it is very weak. Thus, the next step should be exploring subdomains by linguistic summaries. The synergy of statistical and fuzzy logic approaches might bring a new perspective on exploitability of knowledge and therefore should be explored and suitably reported. The data are the p2p anonymized loans from several countries considering their differences from economic, cultural and historical aspects.