As a growth input, human capital and remittances have received significant attention and their role on other macro fundamentals has also been investigated. However, the effects of remittances on human capital development are not yet conclusive in the literature. The motivation of the study is to gauge the role of remittances in the process of human capital development in the topb10 remittance recipients for the period spanning from 1980 to 2019. The study has implemented symmetric and asymmetric estimations to explore the effects of remittances, FDI, and gross capital formation on human capital development. The study documented a positive and statistically significant linkage between remittances and human capital development; a similar linkage was revealed for FDI and gross capital formation. Asymmetric assessment detected asymmetric effects running from remittances, FDI, and gross capital formation to human capital development, both in the long-run and the short-run. Moreover, asymmetric shocks in remittances and FDI have exposed positive and statistically significant human capital development. In contrast, gross capital formation revealed a negative and statistically significant connection with human capital development. Referring to a directional causality test, the study documented a feedback hypothesis that holds in explaining the causality between remittances, FDI, and human capital development and unidirectional causality running from gross capital formation and human capital development. In regard to policy formulation, the study suggested that offering additional incentives could induce migrants to send more remittances into the economy, eventually supporting sustainable economic growth. Second, an efficient and effective financial sector can ensure optimal utilization through the channel of capital formation in the economy; therefore, countries must pay attention to the establishment of efficient intermediation.

In order to improve the monitoring effect of financial security risk in colleges and universities, this paper studies the financial security risk control of colleges and universities combined with the big data clustering center scheduling algorithm and inverts the multilevel sampling algorithm of quantum potential support. Moreover, this paper considers that the multilevel sampling algorithm is applied to the potential backscattering problem of the stationary Schrödinger equation to invert the support of the potential in the equation. In addition, this paper uses far-field data to invert the generalized linear sampling method of potential support and builds a college financial security risk monitoring model that relies on the big data clustering center scheduling algorithm. The experimental study shows that the financial security risk monitoring system for colleges and universities based on the big data clustering center scheduling algorithm proposed in this paper has good risk clustering and risk identification effects.