TRAINING COURSE
AI in Insurance: Risk Assessment and Fraud Prevention
STARTING TWICE A MONTH
DURATION 7 WEEKS
‎‎ ‎9 000 €
This course is designed for professionals in the insurance industry, including underwriters, risk assessors, fraud prevention specialists, and data analysts, who want to leverage AI for improving risk assessment, fraud detection, and process automation. It caters to individuals interested in applying ML, DL, and NLP to analyze data, detect fraud, and streamline insurance processes.
AI-Driven Risk Assessment
AI for Fraud Detection
NLP in Insurance
Training Course Program
STARTING TWICE A MONTH
Lecture 1:
Fundamentals of AI
  • Definition of AI
  • History of AI development
  • Main directions of AI: Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP)
  • Examples of AI applications in different industries
Lecture 2:
Application of AI in Insurance
  • Overview of AI application in the insurance industry
  • Examples of successful cases of AI application in insurance: risk assessment, process automation, forecasting
  • Impact of AI on efficiency and accuracy of insurance processes
Lecture 3:
DL and its applications
  • Introduction to DL
  • Neural networks and their architectures: CNN, RNN, LSTM
  • Examples of using DL in insurance: image, text, time series processing
Lecture 4:
NLP in Insurance
  • Basic NLP techniques: tokenization, stemming, lemmatization, text vectorization
  • Application of NLP in insurance: analyzing customer feedback, processing insurance documents, chatbots
Lecture 5:
Data analysis for insurance risk assessment
  • Introduction to data analysis
  • Data collection, cleaning and preparation
  • Data analysis techniques: descriptive statistics, correlation, regression
  • Examples of data analysis in insurance
Lecture 6:
Using AI for fraud prevention
  • Types of fraud in insurance
  • Methods of fraud detection using AI: anomaly analysis, clustering, predictive models
  • Examples and cases of using AI for fraud prevention
Lecture 7:
Ethical and legal aspects of the application of AI in the insurance industry
  • Ethical issues in the use of AI: transparency, bias, confidentiality
  • Regulatory requirements and regulations
  • Risk management in AI implementation
Lecture 8:
The future of AI in insurance
  • Trends and prospects for AI in insurance
  • Innovative technologies: blockchain, Internet of Things (IoT), robotization
  • How to prepare for and adapt to future changes
Practical Session 1:
Introduction to working with data
  • Collecting data from a variety of sources
  • Cleaning data from errors and omissions
  • Preparing data for analysis and visualization
Practical Session 2:
Applying ML to risk assessment
  • Selection of ML algorithms
  • Training and tuning models on trained data
  • Evaluating the accuracy and quality of the models, analyzing the results
Practical Session 3:
Using NLP to analyze textual data
  • Pre-processing textual data using NLP
  • Building and training models to analyze textual data
  • Applying models to analyze customer feedback and insurance documents
Practical Session 4:
Fraud detection using AI
  • Applying anomaly analysis and clustering techniques to detect suspicious cases
  • Building and training models for fraud detection
  • Evaluating the effectiveness of methods and models, developing fraud prevention strategies
What kind of result will you get

Participants will be equipped with advanced skills in using AI to enhance risk assessment, streamline fraud detection, and leverage NLP for analyzing insurance-related data. They will gain practical experience in applying ML algorithms and DL models to improve accuracy and efficiency in insurance processes, as well as a deeper understanding of ethical and legal considerations associated with AI in the industry.

Student feedback on the course
The course provided clear and actionable insights into AI applications.
Dragomir Novotný
Hands-on experience with AI tools was highly beneficial and practical.
Milena Kostka
Excellent content on emerging AI trends and their industry impact.
Vladislav Černý
Thorough exploration of ethical and legal considerations in AI.
Svetlana Dražic
Valuable skills and knowledge for applying AI effectively.
Zdenek Lukavský
What you will get after the course
  1. AI-enhanced risk assessment skills
  2. Expertise in fraud detection using AI
  3. Proficiency in NLP for insurance
  4. Practical experience with ML and data analysis
  5. Understanding of ethical and legal AI considerations
Official school certificate
Recordings of all lectures
10% discount on any of our courses
Price without discount 10 000 €
9 000 €
Course fees
If you register early (over a month prior to the beginning of the course), you will receive a 10% discount on the entire program.
Register for the course and get 10% off!
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"Cosmopolitacademy" LLC
264.110.1320023
TIN: 08256519
Komitas 19/1, Erevan, Armenia