Paper Title
Artificial Intelligence and Machine Learning Solutions for Attracting Investment and Financial Aid in the Digital Economy

Abstract
In 2020, digitization and digital transformation required a new question for an entrepreneur in the startup ecosystem, and to answer it, the "Digital Transformation Guide" from Columbia Business School (Rogers, 2016) suggested that the company's activity in this area be revised. . Digital age. Through the allegory of the matrix, this idea of the world of tomorrow was presented for startups that face new environmental, financial, social and social challenges. In this context, new technologies allow entrepreneurs to use artificial intelligence (AI) and machine learning (ML) in the financial sector and policy implications. A non-technical background on the evolution and capabilities of AI/ML systems, their deployment and use cases in The financial sector and the new challenges they present to the financial sector policy makers are used. AI/ML systems have made major advances in the past decade. Although it is not yet possible to develop a machine with the capacity to understand or learn every intellectual task that a human does, today's artificial intelligence systems can perform well defined tasks that typically require human intelligence. The learning process, a critical component of most artificial intelligence systems, is in the form of ML, which relies on mathematics, statistics, and decision theory. Advances in ML, and especially in deep learning algorithms, are responsible for most recent achievements such as self-driving cars, digital assistants, and facial recognition. To determine his path and choose the best path of growth to fulfill his mission with the desired success. The example Covid-19 vaccine(s) provides an opportunity to leverage research in the drug discovery and business development phases of international pharmaceutical companies such as Pfizer, Moderna, Astrazeneca, Johnson & Johnson, Sanofi, etc. by new technologies for the commercialization and deployment of global vaccine campaigns. Therefore, an excellent knowledge of the digital world thanks to overgrowth, the scalability of a business model, the implementation of a strategy by a management team, allows to reduce uncertainty and increase the chances of success. The financial sector, led by financial technology (fintech) companies, has rapidly increased the use of AI/ML systems (Box 1). The financial sector's recent adoption of technological advances, such as big data and cloud computing, along with the expansion of the digital economy, has enabled the effective deployment of AI/ML systems. A recent survey of financial institutions (WEF 2020) shows that 77 percent of all respondents predict that AI will be of general or very high importance to their business over the next two years. McKinsey (2020a) estimates the potential value of AI in the banking sector at $1 trillion Keywords - Digital Economy, Artificial Intelligence, Machine Learning, Investment, Income