The general dynamic risk assessment for the enterprise by the hologram approach in financial technology

Abstract

The purpose of this paper is to discuss the general risk assessment under the Hologram framework for the enterprise based on big data language; and to illustrate the Hologram as a new tool for establishing a mechanism to evaluate SMEs growth and change in financial technology dynamically (here we mainly focus on SMEs as they are one of the very important classes for enterprises with less information available from financial accounting report and associated assets. Indeed, the approach discussed here is applicable to general enterprises). The key idea of our new approach is to introduce and use the “Hologram” (similar to, “holographic portrait” used in portrait holography), a platform for data fusion dynamically, as a tool and mechanism to describe the dynamic evolution of SMEs based on their business dynamic behavior. Through processing structured and/or unstructured data in terms of “related-party” information sets which analyze (1) “investment” and (2) “management” information provided by SMEs’ business behavior, and extracting “Risk Genes” from complex financial network structures in the business ecosystem, we can establish a “good” or “bad” rating for SMEs by using data fusion dynamically and financial technology. This method to assess SMEs is a new approach to evaluating SMEs’ development dynamically based on the network structure information of enterprise and business behavior. The framework introduced in this paper for the dynamic mechanism of SMEs’ development and evolution allows us to assess the risk of any SMEs (in particular to evaluate SMEs’ loan applications) even not available for critical data required in traditional finance analysis including information such as financial accounting and associated assets, etc. This new “Hologram” approach for SMEs assessment is a pioneering innovation that incorporates big data and financial technology for inclusive financial services in practical application. Ultimately, the Hologram approach offers a new theoretical solution for the long-standing problem of credit risk assessment for SMEs and individuals in practice. Since the information embedded in SMEs’ business behavior reveals the competition and cooperation mechanism that drives its stochastic resonance (SR) behavior which is associated with successful SMEs development, the two concepts of SAI and URR under the Hologram approach to risk assessment that identifies if an SME is “good” are based on the network generated from an SMEs’ related-party information in terms of “investment” and “management” dynamically, along with other available information such as related investment capital and risk control. Significantly, the Hologram approach to risk assessment for SMEs does not require critical data of traditional financial account and related assets, etc. which heavily depend on financial accounting and associated assets used by financial risk analysis in practice. Using big data and FinTech Hologram method discussed in this paper utilizes the related-party information (in term of investment and management) of each SME which exists in an embedded business network to overcome the situation for SMEs which always have not or have not enough in providing accounting and associated asset information in the practice. By the feature of each Hologram for a given SME, one always has the related-party information in terms of either investment, or management dynamically, which is indeed also an explanation for the reason why the new approach proposed only comes true only until the era of big data’s occurring by using ideas from financial technology today. Furthermore, this paper explores the implementation of the “Holo Credit Loan”, a pure credit loan without any collateral and guarantee launched in 2016, as practical applications of the Hologram approach. We illustrate the framework of SMEs risk assessment under the Holograms new theoretical basis for solving the long-standing problem of credit risk assessment for SMEs (and individuals). Moreover, this paper’ conclusion will address the performance of the “Holo Credit Loan”.

The decision‐making of optimal equity and capital structure based on dynamical risk profiles: A Langevin system framework for SME growth

“…Actually, in network environment it has been widely found that SMEs by no means operate independently, but cooperate in groups and form symbiotic relationships with strategic partners by joining resources to achieve common goals, gain competitive advantage, and even share risks. 22,23 Furthermore, in the development process there exist nonstrategic partners, which are numerous and often replaceable. The instable relationships between nonstrategic partners and focused SME are created temporarily, and only exist in certain time periods as required, which leads to the fluctuating number of nonstrategic partners with the time.…”

“…The effect of SMEs acting as outward investors cannot be neglected in the process of growth, and the investment process inevitably results in the active or negative influence on state evolution. Therefore, we are motivated to employ the dichotomous process 24 to mimic the outward investment influence on damping effect, and the typical model, only with additive risk, 22,23 is extended to the generalized form with both internal additive risk and external multiplicative risk. In essence, it is based on Schumpeter's economic thought for economic development theory with the "innovation" being an internal factor, and the "economic development" being a change of economic life from internal creativity applying to the SME growth in the tech-economic paradigm.…”

“…However, all these works were based on the assumption that SMEs didn't have the ability of outward investment, and the models were restricted to the constant damping efficiency, which indicates that the frictional damping effect is supposed to be proportional to change rate of SME state. Actually, in network environment it has been widely found that SMEs by no means operate independently, but cooperate in groups and form symbiotic relationships with strategic partners by joining resources to achieve common goals, gain competitive advantage, and even share risks 22,23 . Furthermore, in the development process there exist nonstrategic partners, which are numerous and often replaceable.…”

“…Furthermore, in the development process there exist nonstrategic partners, which are numerous and often replaceable. The instable relationships between nonstrategic partners and focused SME are created temporarily, and only exist in certain time periods as required, which leads to the fluctuating number of nonstrategic partners with the time 21,23 . In the previous literatures, the ability of outward‐investment ability of SMEs is neglected in under‐capitalization regime, and thus all the strategic or nonstrategic partners are supposed to play the role of inward investors.…”

A Hybrid Blockchain Model for Trusted Data of Supply Chain Finance

“…Li et al [ 34 ] uses big data technology to analyze customers' browsing behaviors, habits and hobbies, so as to help enterprises understand customers' needs more clearly and provide customers with efficient and accurate services. With the help of "hologram", Yuan et al [ 35 ] provides a new method to evaluate enterprise credit risk based on business behavior interaction. Although the emergence and application of emerging technologies such as the Internet of things and big data, supply chain finance can’t be divorced from credit risk.…”