FPGAs, HPC, Federated Learning, Specialized Architecture: Not Just Concepts For Select Few

Please note: We are not affiliated with Intel. We simply use Intel as an example of a familiar accredited solution provider who is offering specialized hardware.

Intel has done much to progress AI adoption across certain verticals through it’s data centric vision, whereby the company has dedicated significant resources across architecture and software. Speaking from Financial Services industry’s standpoint, as of today, only a handful of large and established banks are availing Intel’s portfolio of custom hardware. Most enterprises are either unaware of nuances of Intel’s offerings or are intimidated by cost and complexity. Most of these concerns are unfounded and it is more of a matter of perception. Objective of this research piece is to shed light on current hardware advancements, their relevance in optimizing advanced AI algorithms and their specific role within Financial Services.

From an Research and Development (R&D) standpoint, Intel’s proactive stance is reflective of how the industry will evolve in the next five years.

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Small Businesses, Small Banks, Right Technology: Extraordinary Potential in Unordinary Times

Small Banks

Wheels of most economies, even as advanced as the United States, are greased by thriving micro and small business segment. In fact, health of an economy is often gauged by the number of successful small businesses and not by conglomerates or venture capital funded unicorns.

Different countries have different definitions for small businesses, some of which aren’t realistic,

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Next Wave of RegTech: Less Manual Oversight via Greater AI Hindsight

Regulation

In uncertain and precarious times, most enterprises split into one of these two camps.

Those wanting to capitalize on lurking opportunities at any cost (arbitrage) and those wanting to retain customers while carefully helping them navigate through uncertainty. Which approach businesses adopt, is strictly their prerogative as the ultimate objective of any business is to maximize profit for their shareholders, ideally by keeping interest of all stakeholders (such as customers) in mind.

In dire times, it is not uncommon for enterprises wanting to fend for themselves but also wanting to capitalize (even if unfairly, unethically) on imbalances in demand and supply. To combat exploitation, unfair opportunistic advantages, consumers look up to regulators and compliance officers.

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Explainability & Interpretability: Difference, Significance & Models for High Stakes Financial Functions

Explainability and interpretability of AI solution have been repeatedly discussed amongst most sincere and committed data scientists and researchers. Best models incorporate both. As per our findings, seasoned data scientists, machine learning experts try to factor in explainability and interpretability, from inception through finalization of their model.

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Looking Beyond Hardship: Managing Liquidity, Supply Chain, Counterparty Risk and Steadying Stock Markets

covid stock market

As per a November 2019 CNBC article by Deutsche Bank‘s Chief Economist, following were the key factors which would shape global markets in 2020:

  • U.S.- China trade wars
  • Downward trend in the US stock exchange due to drop in demand for US Treasuries, credit rating downgrade of various corporations, tightening credit conditions on both, corporate and consumer side
  • Possibility of impeachment of the President of the United States on U.S. and impact of that judgement on global stock markets (NYSE has equity market capitalization of over $19 trillion and is the largest in the world, so a significant movement on NYSE almost always has a ripples effect on other exchanges)
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Evolutionary AI: Tempering High Risk of Complicated Financial Instruments

CFI Derivatives

Evolutionary AI (EAI) is a subset of evolutionary computation, inspired by biological evolution. In algorithm and AI world, it can be described as the survival of the fittest, where ‘fittest’ or optimal solution is the one that can most efficiently solve a problem, based on defined parameters or conditions.

Simple analogy: Would you use a $1,000,000 24k Gold Vaccum called GoVaccum to clean a 100 square feet, one room apartment or would you use a Dyson Cycle V10 industrial vaccum?

Or would a simple vaccum cleaner suffice? How about just a broom?

First two options are unnecessary (for most people…we think). Most people would sensibly choose either option three or four, depending on other constraints such as time, budget, frequency of cleaning, level of effort, etc.

Evolutionary AI (EAI) is such a sensible solution but is endowed with a creative, breakthrough twist.

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Trading Chronicles: Factors influencing ‘Day Trades’& ‘Buy and Hold’, Role of AI and AI Initiatives at Ten Leading Global Traders (by Revenue)

AI systems can analyze information from myriad sources such as market data, social media, corporate filings and economic conditions to ‘accurately’ provide a comprehensive image of the market, so that a trade may be executed at optimal conditions. In trade speak, optimal implies, ‘buy low, sell high with minimum deal execution cost’. However, both ‘optimal’ and ‘accurate’ are relative terms and highly transient in trading world, as there are many participants with differing psychology in the markets operating with access to different sources of information, that influence their trading decisions, at any given time.

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