As an application of blockchain technology, crowdsales are generally unregulated, allowing investments to reach startups faster and without fees. Additionally, although investors may hold onto their coins or tokens to receive dividends as if they enjoyed shares in the company, they do not have enjoy the same control over company management. Startups then enjoy a level of managerial freedom that companies previously did not have.
Finally, in addition to providing much-needed capital to startups, crowdsales provide crucial measures of the level of interest in a new project.
Since most cryptocurrencies are not yet regulated by a central authority, crypto owners cannot store their currencies in traditional bank accounts. Thus, cryptocurrency wallets (or crypto wallets) were developed.
These wallets generally come in the form of either software or hardware—also called hot or cold wallets. Hot wallets connect to the internet and allow the owner to both receive and send crypto tokens. Cold wallets, on the other hand, do not connect to the internet. For this reason, hot wallets have more security features than cold wallets.
Banks, credit unions, credit card companies, insurance companies, stock brokerages, investment funds, and more must report their activities to government regulatory agencies. Following financial crises in the late 2000s, regulatory compliance has become stricter and more onerous on financial services companies like those listed above.
From the stricter need for reporting and the massive amounts of data generated by financial institutions, the regtech industry has sprung up, combining regulatory reporting and big data technology.
Gig Economy Data Hub provides data about the workers, the size of the gig economy, and the types of work done. The data hub focuses on gig work in the US and tracks information state-by-state. It also provides introductory information for readers.
African Financial & Economic Data is a data provider that offers reference sources and analysis on the African financial market.
African Financial & Economic Data (AFED) gathers resources from various sources to provide marketers with reference sources and contextual analysis on the African financial markets for all 54 African economies. They also provide translation services for their documents, presented in a standardized format for marketers and forecasters.
African Financial & Economic Data Country Profile provides insights on any country in Africa.
African Financial & Economic Data Sector Focus provides in-depth coverage in any sector to evaluate and track economies in Africa.
African Financial & Economic Data Hub provides African economic data through data points.
A store’s location directly impacts supply, profits, marketing, and almost every other aspect of store performance. Much can be learned from the performance of different types of retail stores in different neighborhoods, countries, or even climate areas. Therefore, retailers use geospatial data machine learning models to plan store locations and predict profits.
Hedge fund investments use several different strategies to achieve returns in both domestic and international markets. They are often aggressively managed and trade in land, real estate, stocks, derivatives, currencies, etc. markets.
The most lucrative hedge funds also have a diverse portfolio—which means investors need to analyze large amounts of data to make investment decisions.
Organizations must satisfy the unique demands of their customers. The good old days of mass marketing and predictions on limited mixture of products in one location are gone. Conversely, the use of artificial intelligence in inventory generates huge dividends to companies willing to reshape their supply chain orders.
This technological development results from the availability of massive amounts of real-time data now routinely generated by enterprise software systems and smart products. By collecting this data, organizing it, and interpreting it, artificial intelligence and machine learning have introduced an entirely new level of data processing leading to deeper business insights.
Everyone wants more leads, but the more we are able to generate, the harder it becomes to identify which of them are actually worth the time and effort spent in order to try to convert them. Lead scoring models let you automatically rank your leads in order of the perceived value each lead represents to your company. Resources for marketing and sales can then be distributed by the priority determined by lead scoring.
An online recommendation engine is software that analyzes available user data to generate suggestions for something the user may also be interested in. Such engines are used in an advertising capacity to promote products or services or for the purpose of recommending similar content to the content the user has consumed in the past, such as in streaming services and online shopping services.
Product performance forecasting predicts future sales volumes—at what price, during which time, and in which market. It enables businesses to make informed decisions in both the short term and the long term. Nowadays, companies rely on machine learning software for product performance forecasting as these programs continuously improve, providing businesses with faster and more reliable estimates all the time.
Property value and mortgage value assessment is the estimation of the future value of a particular asset for purchase, insurance, and more.
Unlike most other purchases, real estate tends to rise in value over time. This rise is influenced by economic and social trends, environmental conditions, and on governmental controls and regulations. These large-scale trends directly affect the general demand for property ownership, the scarcity of property for purchase, the utility of the property for potential owners, and the ease at which property rights can be transferred.
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