Unleashing the power of AI to prevent financial crime

ING's AI system stops 70% of fraudulent transactions before funds even leave the bank.

Unleashing the power of AI to prevent financial crime
#1about 5 minutes

Using AI to combat financial crime at ING

ING uses AI in areas like transaction monitoring and customer experience, focusing on fraud detection and transaction categorization.

#2about 5 minutes

Understanding credential theft through phishing attacks

Fraudsters use phishing emails to steal login credentials, gain control of an account, and initiate unauthorized transactions that appear legitimate.

#3about 6 minutes

Implementing a two-step fraud detection solution

A hybrid approach combines a rule-based system for initial checks with a machine learning model for anomaly detection based on customer behavior.

#4about 6 minutes

Categorizing transactions to improve customer experience

Transactions are categorized differently based on whether they are card payments, which use merchant codes, or non-card payments, which rely on machine learning models analyzing transaction descriptions.

#5about 4 minutes

Solving the challenge of multilingual transaction data

Machine learning models struggle with transaction descriptions in multiple languages, as performance degrades for minority languages with less training data.

#6about 4 minutes

Creating a scalable translation mapping solution

A custom translation table is built by identifying frequently occurring keywords in the majority language and mapping them to their equivalents in minority languages, improving model accuracy.

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Jobs that call for the skills explored in this talk.

Data Engineer

Data Engineer

ING Bank
Frankfurt am Main, Germany

ETL
Kafka
Python
Google BigQuery
Machine Learning