NEWSLETTER of July 19, 2024

The following content has been added at finexpert:

Allianz Research
GENAI IN THE INSURANCE INDUSTRY: DIVINE COINCIDENCE FOR HUMAN CAPITAL
Who's afraid of GenAI? While experts predict substantial positive economic effects from the rise of generative artificial intelligence, public sentiment is not so optimistic. In our survey of over 6,000 people in Austria, France, Germany, Italy, Poland and Spain, 36% expressed concerns over the risks presented by AI, with 46% expecting AI to cut the number of jobs available (vs. 33% who expect AI to increase the number of jobs available). More worryingly, more than half of all respondents (51%) believed that the skills gap and inequality could widen as AI uptake expands across industries, with the smart getting smarter and the rest being left behind. Just 21% of all respondents were optimistic about the benefits of AI for their economies. But we find that fears of AI causing a massive labor dislocation in the insurance industry are overblown. As a data-driven industry like few others, the insurance industry in particular has significant potential for automation and productivity enhancement. >more

BCG
THE GENAI ERA UNFOLDS: GLOBAL WEALTH REPORT 2024
Global net wealth staged a significant recovery in 2023, growing by 4.3% after a difficult year in 2022. Much of the growth was due to a rebound in the financial markets, accompanied by a rise in the volume of assets under management (AuM). Financial wealth — a subset of global wealth — rose by almost 7%, following a decline of 4% in 2022. The gains were especially strong in North America and Western Europe, while growth in China remained more subdued. Cross-border wealth followed a similar pattern. Key booking centers such as Switzerland, Singapore, the US, and the United Arab Emirates (UAE) grew in line with recent trends, while Hong Kong witnessed a notable slowdown — growing by just 3.2% — due to reduced inflows from mainland China. >more

KfW Research
KFW-KREDITMARKTAUSBLICK Q2 2024
Business with corporate loans continues to decline. In the first quarter of 2024, new loan commitments calculated by KfW Research fell by 3.9% compared to the previous year. In the two previous quarters, new business fell by double-digit rates. The recovery in new lending business is being dampened by the weak development in corporate investment. New lending business is only expected to grow slightly in the second half of the year if the economic recovery stabilizes and the turnaround in interest rates is reflected more strongly in financing conditions. Economic policy planning security for companies also influences their financing requirements via their investment decisions. In this respect, the outcome of upcoming decisive elections and the development of trade conflicts represent an uncertainty factor for the recovery of the credit market. >more

ifo Institut
DIE ZUKUNFT DES EUROPÄISCHEN FINANZSYSTEMS – ZWISCHEN RISIKEN UND MANGELNDER WETTBEWERBSFÄHIGKEIT?
In its latest Financial Stability Report, the ECB states that the stability of the financial system has improved. The opinion of the European Systemic Risk Board (ESRB) has also recognized the resilience of the banking system. The turmoil surrounding Silicon Valley Bank and Credit Suisse had still raised concerns last summer. Currently, increased risks remain - due to geopolitical uncertainty and developments on the real estate markets, among other things. At an institutional level, important steps towards a banking union and the strengthening of a European capital market are also missing. What about the stability and competitiveness of the European banking sector? Are the existing instruments sufficient to cushion potential risks? Are the developments on the US commercial real estate market and the insolvency of the Signa Group having an impact on German and European banks? Are climate risks having an impact on stability? And to what extent does the governance of banks contribute to their solidity? >more

CHATGPT AND PERCEPTION BIASES IN INVESTMENTS: AN EXPERIMENTAL STUDY
Anastassia Fedyk, Ali Kakhbod, Peiyao Li, and Ulrike Malmendier
2024
Applications of artificial intelligence (AI) in finance have been met with concerns about algorithmic bias, following issues observed in domains such as medical treatment and lending. We ask whether AI models accurately capture investment preferences across demographics. We elicit investment preferences from over 1,200 survey participants and compare the data directly to investment ratings generated by OpenAI’s ChatGPT (GPT4). We find that ChatGPT predicts investment preferences with high accuracy across demographics. Specifically, ChatGPT correctly predicts that women rate stocks lower than men, older individuals prefer holding cash, and higher incomes are associated with higher ratings for stocks and bonds. Moreover, free-form responses from ChatGPT focus on the same aspects as human free-form responses. Most common themes in both responses are “risk" and “return," and "knowledge" and "experience" play an important role for stock market participation. One difference is that ChatGPT responses are almost always transitive, whereas human responses are more prone to violating transitivity, especially when expressing indifference. Overall, the use of AI in finance offers a promising direction for augmenting human surveys in preference elicitation, with important applications for areas such as robo-advsing.Applications of artificial intelligence (AI) in finance have been met with concerns about algorithmic bias, following issues observed in domains such as medical treatment and lending. We ask whether AI models accurately capture investment preferences across demographics. We elicit investment preferences from over 1,200 survey participants and compare the data directly to investment ratings generated by OpenAI’s ChatGPT (GPT4). We find that ChatGPT predicts investment preferences with high accuracy across demographics. Specifically, ChatGPT correctly predicts that women rate stocks lower than men, older individuals prefer holding cash, and higher incomes are associated with higher ratings for stocks and bonds. Moreover, free-form responses from ChatGPT focus on the same aspects as human free-form responses. Most common themes in both responses are “risk" and “return," and "knowledge" and "experience" play an important role for stock market participation. One difference is that ChatGPT responses are almost always transitive, whereas human responses are more prone to violating transitivity, especially when expressing indifference. Overall, the use of AI in finance offers a promising direction for augmenting human surveys in preference elicitation, with important applications for areas such as robo-advsing. >more

LARGE LANGUAGE MODELS AND M&A: CAN CHATGPT HELP FORECAST M&A ACTIVITY?
Dominik Degen, Jens Kengelbach, Daniel Kim, Soenke Sievers, and Yiran Wang
2024
This paper employs ChatGPT on firms' earnings conference calls transcripts to extract managers' so far private information regarding their sentiment and expectations concerning (future) mergers and acquisitions (M&A) activity. We aggregate these firm-level scores to a market wide ChatGPTbased M&A sentiment score (MASS) and successfully perform various construct validity checks including employing M&A experts and back testing. Our main results suggest that M&A sentiment has strong forecasting power for future M&A activity and adds additional explanatory power to established sentiment indices and fundamental drivers. The predictability holds for both in-sample and out-of-sample tests. Overall, our novel index will be useful to further understand M&A patterns, to predict future M&A activity, and for practitioners to evaluate and benchmark their own M&A activities. >more