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.
iBehavior provides a database designed around capturing SKU-level transaction data to provide useful insights to their clients.
Fighting money laundering is a complicated task with substantial costs and risks, including—but not limited to—regulatory, reputational, and financial crime risks. Money laundering can be difficult to track, with many false alerts making detection even more challenging. But new technology, such as artificial intelligence (AI) and big data, can increase detection rates and keep your firm safe.
Many companies supply goods, loans, and services based on business and trade credit, either invoicing customers for payment at a later date or providing B2B loans. Business credit risk management assists companies with lending decisions based on a client’s financial health as well as other parameters that may indicate how likely they are to pay on time. Providing the right amount of credit will reduce the risk of late payments or defaults, which expose the vendor to financial risk.
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.
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.
Insurance claims management is the process of managing a claim from reception to settlement. The insurance claim process is particularly suited to machine learning solutions as much can be done to cut time and costs, leading to speedier resolution of claims to the satisfaction of both insurer and insured.
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.
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.
In order to enter into a new market, businesses must have an effective product adaptation strategy. This strategy is essentially the knowledge of what part of a product or service must be changed in order to appeal to local customers.
Adaptation differs from localization in that the former changes only surface-level factors.
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.
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.
The shelf is a dynamic environment, where shoppers select items purposefully and on impulse, where store owners showcase products to entice customers in the store and online.
Inventory management does not just entail having the right stock but also ensuring said stock was effectively sourced, stored, and sold at the right price, at the right time.
USA High School Student Marketing Database by ASL Marketing dataset provides information regarding: and more.
USA College Student Database – ASL Marketing dataset provides information regarding: and more.
Student Marketing Data – Reach Out to Students With Our Customizable Student Data dataset provides information regarding: and more.
B2C Contact Data – Global Contact List – Reach B2C Audience Globally With Our Verified 200M+ B2C Contact Data dataset provides information regarding: and more.
Small Business Contact Data – Reap Higher ROI With Our Small Business Owners Data dataset provides information regarding: and more.