Artificial Intelligence in Insurance

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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.

Most common AI Use Cases

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Effective Risk Management

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    Machine Learning modelling and Data Preparation for Underwriting

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    Interpretability of AI Model Decisions

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    Behavioral Analysis

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    Data Enrichment Services

Claim Processing Automation

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    Car damage control and examination, repair costs estimation

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    Property assessment and evaluation

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    OCR-based claims processing automation

Efficiency-focused Optimization

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    Pricing Policy and optimization of business-relevant KPIs

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    Customer Churn Prediction and Retention Strategy assessment

Our Projects

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Road Entities Recognition and Traffic Analytics

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Category

CV, Core ML

Client

System Integrator

Potential industries

Retail

Industry

Government
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Social Media Analytics for Marketing Activities

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Technology

Core ML

Client

Bank

Potential industries

Retail, Telco, Insurance, Education

Industry

Government
AI in the Real Estate Industry

Road Entities Recognition and Traffic Analytics

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Technology

Core ML

Client

Real Estate Company

Potential industries

Retail

Industry

Real Estate
Graphic showing the AI Project Lifecycle

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.

Deep Dive in Business Challenges and our AI Expertise

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