AI and Data Science Consulting Services
“Rowzzy Neurons” is one of the machine learning initiatives. Our customer is spread across from healthcare to supply chain, from hospitality to energy, from finance to retail. We are in need to help them on decision making through prediction by using algorithms to identify patterns in their data and improve their experience.
We took historic procedures of our healthcare provider from their various centres and gave a recommendation of smart predictive procurement that saves their unwanted dump of inventory. It reduces a lot of time of the procurement manager’s time and the system has been improved with current appointment details.
You can do magic with the data from your customer preferences, between patient and doctor conversations, between sales support and customer resolutions, weather patterns, history of payments, drug trial results, booking details and insurance histories.
We can build your business efficiently and help you to make a better decision with the help of AI/ML capabilities. You can contact email@example.com for further support.
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Data Science in Healthcare Insurance
In 2005 Starbucks spent more on health insurance costs than on raw coffee beans (NBC). Handling and analysing healthcare data lead to a larger issue in modern life. For whatever reason, the expense drastically increases on chronic disease management, preventive care, and emergency care. Healthcare Insurance not only clutches the importance for individuals but for everyone as it has a greater impact on the safety of our lives and assets. Data Science wires the Mediclaim companies in taking the correct decisions by providing them with intuitive insights. With the computing power and a bucket full of technologies like data science, machine learning, chatbots, big data analytics and data warehouses the healthcare providers have a lot of opportunities to start introducing optimization and cost-saving methods everywhere.
Raw Data Collection
Data Analytics refers to gathering data from structured and unstructured database; this feature builds a crucial use case for the healthcare insurance company to pounce on. The insurance firms mount up streaming and unstructured data from the authorized resources and transforms into structured feature. Extracting structured information aids insurance companies in providing the detailed report on disease symptoms and preventive measures. The premium shoots up in accordance to offer coverage if the predictive model fails to alert. Raising the cover makes the customer feel more comfort when under the life insurance.
Gaining Customer Insights
The user’s knowledge and their requirement are the major resource to build the prediction model. BigData in addition to Machine learning model can store voluminous data (Giga – Ziga bytes), increase the processing speed, manage and access the information from various sources, which is linked directly to the user. This extracted data assists the insurance company in gaining the users insights, like the past mediclaim policies and the queries related to the insurance. Model built on Big data and machine learning have a structured data which aids the insurance company to focus on the customer experience.
Fraud detection is common at healthcare insurance. Machine learning based predictive models are more effective in detecting the abnormal patterns. The trained models will keep a record of the users past mediclaim and updates them at regular intervals to avoid the claim being fake. As soon as the predictive model identifies the claim to be fake, the system automatically stops the process and starts investigation towards the user.
The insurance company should be aware of all the possible factors that influence the customer from not filing the claim. Setting policy norms and premium turns out to be an easy process as the Machine Learning model generates a detailed report to the insurance company to analyse. For instance, when a customer claims an insurance policy, the company can analyse the information about the age factor, type of disease and the curable rate before fixing the premium for the customer to stay clear of any losses.
The healthcare insurance company does not have any physical product, but it has gained its importance since it benefits the customer on their social security. The insurance company can learn from different use cases and understand the significance of the predictive model.
Technologies we use
- Data Science
- Big Data
- Artificial Intelligence
Benefits of Data Science in Healthcare
- Advanced patient care
- Improve operational efficiency
- Finding a remedy for diseases
- Eliminates double claims for same diseases
- Establish digital certificate and reducing Counterfeiting
- Unlicensed brokers selling insurances and pocketing premiums
Schedule a meeting or arrange a call with our team to see how our business model can help you achieve your business goals.