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Self Paced

AI for Fraud Detection in BFSI

Ensuring Financial Integrity with AI-Powered Fraud Detection

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Enroll now for early access of e-LMS

MODE
Online/ e-LMS

TYPE
Self Paced

LEVEL
Moderate

DURATION
3 Weeks

About

This course aims to equip participants with advanced knowledge and skills in utilizing artificial intelligence to detect and prevent fraud within the Banking, Financial Services, and Insurance (BFSI) sector, focusing on practical applications and cutting-edge technologies.

Aim

Program Objectives

Understand the fundamentals and advanced concepts of AI as they apply to fraud detection.
Analyze various types of financial fraud and the role of AI in combating these activities.
Develop hands-on skills in data handling, machine learning models, and AI strategies specific to fraud detection.
Explore the ethical and regulatory aspects of using AI in financial environments.

Program Structure

MODULE 1 : Introduction to AI and Fraud Detection

Basics of AI in BFSI.
Types and impacts of financial fraud.
Evolution of fraud detection technologies.

MODULE 2 : Mastering Data Handling & Preprocessing for AI in BFSI

Data collection and preprocessing techniques.
Feature engineering and data quality’s impact on fraud detection.
Practical exercises on real financial datasets.

MODULE 3 : Machine Learning Models for Fraud Detection

Application of supervised learning models like decision trees and logistic regression.
Advanced models including random forests and gradient boosting machines.
Building, training, and evaluating models for fraud detection.

MODULE 4 : Deep Learning and NLP for Fraud Detection

Using neural networks and NLP to detect complex fraud patterns.
Practical application of deep learning in real-world fraud detection.
Integration of NLP techniques into fraud detection projects.

MODULE 5 : Anomaly Detection and Behavioral Biometrics

Techniques for identifying anomalies and behavioral patterns.
Application of behavioral biometrics in fraud prevention.
Hands-on case studies and project work on anomaly detection.

MODULE 6 : AI in Fraud Detection: Case Studies and Regulatory Compliance

Examination of real-world applications and case studies.
Navigating legal and ethical considerations.
Regulatory compliance affecting AI fraud detection systems.

MODULE 7 : Developing an AI Fraud Detection Strategy

Strategic considerations for implementing AI in fraud prevention.
Emerging technologies in AI fraud detection.
Design and implementation of AI strategies in financial institutions.

Participant’s Eligibility

This course is intended for professionals and students in the BFSI sector seeking to enhance their expertise in AI-driven fraud detection and financial integrity.

Program Outcomes

Mastery of AI technologies for detecting and preventing fraud in BFSI.
Practical experience in applying AI to real-world fraud detection scenarios.
Enhanced understanding of the regulatory and ethical frameworks governing AI use in finance.

Fee Structure

Standard Fee: INR ~~4,998~~ USD 78

Discounted Fee: INR 2,499 USD 39

We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!

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Key Takeaways

Program Assessment

Certification to this program will be based on the evaluation of following assignment (s)/ examinations:

Exam	Weightage
Mid Term Assignments	50 %
Project Report Submission (Includes Mandatory Paper Publication)	50 %

To study the printed/online course material, submit and clear, the mid term assignments, project work/research study (in completion of project work/research study, a final report must be submitted) and the online examination, you are allotted a 1-month period. You will be awarded a certificate, only after successful completion/ and clearance of all the aforesaid assignment(s) and examinations.