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Artificial Intelligence in Insurance

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 may be key to driving insurance digital transformation. Although various studies show that the insurance industry is currently still concentrating on Robotic Process Automation, the IT infrastructure in insurance companies is not yet fully prepared for Artificial Intelligence, Data Science and Machine Learning Solutions, and Machine Learning Algorithms.

At AI Superior we understand that AI and Data Science pose a challenge, and we recognize that decision-makers don’t always trust AI and Data Science. It may seem that machine learning solutions are only accessible for big players like Google or Amazon, but we are working on this challenge, and we can show you that AI and Data Science can also bring value to insurance companies.

What can AI do for the Insurance Industry?

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Most common AI Use Cases

Effective Risk Management

Machine Learning modelling and Data Preparation for Underwriting

Interpretability of AI Model Decisions

Behavioral Analysis

Data Enrichment Services

Claim Processing Automation

Car damage control and examination, repair costs estimation

Property assessment and evaluation

Car damage control and examination, repair costs estimation

Efficiency-focused Optimization

Pricing Policy and optimization of business-relevant KPIs

Customer Churn Prediction and Retention Strategy assessment

Customer success stories
Our Projects

Road Entities Recognition and Traffic Analytics

Social Media Analytics for Marketing Activities

Road Entities Recognition and Traffic Analytics

Our Project Approach

The AI ​​project lifecycle has been adopted from an existing standard used in software development. Also, the approach takes into account the scientific challenges inherent in machine learning projects involving software development processes. The approach aims to ensure the quality of development. Each phase has its own goals and quality assurance criteria that must be met before the next stage can be initiated.

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