Monday, November 29, 2021

OzTech: CBA gets machine learning to tackle abusive messaging; Smart city tally ranks 5 Australian cities; Australia and Finland to exchange supercomputer information


Commonwealth Bank gets machine learning to solve abusive messaging issues

Eighteen months after finding a large number of abusive messages attached to customers’ transactions with each other, the Commonwealth Bank of Australia (CBA) is implementing machine learning to detect abusive behaviour in transaction descriptions within the CommBank app and Netbank.

In June 2020, CBA had found more than 8,000 transactions received by customers to contain “potentially abusive” messages. “All genders were sending and receiving these messages, but the nature ranged from fairly innocuous ‘jokes’ using profanities to serious threats and clear references to domestic and family violence,” said Catherine Fitzpatrick, CBA’s general manager of community and customer vulnerability, at the time.

CBA started blocking transactions that contained offensive language in transaction descriptions. The bank found at the time that often transactions—for amounts as low as $1—would be used for the sole purpose of harassment.

Among 100,000 blocked transactions, what the bank called the ‘new AI model’ has identified 229 unique senders of potentially serious abuse, which were then manually reviewed to determine severity and the appropriate action required from the bank.

This AI model combines a range of machine learning techniques and adapting capability developed by Google. “For example, natural language processing (NLP), is used to transform all transaction descriptions sent between individuals, and the results are assessed for many factors, including how toxic or emotional the language is,” said CBA chief decision scientist Dan Jermyn. “This is then combined with further data points to understand patterns of transactional behaviour between customers. Billions of transactions can be assessed, from which we are able to predict those cases that are highly likely to require attention. The use of machine learning also allows us to adapt to results and become increasingly effective over time.”

Smart city tally ranks 5 Australian cities

Five Australian cities have been ranked in a smart city tally that considered 150 cities across the world across four areas. The Cities of the Future Index was performed by EasyPark Group

Copyright © 2021 IDG Communications, Inc.



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