Snippings

The Publicis Sapient Global Banking Benchmark is a longditudonal survey of more than 1,000 senior banking executives around the world and provides a useful insight into banking thinking and shifting priorities. The 2024 survey says that AI is kickstarting the next wave of digital transformation in banking and notes that banks are spending nearly one-third of their customer experience digital transformation investment on AI.

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Until now, manufacturers were expected to follow security guidelines, but the new law makes three new requirements:
that password procedures are more secure, including ensuring any set by the manufacturer are not left blank or using easy-to-guess choices like “12345” or “admin”
that there is clarity around how to report “bugs” or security problems that arise
that manufacturers and retailers inform customers how long they will receive support, including software updates, for the device they are buying
Failure to meet these minimum requirements, known as the Product Security and Telecommunications Infrastructure (PSTI) regime, can trigger fines.

From: Smart gadgets: Tougher rules for sellers of internet-enabled devices in the UK.

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On August 21, 2024, the National Institute of Standards and Technology (NIST) released its second draft for the fourth revision of the Digital Identity Guidelines. The revised draft guidance puts forth a risk-mitigating framework and requirements for “identity proofing and authentication of users (such as employees, contractors or private individuals)” accessing government services or interacting with government information systems online. Building off the first draft of the revised guidance, the latest draft now includes an entire section on AI in identity systems, recognizing both the benefits and risks that AI poses in identity systems and proposing three broad requirements to mitigate these risks.

From: NIST Releases Updated Draft Guidance for Federal Agencies’ Use of AI in Identity Verification Systems — AI: The Washington Report | Mintz – Antitrust Viewpoints – JDSupra.

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Balancing the benefits and risks of AI, the new draft guidance proposes three requirements for AI in identity systems, focused on transparency and risk mitigation:

 

Organizations that rely on AI would be required to document and communicate about their AI usage in identity systems. Identity providers and content security policies that leverage AI would be required to document and communicate their AI “usage to all [relying parties] that make access decisions based on information from these systems.”

Organizations that utilize AI would be required to provide certain information “to any entities that use their technologies,” including information about the techniques and datasets used for training their models, the frequency of model updates, and the results of any tests of their algorithms.

Lastly, organizations that utilize AI or rely on systems that use AI would be required to adopt the NIST’s AI Risk Management Framework for AI risk evaluation, and also consult the Towards a Standard for Managing Bias in Artificial Intelligence. Both NIST publications lay out practical steps to reduce AI bias, including using datasets with balanced statistical presentation, documenting potential sources of human bias into datasets, updating and testing AI models regularly, creating a fairness metric by which to evaluate AI models, and assembling diverse and inclusive teams to design and deploy AI systems.

A case study conducted by TELUS International (O’Niel. “How to use AI to shape efficient digital and omnichannel experiences.” Journal of Digital Banking 8(3): 256-262, 2023) noted an improvement in customer satisfaction scores by 40%, a decrease in average call handling time by 9% and a significant reduction in human involvement in mundane tasks after implementing intelligent automation solution for the customer services agents in a financial services client. Personally, I don’t really care whether I am chatting with a bot or not, so long as I get the service I want, so I can such deployments spreading rapidly.

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It seems to me these examples illustrate my theory that in day-to-day life there are only two categories of retail financial transactions. There are the transactions that are too boring for people to do and transactions that are too complicated for people to understand. In both cases, the bots stand ready to help and given the rapid advances in technology, I don’t think I’ll have to wait too much longer before I can stop thinking about transactions completely.

From: ChatGPT Is A Window Into The Real Future Of Financial Services.

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It is worth noting that Elon’s role as part of PayPal is sometimes over-exaggerated. He took on the role of CEO of PayPal after the Confinity/X.com merger, but PayPal was already a product with reasonable traction with eBay prior to his arrival, and he lasted only a short time as CEO before butting heads with employees and the board. He undoubtedly provided crucial expertise as part of their growth but not the core figure in the ideation of PayPal that some think of.

From: PayPal: A Fintech OG rejoining the Fastlane.

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Specialist officers then undertook comprehensive analysis of Shu and Huang’s mobile phones, revealing that the pair were using a Chinese messaging app to sell British pounds to university students to circumnavigate foreign currency controls which limits the amount of cash that can be taken out of China per year.

The messages also identified that Shu and Huang were working for a person with the user handle ‘There is a Big Sun in the Sky.’ This person arranged for the pair to collect large amounts of cash, sometimes as large as a quarter of a million pounds at a time.

Shu and Huang were not told the identities of those they collected cash from, and were instructed to take a photo of a £5 bank note, including the unique serial number. This was then passed onto the courier allowing the interaction to take place without either party knowing the identity of the other.

This was done by the group to prevent those in the chain giving information to police if they were arrested.

From: NEWS: Detectives in UK break up sophisticated £55m Chinese underground banking laundry, student money mules at its heart | LinkedIn.

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A report produced by digital identity company Signicat (disclosure: I co-wrote the forward to the report) shows how bad the situation is. They commissioned a survey of industry prractioners across Europe to see what is happening on the ground right now and found that (along with, much to my surprise, that only two-thirds of the those questioned thought that AI-driven identity fraud is a bigger threat today than it was three years ago!) the decision-makers in the fraud world as confused about the nature of the threat, the impact of attacks and the countermeasures that might be avilable.

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Using AI, financial institutions can elevate their omnichannel approach, ensuring a seamless and personalised customer journey across a diverse set of interactions.

From: How to use AI to shape efficient digital and omnichannel experien…: Ingenta Connect.

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A case study conducted by TELUS International noted an improvement in customer satisfaction scores by 40 per cent, a decrease in average handle time by 9 per cent, and a significant reduction in human involvement in mundane tasks by implementing a comprehensive intelligent automation solution for a financial services client that provided their customer service agents with 24/7 support when responding to customer queries.3 This resulted in a win-win for both the company and the customer.

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While the threat associated with chat bots stems from the web-based implementation of an AI-powered system, such systems are also associated with inherent vulnerabilities. A major concern is that hackers may embed fraudulent mechanics in AI engines by feeding them fake data.

From: Full article: Artificial Intelligence and Cyber Defense System for Banking Industry: A Qualitative Study of AI Applications and Challenges.

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employed AI-based tools have vulnerabilities that can be exploited

From: Full article: Artificial Intelligence and Cyber Defense System for Banking Industry: A Qualitative Study of AI Applications and Challenges.

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