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.
Language revitalization refers to the process of bringing a dead or dying language back into common usage. It is also called language revival, although many believe the term “revival” should only apply to dead languages and “revitalization” to dying ones.
Language reclamation is a related concept and frequently occurs together with revitalization/revival. However, it refers only to the process of a population reasserting its right to speak its language.
As organizations continue to adopt IoT technology, ensuring secure access to a private network becomes particularly difficult. Network access control systems, however, protect network data by requiring user authentication and authorization before every request.
These systems also proactively address security breaches, though many also integrate with anti-virus or malware systems that organizations already use.
Network segmentation refers to the act of dividing different parts of a network into separate segments or subnets. This is done either physically or technologically, usually as part of a network access control system that limits who can access what parts of the network.
Once organizations have identified subnetworks, they establish virtual fences around them using a variety of techniques, including VLANs, SDNs, and firewalls.
A large proportion of data breaches come from authorized network users. Since they have network privileges, however, this type of cybersecurity threat is extremely difficult to address. Insider threat detection comprises the methods and technologies that organizations use to identify and mitigate these insider threats.
There are various types of insider threats, not all intentional or malicious. Pawns, for example, are simply victims of phishing or other social engineering traps while Goofs lost confidential data due to ignorant or arrogant flaunting of security policies. The malicious types of insider threats come from Collaborators and Lone Wolves, who are rarely encountered.
Taking the place of an in-person managers, a financial robo-advisor provides personalized investment and wealth management services to individuals as well as small and medium-sized businesses.
Robo-advisors use deep learning and other artificial intelligence techniques to offer advice and even automate trades in a variety of industries and account types, from individuals with retirement accounts to small businesses with equity finance plans.
VR therapy is the use of virtual reality equipment and programs within a therapeutic setting, sometimes as the primary therapy used, to address both mental illness and physical injury. In many cases, VR headsets are used in combination with biometric sensors like heartbeat or electrodermal activity sensors.
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.
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.
The abundance of job seekers nowadays leads many companies to use machine learning throughout their recruitment process. Some examples of this can be found in the fields of talent management, talent attraction, and candidate selection.
Talent management entails understanding the best fields, positions, and backgrounds to set talent up for success. Talent attraction selects the top outlets and channels for attracting the most suitable employees. Finally, candidate selection use neuro-linguistic programming (NLP) tools on CV’s to find suitable candidates.
CoreLogic’s Consumer Disputes Resolution provides free access to FCRA (Fair Credit Reporting Act)-compliant credit information. CoreLogic offers investigative and consultation services to individuals, with a readiness to correct missing or mistaken bureau data.
DataX Know Your Customer provides data to better asses consumer risk assessment.
Twenty Billion Neurons Crowd Acting platform enables your own interactive AI to train using large and and diverse datasets.
Wiser Solutions Retail Auditing And Mobile Crowdsourcing provides actionable insights on in-store sales performance, competitors, and consumer behavior.
Grandata Social Universe provides coded information about consumers, including locations, and spending habits to paint a rich picture about how consumers make purchasing decisions.