Money has always been the cornerstone of civilisation. The ability to trade gave rise to the evolution of modern man, and it is perhaps this dependence on wealth that sets human beings apart from our fellow earth dwellers. The stock market has been a beacon in the finance sector, ever since the Dutch East India Company began issuing paper shares in the early 1600s.
In recent times, trading on the stock market is a source of income for many and when something becomes a pillar of dependence, it is prone to dangers and mishaps.
Mishaps in the stock market can arise due to various reasons, such as mathematical blunders, frauds, clerical errors or even geopolitical conflicts.
These mishaps all gravitate towards human behaviour that governs trading or even world events, so, as we enter the age of AI, are we looking at a future where AI financial advisers could prevent calamities that occur during a major stock market crash, just by altering the vices of human behaviour?
Firstly, what is an AI financial adviser?
An AI financial adviser is simply a tool that analyses financial data and provides instant guidance on investing, trading and market performance among other things.
An AI adviser or a stock picker analyses thousands of different scenarios in real time in order to give its two cents on income and trading.
With this in mind, let us look at some of the major human-caused stock market mishaps that have occurred in history and analyse whether an AI adviser could have prevented or even mitigated the crisis.
A) The 1992 Harshad Mehta Scam
The Harshad Mehta scam is one of the most infamous scams in Indian stock market history.
Here’s how the scam worked:
Harshad Mehta acted as a middleman in Ready Forward Deals between two banks.
A Ready Forward Deal is one where one bank lends capital to another bank for a short period and holds government securities as collateral.
When a Ready Forward Deal is carried out, the selling bank normally issues a receipt which confirms that they hold security for the buying banks.
Harshad Mehta convinced banks to issue fake bank receipts and took these to larger banks who accepted the counterfeit receipts without verification and released a large amount of funds.
These funds would then be transferred by Harshad Mehta into his own brokerage account, instead of going to the buying banks and this allowed him to freely play in the stock market with unsecured capital.
It took four years for the scam to be exposed and when the fraud finally came to light, the aftermath was a devastating stock market crash which wiped out 40-50% of the market’s value and caused severe losses to Indian families and common investors who saw the Associated Cement Companies stock manipulation as a genuine economic boom.
Now, the question stands, could an AI financial adviser or an AI stock market analyst have prevented this scam?
Here, we have the things that Harshad Mehta capitalised on to carry this scam forward.
Firstly, the fake receipts shown to the larger banks worked solely because banks had a 15-30 days’ lag before reconciling their books. Mehta exploited this lag to carry out his transactions.
Secondly, he used under capitalised banks to obtain counterfeit bank receipts without a backing collateral.
Thirdly, Mehta pumped massive amounts of capital into specific stocks such as Associated Cement Companies and increased their stock value tremendously.
For the first issue of the time lag in reconciliation of books, an AI driven ledger working in real time would flag unmatched Ready Forward Deals and duplicate Bank Receipts and the regulators would be notified about the receipts within days. This would have blocked the very foundation of the scam.
For the second issue of the under capitalised banks issuing counterfeit receipts, AI auditors such as Natural Language Processing and computer vision models would automatically audit Bank Receipts structures and signatures and block the issuing of unbanked receipts. This would dismantle a key partnership that kept the 1992 scam going.
As for the third issue, the one which caused countless common Indians to go into a retail frenzy, an AI financial adviser or an AI stock market surveillance system would have raised alerts on abnormal spikes which would trigger regulatory alerts and circuit breakers. This would have potentially saved the savings of countless Indian families who succumbed to the aftermath of the scam.
Harshad Mehta capitalised on the blind faith that governed the banking and trading systems, satiating the human attribute of greed.
It took four years for the scam to be detected, but if an AI stock market system was in place, perhaps, the scam could have been routed at the outset.
AI financial advisers and stock systems would indeed play a huge role in preventing crashes due to fraudulent practices.
B)The Long Term Capital Management(LTCM) Crisis 1998
The LTCM crisis of 1988 is an unfortunate instance of genius mathematical strategies failing due to an unprecedented geopolitical shock which was the Russian government defaulting its domestic bonds and devaluing the rouble.
The strategies, drafted by Nobel Prize winning economists initially produced great returns for the firm, but the data models assumed that extreme shifts in the market were impossible, leaving no preparation for the impact of a major geopolitical shock.
The firm was also vulnerable, as they employed ,assign amounts of borrowed ones to amplify their returns, so when the geopolitical shock occurred, their vulnerability led to the firm completely submerged in a crisis.
Could an AI adviser or an AI stock market system have prevented this?
AI could not have possibly prevented the devaluation of the rouble and the Russian government’s defaulting, also, AI works on historical data models which would have assumed the liquidity of the firms, but there are ways in which AI systems could have mitigated the crisis.
Firstly, AI financial analysts would have flagged geopolitical tensions, such as the political climate in Russia and policy shifts. The LTCM’s strategy turned a blind eye to the possibility of a geopolitical crisis and AI would have taken the scenario into account and perhaps forced a reduction in leverage by sending out alerts and warnings.
AI trading systems would also have stimulated a scenario to reveal the portfolio’s vulnerability in a hypothetical environment which would have helped in the preparedness of the firm and helped them look into their own shortcomings.
Finally, AI would have been better at pricing transaction costs which may have stopped the firm from excessive borrowing.
A crisis catalysed by a geopolitical crisis catches everyone off guard and while AI cannot predict a destined occurrence, it can act as a shield by enhancing preparedness.
C) Finfluencers
Time has brought the world to an era where speed is everything. All of us are looking for instant ways to earn, instant ways of spending what is earned and finally ways in which wealth can grow, instantly.
This has given rise to a group of financial influencers or “Finfluencers” who are, albeit self proclaimed, “the only guidance one ever needs to conquer the stock market”.
From fraudulent practices to risky advice, Finfluencers disguise all sorts of things under a facade of promising growth.
For instance, the pump and dump scandal where Finfluencers buy a small, illiquid stock or even a crypto coin at a low price and convince their followers to invest in that stock, thereby increasing its value.
These Finfluencers quietly sell off their own shares and when the price falls, the followers are left with massive losses while the mentor escapes unscathed.
A recent example is the YouTube Bollywood Stock Manipulation in 2023 and the 114 million dollar Atlas Trading Discord Fraud.
Schemes such as this target young and new investors who end up burning their feet right at the beginning.
AI financial advisers monitor such dangerous trends and can immediately flag a Finfluencer’s asset’s volatility and also predict the potential capital loss.
AI stock pickers and advisers are a much better way to start one’s trading journey as most finfluencers often bypass legal regulations while AI advisers are built to comply with regulations and even with the sense of fiduciary duty towards the investor.
Finfluencers are also known to mask risks but an AI stock pickers will always analyse the risks before suggesting market exposure.
AI cannot completely replace human financial advisers but they can help in overcoming or even mitigating the mishaps which are historically attributed to the human mind.
Perhaps a non human angle increases agility and works in real time, reduces behavioural mishaps and even oversights and excessive trust in one’s ability.
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