Regulators Warn of Machine Learning, Shadow Banking and Artificial Intelligence

The Group of 20 Economies (G20) financial regulator, the Financial Stability Board (FSB) warned about replacing humans with artificial Intelligence (AI) and Machine Learning. In a world of Ponzi, Fiat and shadow banking we have a new layer upon us.

The Group of 20 Economies (G20) financial regulator, the Financial Stability Board (FSB) warned about replacing humans with artificial Intelligence (AI) and Machine Learning. In a world of Ponzi, Fiat and shadow banking we have a new layer upon us. 

Machine and man

In what has been glaringly obvious to any of us not trapped in doublespeak, group think and any other thought of not thinking for yourself that there is a risk of losing control. The FSB said that ‘replacing bank and insurance workers with machines risks creating a dependency on outside technology companies beyond the reach of regulators’. One would offer not just regulation, but losing control of the machines or the machines running array themselves.

This was the FSB’s first report on AI and machine learning, it also comes at a time when cryptocurrencies have come to the fore and hitting all time highs. With the CME  and the impact of algoritims across all markets dominating the lateness of this realisation gives an idea of how far behind groups like the FSB, SEC and CFTC are.

Discussing big government, data and machines leads us to Aldous Huxley. How close are we to a Brave New World? 

“Stability,” said the Controller. “No civilization without social stability. No social stability without individual stability.” His voice was a trumpet. Listening, they felt larger, warmer.

The machine turns, turns and must keep on turning—for ever. It is death if it stands still. A thousand millions scrabbled the crust of the earth. The wheels began to turn. In a hundred and fifty years there were two thousand millions. Stop all the wheels. In a hundred and fifty weeks there are once more only a thousand millions; a thousand thousand thousand men and women have starved to death.

Wheels must turn steadily, but cannot turn untended. There must be men to tend them, men as steady as the wheels upon their axles, sane men, obedient men, stable in contentment.

Crying: My baby, my mother, my only, only love; groaning: My sin, my terrible God; screaming with pain, muttering with fever, bemoaning old age and poverty—how can they tend the wheels? – Aldous Huxley, Brave New World Chapter 3

We are largely delving into the world of the unknown here with usage of AI data largely unavailable, There are no international regulatory standards for AI and machine learning. With the World Bank worried about shadow banking one doesnt have to draw too big a bow to understand the causal links and risk of potentially new and unexpected links between markets and banks. Whatever is true or not with the Russia hacking investigation what we do know is regulators really have no clue and politicians and money launders will stop at nothing when greed takes over.

One favorite line from the report was that AI could lead to “non-sustainable” increases in credit by automating credit scoring. Doesn’t that sound very much like the sub-prime crisis? 

The FSB’s analysis reveals a number of potential benefits and risks for financial stability that should be monitored as the technology is adopted in the coming years and as more data becomes available. They are:

  • The more efficient processing of information, for example in credit decisions, financial markets, insurance contracts and customer interactions, may contribute to a more efficient financial system. The applications of AI and machine learning by regulators and supervisors can help improve regulatory compliance and increase supervisory effectiveness.

  • Applications of AI and machine learning could result in new and unexpected forms of interconnectedness between financial markets and institutions, for instance based on the use by various institutions of previously unrelated data sources.

  • Network effects and scalability of new technologies may in the future give rise to third-party dependencies. This could in turn lead to the emergence of new systemically important players that could fall outside the regulatory perimeter.

  • The lack of interpretability or auditability of AI and machine learning methods could become a macro-level risk. Similarly, a widespread use of opaque models may result in unintended consequences.

  • As with any new product or service, it will be important to assess uses of AI and machine learning in view of their risks, including adherence to relevant protocols on data privacy, conduct risks, and cybersecurity. Adequate testing and ‘training’ of tools with unbiased data and feedback mechanisms is important to ensure applications do what they are intended to do.

Source: FSB considers financial stability implications of artificial intelligence and machine learning

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