Bank Assets Tokenization

The object of the study is the securitization process in the banking sector, as well as the process of its modernization and assessment of possible risks. The purpose of the work is to evaluate the effectiveness of the existing tokenization algorithm, create an alternative algorithm, as well as model the possible risks of the investor. In the process, a probabilistic tokenization algorithm was developed and implemented in Python. The efficiency of the existing greedy algorithm was also evaluated by the criterion of “non-tokenizable balance in the bank account” and a comparison of the “greedy” algorithm with the probabilistic one, which showed that the probabilistic algorithm is more efficient than the greedy one, although it has longer operating time. Possible investor risks were also modeled by searching for the dependence between the probability of negative investor income and the number of tokens in the token pack. The results can be useful for banks who want to improve the liquidity of their assets and for people who want to have a reliable income.