Development and validation of a model for assessing potential strategic innovation risk in banks based on data mining-monte-carlo in the “open innovation” system

Abstract

Innovation risk in banks, a formalized instrument that is part of banks’ financial and innovative strategies, influences the assessment of innovative activity, demonstrating the importance of forecasting and assessment models of potential innovation risks. Our research into general scientific and specific methods allowed us to: (1) distinguish hierarchical concepts and their order— namely, “banking innovation”, “economic effects of innovational activities”, “financial and innovative strategy”, and “innovation risk”; (2) identify links between innovative and strategic bank management, since bank innovations are carried out in conjunction with strategies and imply positive strategic economic effects, making the assessment of potential innovation risk necessary for the current moment and the future; (3) note that the launching and use of new technologies on economic cycles and phases involving a necessary correlation between innovative profit and these phases; (4) provide preferable measurements of banks’ innovative activity and financial performance against commission income; (5) assess the potential financial performance of banks’ financial and innovative strategies within economic cycles and phases and in accordance with the nature of income; (6) present general areas for the practical application of an adapted data mining–Monte Carlo method, based on a proprietary software product. The model’s application in the “open innovation” system exhibits its multipurpose nature and allows for the selection of alternative strategic innovative solutions within economic cycle phases. It also serves in the promotion of Big Data technology in relation to finance and innovation, which is a promising area, and determines the values of the desired indicators for the “bank of the future” concept