Data Science in Insurance
Data science is the practice of taking the data that companies generate over time, analyzing it, and using the results to improve your future decision making. This is a critical facet to any software development process which should help to create valuable decision-making tools.
Common data science and analytics efforts include:
- Segmenting businesses to identify the most profitable products or services
Evaluating your historical data sets to predict future success factors
Reviewing third party data to enrich your data density
Running simulations to forecast the probability future events
Analyzing performance data as part of A/B software testing
Assessing at your customer’s performance data to better cater your products and services to their needs
Jaroop’s Approach to Data Science
Jaroop buckets data into three different types.
- Structured Data is organized and usually tabular. For example, employee and customer information like names connected to phone numbers and addresses in relational databases.
- Semi-structured Data has a self-describing structure in the form of tags, markers or key-value pairs that separate semantic elements and create hierarchies of records and fields. Examples include data in CSV, XML and Json formats.
- Unstructured Data consists of photos and videos, satellite imagery, radar, mobile, and various types of textual data such as web and social media content.
Jaroop’s data scientists focus mostly on creating solutions for semi-structured and unstructured data. Using programming, Natural Language Processing (NLP), statistics, data mining, machine learning, and visualization, combined with techniques from other disciplines, we can interpret and draw conclusions the complex data.