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Assessing risk associated to structured financial products requires processing information about diverse risk factors. Some information comes from the different sources directly in aggregated form, so that it is not possible to estimate the correlation among different risk components. In this paper we argue that Secure Multiparty Computation could be used to merge the information from the different sources so as to compute more accurately the overall risk profile of securitized assets, thanks to the use of reliable information from the individual sources, but without disclosing the information from each source. Our simple model for securitization can solve in many cases information asymmetries between lenders and borrowers.