Digital Transformation of Financial Services using Artificial Intelligence, Machine Learning, and Cloud Computing

Digital disruption is redefining industries and changing the way business function. Artificial Intelligence is the future of banking as it brings the power of advanced data analytics to combat fraudulent transactions and improve compliance. Financial services are the economical backbone of any nation in the world. There are billions of financial transactions which are taking place and all this data is stored and can be considered as a gold mine of data for many different organizations. No human intelligence can dig in this amount of data to come up with something valuable. This is the reason financial organizations are employing artificial intelligence to come up with new algorithms which can change the way financial transactions are being carried out. Artificial Intelligence can complete the task in a very short period. Artificial intelligence can be used to detect frauds, identify possible attacks, and any other kind of anomalies that may be detrimental for the institution. This paper discusses the role of artificial intelligence and machine learning in the finance sector. Additionally, the paper will provide the necessary strategies that any banking organization can follow when digitizing its operations when implementing Artificial Intelligence, Machine learning and Cloud Computing.

To the problem of using an automated workplace by people with disabilities

Introduction. Employees of the banking sector with health restrictions have negative experience of using internal software to interact with customers and perform their official duties. Many employees, for example, with hearing problems, would like to work in call centers, but do not have this opportunity due to the outdated software. The research objective is to analyze the priority tasks for the further development of software products, taking into account the existing health problems of employees.Materials and Methods. One of the subsystems of the automated workplace (hereinafter referred to as the AWP) was selected the software, which allows the employee to interact directly with the clients of the given organization. The analysis used the method of expert evaluation by T. L. Saati with the assistance of one of the experts in the development of software for people with disabilities.Results. Using the fundamental preference scale and expert opinion in the field of software development for people with disabilities, a priority matrix was built for each of the criteria (subtitles, simplified fonts, voice guidance, simplified and remote management) and platforms (IOS, Android, Windows OS), as well as a global priority matrix for all criteria and platforms.Discussions and Conclusions. An expert assessment of several characteristics of the software of a commercial banking organization of the Russian Federation was carried out to identify the disadvantages of using the software by employees with disabilities. During the analysis, intermediate conclusions were made: the most demanded criterion for people with hearing problems is “Subtitle”; for people without the ability to leave the house — “Remote control”; for people with amputations or irreversible limb injuries — “Simplified control”. The other parameters are not recommended for implementation.

A Novel Model Structured on Predictive Churn Methods in a Banking Organization

A constant in the business world is the frequent movement of customers joining or abandoning companies’ services and products. The customer is one of the company’s most important assets. Reducing the customer abandonment rate has become a matter of survival and, at the same time, the most efficient way to maintain the customer base, since the replacement of dropouts by new customers costs, on average, 40% more. Aiming to mitigate the churn (customer evasion) phenomenon, this study compared predictive models to discover the most efficient method to identify customers who tend to drop out in the context of a banking organization. A literature review of related works on the subject found the neural network, decision tree, random forest and logistic regression models were the most cited, and thus the models were chosen for this work. Quantitative analyses were carried out on a sample of 200,000 credit operations, with 497 explanatory variables. The statistical treatment of the data and the developments of predictive models of churn were performed using the Orange data mining software. The most expressive results were achieved using the random forest model, with an accuracy of 82%.

Risk Assessment under Conditions of Uncertainty for Profit in the Banking Sphere: The PAO Sberbank Case

Subject. The article considers the economic relationship between the banking sector and the population. Objectives. We focus on theoretical and empirical analysis of the activities of PAO Sberbank, identifying threats and measures to minimize any damage to the banking organization. Methods. The study rests on the analysis of data provided by PAO Sberbank on its official website. Our calculation of indicators bases on these data. The main methods employed are expert assessments, the method of threshold values of the main threats to economic security. Results. We performed a horizontal and vertical analysis of the financial statements of PAO Sberbank, considered the structure of income and expenses and the bank's loan portfolio by sector of economy. Using the threshold value method, we unveiled the threats inherent in PAO Sberbank and developed a strategy to minimize the identified threats. The findings may be useful for analyzing the bank’s activities and identifying the threats to the banking sector in a socially oriented market economy. Conclusions. The study reveales that this bank is inherent in such threats as low short-term liquidity and loan impairment risk. We offer a strategy that affects the policy of PAO Sberbank. It includes long-term measures to increase the share of mortgage loans, which, as a result, will enable the development of the construction sector and have a positive effect on society as a whole.

Factors Affecting Total Risk in Banking Sector of Pakistan: Empirical Evidence from Panel Data Analysis

If a financial organization flops, it can impose an externality nationwide as a whole. Augmented globalization along with deregulation of financial organizations has not only given rise to competition, but it has also amplified the need for powerful policies to manage risk for the industry. Being cautious of elements which might direct to failure of banking organization support in future for evading losses by introducing preemptive initiatives to minimize damage caused by risk. This study analyzes the factors affecting total risk in banking sector of Pakistan using sample data from 2006 to 2013. The results revealed that the size of bank, financial leverage, liquidity, loan to asset ratio, growth in real GDP, supply of money and spread of interest rates all seem to be statistically significant with total risk faced by bank. However, the ratio of loan losses remained statistically insignificant. This study stresses the insertion of macroeconomic factor as a probable determining factor for total risk.

Development of Corporate Culture Based on Improving the Motivation System of the Bank's Staff

The relevance of the topic lies in the fact that the transition to innovative personal management is currently a global trend to improve enterprise management processes in the context of deep integration of the world market, high-tech industries, increased competition and improved uncertainty of the external environment in relation to the enterprise, considering the motivational system. The purpose of the research is to study the role of motivation and corporate culture as the basis for innovative development and improving the productivity of an organization. The database was used by a banking organization; for instance, during the study the approaches of scientists were studied and diagnostic methods for studying the components of corporate culture were selected. Based on the results, a model of practical implementation was formulated, and a sociological experiment was conducted. On this ground using results of the experiment, statistical data on labour productivity were obtained and methodological recommendations were made for using the model proposed in the article. The results obtained are presented as a diagnostic tool and used to include the contact centre management in the work process.

Computing Capital Budgeting for Banking Sector

Perhaps the most difficult hurdle which companies come across is the selection of the project which is beneficial to the organization in the long-run and also increases the present value of the shareholders. This is where Capital Budgeting comes into play. Capital Budgeting is one of the most important areas of financial management. This paper gives an overview of what capital budgeting is, what different types of techniques comes under capital budgeting and how to represent capital budgeting technique algorithmically. In this paper we also throw some light on what the results of various capital budgeting techniques will be if any banking organization follows these techniques and compare those results. These techniques namely as Payback Period (PP), Average Rate of Return (ARR), Net Present Value (NPV), Profitability Index (PI) and Internal Rate of Return (IRR) are used to evaluate projects.

TECHNOLOGICAL MANAGEMENT OF BANKING ACTIVITIY WITH CHANGES IN THE SETTLEMENT AND PAYMENT SYSTEM OF THE BANK OF RUSSIA

The evolution of the banking system is especially noticeable during the period of global digital transformation. In the article, the authors present a look at the internal changes in the Russian banking sector at the time of radical changes both in the economy and in the industry. The Industrial Revolution 4.0 and the sixth technological mode bring changes in the settlement and payment technologies, and therefore in the technological management of the banking organization.