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.
Business Intelligence for Blockchains provides businesses with specific insights into behavior of stakeholders, improving decision making
Data Cooperative by Flipside Crypto can be used by businesses to better understand their blockchain business, the industry and increase transparency.
Fraud between companies can interrupt the flow of business and destroy their reputations and it is becoming increasingly difficult to identify and stop criminals from committing fraud: PYMNTS.com’s 2019 yearly report, “Securing B2B Payments,” relates that global markets lost $4.2 trillion in 2019 alone due to fraud. However, machine learning can identify fraud accurately before it has occurred.
Credit scoring is a statistical analysis performed by lenders and financial institutions to assess a person’s creditworthiness for mortgages, credit cards, and private loans. Credit scoring is used by lenders to decide whether to extend or deny credit.
Traditionally, a person’s credit score determined by credit bureaus is a number between 300 and 850 with 850 being the highest credit rating possible. As new types of lenders and insurers emerge, however, the traditional credit score becomes just one parameter joined with a large variety of alternative data that helps determine a person’s creditworthiness.
Nowadays, the abundance of data and the advances in Machine Learning and big data applications reduce the need for top-down segmentation of customers. Smart customer clustering based on many commonalities help companies better address customer needs to provide the right experience and divide resources efficiently.
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.
Insurance fraud can be committed by either the buyer or the seller of an insurance policy.
The seller may offer policies from non-existent companies, fail to submit premiums, and churn policies to create more commissions. The buyer exaggerate claims, falsify medical history, post-date policies, sell their policy to for cash when they are diagnosed with a terminal disease, or fake their death or kidnapping. We will focus on the buyer insurance fraud in this post.
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.
Most if not all companies and organizations seek to establish themselves in social media platforms such as Facebook, Twitter, and Instagram in addition to their official website. Online and social media performance tracking is meant to analyze the effectiveness of a company’s social media presence. Are they generating new leads? Are they promoting brand awareness? These questions are important to assess the efficiency of the use of these social media platforms.
Portfolio management is the management of investments to meet long-term financial objectives.
Today, machine learning models and external data are used in order to help companies and individuals better manage, diversify, and maintain their assets and take on less risk for higher reward.
Today, machine learning models and external data are used in order to help companies and individuals better manage, diversify, and maintain their assets and take on less risk for higher reward. Portfolio management models and use cases include any collection of investment instruments like shares, mutual funds, bonds, FDs and other cash equivalents, etc.
Promotional planning is the process of optimizing marketing tools, strategies, and resources to promote a product or service to generate demand and meet set objectives. Artificial intelligence (AI) can be used to effectively plan promotional events, measuring their outcomes, and adjusting as necessary to achieve growth.
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