Predictive analytics is one of the major branches of data science that is concerned with using statistical tools and techniques to make accurate predictions about future events. Machine learning, artificial intelligence and more can be used to effectively implement predictive analytics in a number of situations. By providing the best assessment for what might happen in the future, you increase your current bottom line and enjoy a significant competitive benefit. The volume of data is very high and effective data processing will allow you to access valuable and deeper insights.
Stream analytics is another element of predictive analytics software, where data is collected from a set of connected devices on the same network. Stream analytics has a major application in the world of Internet of Things (IoT), where sensor data can be analyzed in real time to provide users with actionable insights. IoT data and predictive analytics can be used in home innovation, by using data to figure out what the optimum home environment must be. Air conditioning, lighting, appliances, etc. can all be optimized by using powerful predictive analytics tools.
1. Mortgage Process Automation: With increasing regulatory and operational changes, many mortgage lenders have shifted to an automated version of the mortgage process. Loan process automation can be implemented to make the mortgage process simpler, cleaner and faster. This will make life much easier for any new homeowners who want to take out a loan to purchase their own home.
In loan process automation, a special AI or machine learning system is trained to perform a set of mundane tasks that would originally be performed by someone at the lender. These automated systems are perfectly capable of navigating systems and performing the tasks very quickly and effectively. By 2020 end, mortgage process automation is expected to grow by 60.5%.
2. Claim Processing in Healthcare: The global health industry is worth more than $6700 billion and is expected to grow at a compounded rate of 9.3% annually. In the healthcare industry, the processing of medical insurance claims is one of the most important tasks. It is tedious and is also one of the most time consuming tasks out there.
The single payer healthcare system can benefit greatly from predictive analytics and automation. In recent times, there have been major efforts to automate the claim processing sector of the medical insurance industry. This will allow them to expedite claims quickly and the entire workflow will also become very efficient. Fraud detection can also be conducted by using predictive analytics tools.
3. Smart Appliances and Home Systems: By leveraging the immense potential of IoT tech, home systems can be enhanced and major innovation can also be carried out. Smart appliances and home systems such as smart TVs, smart fridges, etc. can be used to create an enhanced home experience for people. All this can be done by using predictive analytics methods.
In the world of home innovation, applied technology services can be used to create predictive analytics models that analyze sensor data and provide residents with the optimum home environment. By using tools like Alexa and Google Assistant, people can now control the lights, appliances, temperature and more. In recent times, even mattresses and bathroom appliances can be enhanced and automated.
4. Fraud Detection in Finance: The detection of financial fraud is very difficult, especially if it is conducted by someone who is inventive and cautious. It is not possible for human auditors to analyze exabytes of financial data and discover instances of fraud. Machine learning algorithms can be used to create predictive analysis engines that can successfully detect financial fraud.
Potential security threats in the world of finance, such as duplicate payments, credit card fraud, unnatural credit card activity, etc. can be easily discovered with the proper application of automated technology. Fraud is constantly evolving and that is why methods need to be applied that are just as inventive and original. Only then can it be brought under control effectively.
5. Improve Retail Bottom Lines: Retail is quite possibly the largest sector in the world that makes use of predictive analytics, and this usage has a significant impact on the field of home innovation as well. Firms like Amazon make use of predictive analytics to model consumer behavior and make recommendations for products/services that they might end up buying.
Sales forecasting and market analysis can also be conducted with the help of predictive analysis engines. It is very important to remember that predictive analytics is a powerful tool that can be used to enhance almost every existing business process there is. It can also be used to make the entire process of inventory management much easier to carry out.
These are the various ways in which predictive analytics can have a major effect on innovation at home and in the workplace. Automation and predictive engines can make life much easier for everybody, and should be welcomed with open arms. By setting up an innovation ecosystem, life can become easier for everyone.
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