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

Viktoriya Valeryevna Manuylenko, Aminat Islamovna Borlakova, Alexander Vladimirovich Milenkov, Olga Borisovna Bigday, Elena Andreevna Drannikova and Tatiana Sergeevna Lisitskaya
Additional contact information
Viktoriya Valeryevna Manuylenko: Department of Finance and Credit, Institute of Economics and Management, North Caucasus Federal University, 355009 Stavropol, Russia
Aminat Islamovna Borlakova: Department of Finance and Credit, Institute of Economics and Management, North Caucasus Federal University, 355009 Stavropol, Russia
Alexander Vladimirovich Milenkov: Joint Department of International Law, Finance and Economics of China, Plekhanov Russian University of Economics, 117997 Moscow, Russia
Olga Borisovna Bigday: Department of Regional Economics, Faculty of Regional Development, Russian Technological University, Stavropol Branch, 355035 Stavropol, Russia
Elena Andreevna Drannikova: Department of Regional Economics, Faculty of Regional Development, Russian Technological University, Stavropol Branch, 355035 Stavropol, Russia
Tatiana Sergeevna Lisitskaya: Department of Accounting, Analysis and Audit, Faculty of Innovative Business and Management, Don State Technical University, 344000 Rostov-on-Don, Russia

Risks, 2021, vol. 9, issue 6, 1-19

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.

Keywords: open innovation; strategic innovation risk; big data mining–Monte Carlo; financial technologies; bank innovations (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/2227-9091/9/6/118/pdf (application/pdf)
https://www.mdpi.com/2227-9091/9/6/118/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:9:y:2021:i:6:p:118-:d:574473

Access Statistics for this article

Risks is currently edited by Mr. Claude Zhang

More articles in Risks from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().