Artificial Intelligence & Machine Learning , Fraud Management & Cybercrime , Fraud Risk Management

AI and Data Masking at Forefront of Fighting Financial Fraud

Financial institutions must address not only data security but also data warehousing and data governance issues to meet regulatory and compliance requirements. M-Pesa's Tim Theuri and Inq. Digital's Tunde Dada discussed the strategies they deploy to meet both security and privacy requirements.

See Also: Alleviating Compliance Pain Points in the Cloud Era

"We do a lot of data masking. We also do data loss prevention. With the data loss prevention technology, I have managed to prevent quite a lot of problems in terms of theft," Dada said, pointing to the need for regular auditing and logging of data. "You have to have the log of every activity and then review it, audit it and put measures in place to make sure everything is secure. Adding those things along with your regulatory compliance requirements will help you a lot."

Artificial intelligence can play a role in maintaining data integrity and data quality, Theuri said. "In M-Pesa, we use AI for fraud prevention. We can identify where fraud cases are happening or are about to happen and ensure that we take proactive actions by blocking them out of our network," he said.

In this video interview with Information Security Media Group, the two discussed:

• How to measure success in various cybersecurity initiatives;
• Ways to approach budgeting and cost management;
• The next big technological innovation.

Dada has more than 20 years of experience in global IT/BCM management and policy development. He has a passion for aligning security architecture plans and processes with security standards and business goals.

Theuri is a cybersecurity and risk professional with experience in the financial and telecommunication industries in cybersecurity, technology risk management, and information security audits.