Business driven Artificial Intelligence and Data Science Solutions for the Insurance Industry

Summary and Readiness Check

Are you challenged to unlock the potential of your data and make use of Artificial Intelligence (AI), Data Science and Machine Learning? Insurance Companies will be affected by Artificial Intelligence during the next years according the McKinsey Report from March 2021 "Insurance 2030 - the impact of AI on the future of insurance".  As a PhD Expert Team for AI, Data Science and Machine Learning Development we can build the solution that is solving your business challenges. We are already recoginzed with several awards for our individual solutions.

What we need from you to proceed?

  • Your interest or even your Roadmap in Artificial Intelligence, Data Science, Machine Learning
  • We need your Data

Are you ready to proceed?

It is a fundamental strategic decision as a company to invest in AI. Without a doubt, this decision must be well prepared. As a PhD team of experts, we are there for you to implement your AI, data science and machine learning projects. Learn more about our Value Proposition.

As an awarded AI, Data Science and Machine Learning Service Provider we would like to share with you our AI Superior Expertise Paper.

If you are currently dealing with the question if outsourcing of your AI projects is a good option than we would recommend you our Expert Blog Post Why You Should Outsource Your Data Science Tasks

Challenges in the Insurance Industry

The pressure to drive one's own digitization or digital transformation does not stop at the insurance industry either. Artificial Intelligence (AI), Data Science and Machine Learning my be key to drive insurance digital transformation. Although various studies say that the insurance industry is currently still concentrating on Robotic Process Automation, as the IT Infrastructure in insurance companies is not yet fully prepared for Artificial Intelligence, Data Science and Machine Learning Solutions.

We from AI Superior see a challenge in the fact that AI and Data Science was and is a hype and we recognized that decision makers don't trust AI and Data Science. It seems to be only accessable for big players like google, Amazon etc. We are working on this challenge and we can show you that AI and Data Science can also bring value to insurance companies.

Solution by AI Superior

We are helping you to solve Business Challenges like:

Effective Risk Management

  • Machine Learning modelling and Data Preparation for Underwriting
  • Interpretability of AI Model Decisions
  • Behavioral Analysis
  • Data Enrichment Services

Efficiency-focused Optimization

  • Pricing Policy and optimization of business relevant KPIs
  • Customer Churn Prediction and Retention Strategy assessment

Claim Processing Automation

  • Car damage control and examination, repair costs estimation
  • Property assessment and evaluation
  • OCR -based claims processing automation

Deep Dive in Business Challenges and our Expertise

Machine Learning and Data Preparation for Underwriting.

Practical experience and theoretical background allow us to properly represent various types of heterogeneous data into ready to use machine learning data sets. We perfect the art of feature engineering for time-series data, financial transactions, spatiotemporal information, behavioral patterns and many more. A high-quality risk scoring model is one of the key success factors in risk management. Our PhD level data scientists in Machine Learning can train and properly validate a Risk Scoring Model that will have a comprehensive view of the insured.

Pricing policy and optimization of relevant business KPIs.

Are you looking for a higher number of customers and are ready to take more risk or rather to stay risk-averse and optimize the profitability with other means e.g. increasing the premium? All these relevant questions for Underwriting, Finance and Marketing can be answered with the help of Data Science by optimization algorithm to further improve the Unit Economics of your Business.

Interpretability of decisions by AI Models

Due to a high number of variables and complexity behind modern machine learning algorithms, it is hard to interpret the reasoning and decisions made by machine learning models. AI Superior can help to overcome this issue. We can provide a tool that gives an explanation either over the whole population or for an individual customer. We work with a wide variety of methods to name a few: Neural Networks, Gradient Boosting, Random Forest.

Behavioral analysis

To understand your customers behavioral patterns and risks associated with them, AI Superior offers a behavioral analysis package. Based on sophisticated machine learning models it allows you to get deeper insights into your customers behavior, segment them based on their assignment to a particular risk group and take relevant actions. A typical example of application of such an analysis is a driving style scoring where the behavior of every driver is analyzed in order to obtain driving profiles and risk of an accident associated with them. Such analysis requires telematic data obtained from an installed sensor or a smartphone. Alternatively, in other scenarios, data might be coming from social media, IoT devices, system logs and others.

Data Enrichment Services 

AI Superior helps to improve the predictive power of your models by providing Data Enrichment Services. It includes data enrichment and data fusion modules allowing to collect, fuse and streamline various heterogeneous data to your AI applications. This enables many use cases such as:

  • Geospatial-based risk indices generation to explore districts and regions on the map and consume demographics, governmental statistics, public information and infrastructure-related insights
  • Satellite imagery-based data for hazard assessment of property e.g. fallen trees or flood prediction, crises prediction and others.