FT.com, February 15, 2024.  How Gen AI will change asset management…With time, the most dynamic and successful parts of the asset management will combine Gen AI enabled tools with new capabilities that, importantly, are Gen AI native….

CNBC, February 14, 2024. Generative AI financial scammers are getting very good at duping work email.

• Even companies that ban employees from using generative artificial intelligence are falling prey to financial scams that deploy the technology and amplify traditional phishing techniques used by hackers.
• Armed with tools like ChatGPT or its dark web equivalent FraudGPT, criminals can easily create realistic videos of profit and loss statements, fake IDs, false identities or even convincing deepfakes of company executives using their voice and image.
• A recent scam that cost a Hong Kong-based company over $25 million shows how convincing the crimes have become and how difficult it is to detect them.

FT.com, February 14, 2024. What the birth of the spreadsheet can teach us about generative AI [read free]. Lessons from an earlier software tool that changed the world. When the spreadsheet launched in 1979, it was a bewildering piece of software. People had no idea what they were looking at. A computer screen, filled with a grid of numbers? As Keith Houston explains in his new history of the pocket calculator, Empire of the Sum, they hadn’t realised that the rows and columns of a spreadsheet could be functional rather than decorative. Accustomed to writing numbers by hand on an 11-by-17 inch sheet of gridded paper designed for accountancy, they would type the same numbers into the computer grid and then do what they had done for the past couple of decades: figure out the sums with a calculator.

FT.com, February 14, 2024. Tech companies axe 34,000 jobs since start of year in pivot to AI. [read free] Microsoft, eBay and PayPal have each cut thousands of jobs since the start of the year…Analysts said the latest wave of lay-offs showed companies were reshuffling their resources in order to invest in new areas such as generative AI while also showing shareholders there was a continued focus on cost discipline.

Quartz, February 14, 2024. AI will judge your entire financial life and Moody’s is stoked about it. The credit-rating firm provided a window into how generative AI could change its business.

Forbes, February 14, 2024. How Financial Services Firms Can Build A Generative AI Assistant. Generative AI assistants are coming to financial services – and this new technology will change the way consumers manage their money and interact with human experts. Following on from last week’s article, this piece will provide an outline of how financial services firms can build a client-facing generative AI assistant. We’ll first summarize the three main build options: a more “off-the-shelf” turnkey solution, an open source large language model (LLM), or a proprietary LLM. We’ll then talk about the importance of ensuring the assistant offers strong conversational capabilities, low latency, and has proper guardrails in place.

NextGov/FCW, February 13, 2024. SEC Chair: Existing financial law can be applied to AI regulatory debate. The Securities and Exchange Commission could have an avenue for regulating artificial intelligence based on existing securities law, particularly surrounding the usage of AI-based financial tools and how brokers may need to navigate an automated trading environment, according to Chair Gary Gensler.  Speaking during a forum at Yale, Gensler discussed his agency’s potential role in providing oversight of firms that use retail investing technologies. “We at the SEC take investor education very seriously,” he said. “The robo-advising platforms and brokerage platforms affirmatively put educational material on their site. What their obligation is, is to make sure that when they do that, it’s accurate and not misleading.” He clarified that it is likely not within the SEC’s purview, drawing on existing securities law, to require financial firms to offer education if they decide not to. But should investment firms use AI and machine learning models to aid in certain decisions, Gensler said they should abide by basic disclosures with clients. “Investor protection requires that the humans who deploy a model …put in place appropriate guardrails,” he said. “If you deploy a model…you’ve got to make sure that it complies with the law.”

Forbes, February 7, 2024. Fighting Financial Crime With AI Is Not A Trend—It’s A Necessity. The most recent geopolitical turmoil, fueled by the financing of terrorism, has brought to light the real-world impact of financial crime and the need to prevent money laundering. The repercussions for the people and financial institutions involved can be detrimental—and regulators are actively addressing these issues. In the recently released annual Examination Priorities, the Securities and Exchange Commission (SEC) elevated money laundering as a top risk area for 2024, calling out customer due diligence and beneficial ownership compliance in particular. Several major banks were on the receiving end of enforcement action from regulators in 2023, and the recent penalty against Binance highlighted the severe consequences of compliance failures. Banking compliance leaders are facing changing regulatory frameworks and scrutiny, economic uncertainty, growing geopolitical risks and the unprecedented sophistication of financial criminals.

MIT Technology Review, February 6, 2024. Building innovation with blockchain. Deploying blockchain technology can bolster innovation and create a more secure way to bank, according to Suresh Shetty, the CTO at Onyx by J.P.Morgan at JPMorgan Chase.

Bloomberg via Yahoo Finance, February 6, 2024. The world’s longest-serving central bank governor, Romania’s Mugur Isarescu, was the target of a deepfake video depicting the policymaker as touting fraudulent investments. From a report: The episode highlights a raft of disinformation designed to undermine the credibility of key institutions. The video echoed similar deepfakes in recent days, including one aimed at Prime Minister Marcel Ciolacu, seeking to back false financial investments. The National Bank of Romania issued a warning, reminding citizens that neither Isarescu nor the central bank make investment recommendations. The video uses the image and voice of the central banker — one of the most trusted officials in Romania — to pitch stock investments and offers viewers a link to a fraudulent platform. “We are extremely concerned about the significant rise of these types of fraud attempts and we urge people to be very careful with every transaction that they make,” central bank spokesman Dan Suciu said. The videos coincide with a surge in interest for equity investments in Romania, fueled by the largest initial public offering in the country’s history last year as well as above-average returns offered by the Bucharest Stock Exchange. Cyber-criminals have taken advantage of the trend in a country that ranks near the lowest in the European Union for financial mediation.

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PAPERS:

NBER. The Unreasonable Effectiveness of Algorithms, Jens Ludwig, Sendhil Mullainathan & Ashesh Rambachan – Working Paper 32125. DOI 10.3386/w32125. Issue Date February 2024. We calculate the social return on algorithmic interventions (specifically their Marginal Value of Public Funds) across multiple domains of interest to economists—regulation, criminal justice, medicine, and education. Though these algorithms are different, the results are similar and striking. Each one has an MVPF of infinity: not only does it produce large benefits, it provides a “free lunch.” We do not take these numbers to mean these interventions ought to be necessarily scaled, but rather that much more R&D should be devoted to developing and carefully evaluating algorithmic solutions to policy problems.

NBER. How Learning About Harms Impacts the Optimal Rate of Artificial Intelligence Adoption. Joshua S. Gans. Working Paper 32105. DOI 10.3386/w32105. Issue Date February 2024. This paper examines recent proposals and research suggesting that AI adoption should be delayed until its potential harms are properly understood. It is shown that conclusions regarding the social optimality of delayed AI adoption are sensitive to assumptions regarding the process by which regulators learn about the salience of particular harms. When such learning is by doing — based on the real-world adoption of AI — this generally favours acceleration of AI adoption to surface and react to potential harms more quickly. This case is strengthened when AI adoption is potentially reversible. The paper examines how different conclusions regarding the optimality of accelerated or delayed AI adoption influence and are influenced by other policies that may moderate AI harm.