FinTech

Human Machine Interface IInextSignals has developed a proprietary relational database that links one’s individual genes to research studies that report correlations between genetic variation and financial decision making.

Our algorithms:

  • match multiple genetic variants, including pleiotropic genetic variants, to Gene-wide Association Studies (GWAS) and large scale meta-analyses
  • cluster lead variants by behavioral associations and provides references for two or more GWAS studies for multiple SNPs
  • assemble a polygenic screen for individual differences in emotional reactivity, impulsivity, cognitive flexibility, and the propensity to take risk
  • calculate genetic risk scores for each gene panel using the weighted sum of the risk allele counts where the weight for each individual variant is determined by the log-odds-ratio of its association with each investment behavior
  • display aberrant genetic variants, ranked by effect size and zygosity
    provide personalized recommendations for allocations to value or growth