Post by account_disabled on Jan 13, 2024 5:40:24 GMT
Identity before continuing to assist us. After all, we don't want banks handing out our money (or our new debit card) to just anyone. Historically, this phone authentication process involved answering a set of questions. What is your account number? What is your PIN? What is your social security number? Can you verify the last three transactions in your account? What was your previous address? The process continues, possibly escalating into a security challenge based on the shared secret, until the bank is convinced of our identity. The process is adversarial by design. Even the name Security Challenge Issue evokes a combative stance, a challenge. The originator of the call is not trusted until it has been tested. Unfortunately for banks, many initial interactions with customers are hostile in nature.
About the author is an associate professor of information systems at Boston College's editor of the MIT Sloan Management Review's Big Ideas in Data and Analytics program. You can contact him at and . Tags: Customer Data Cybersecurity Data Security More like this Leveraging Generative AI for Marketing: Harvard Business School’s What Managers Should Ask About AI Models and Datasets How Developers Can Reduce AI’s Climate Impact Generative The Impact of Artificial Intelligence on Hollywood and the Entertainment Industry Thomas Email Lists Database Davenport and Randy Bean You must be logged in to post a comment. First time here? Sign up for a free account: comment on articles and access more articles. Comments by Chandra Pandey Year Month Day Interesting article, when evaluating how cross-cutting issues interact in user experience, it's important to understand that risk and security are different. Of course, when the stakes are high.
The gravity of the minimum viable window becomes a business issue, locking everything in. The solution somewhere lies in having the building blocks of a federated security service supported by integrated risk modeling that can classify transactions at runtime to enable additional security as a multi-factor approach. Unfortunately, industry and standards bodies have not invested enough time, effort, and funding into risk modeling as a science to develop an ecosystem of automated yet intelligent transaction processes. The security business is focused on ideas for new safe vaccines.
About the author is an associate professor of information systems at Boston College's editor of the MIT Sloan Management Review's Big Ideas in Data and Analytics program. You can contact him at and . Tags: Customer Data Cybersecurity Data Security More like this Leveraging Generative AI for Marketing: Harvard Business School’s What Managers Should Ask About AI Models and Datasets How Developers Can Reduce AI’s Climate Impact Generative The Impact of Artificial Intelligence on Hollywood and the Entertainment Industry Thomas Email Lists Database Davenport and Randy Bean You must be logged in to post a comment. First time here? Sign up for a free account: comment on articles and access more articles. Comments by Chandra Pandey Year Month Day Interesting article, when evaluating how cross-cutting issues interact in user experience, it's important to understand that risk and security are different. Of course, when the stakes are high.
The gravity of the minimum viable window becomes a business issue, locking everything in. The solution somewhere lies in having the building blocks of a federated security service supported by integrated risk modeling that can classify transactions at runtime to enable additional security as a multi-factor approach. Unfortunately, industry and standards bodies have not invested enough time, effort, and funding into risk modeling as a science to develop an ecosystem of automated yet intelligent transaction processes. The security business is focused on ideas for new safe vaccines.