[What is insidious about today’s accelerating rate of change for advisors and asset managers is how new technologies, evolving investment processes, and ensuing new competitors can creep up on you. With the greater speed in adoption rates today of new technologies, financial services professionals need to be steadfastly vigilant and proactively curious about how these new approaches can competitively impact their business offerings and performance results. This is especially so in the rapidly changing money management arena where new technologies are increasingly either going to be used by managers or potentially used against them.

Artificial intelligence (AI) and machine learning is one key example of an area to be keenly aware about and to actively follow. To better understand where we are and the bigger implications of these technologies, we talked with Institute member David Aferiat, co-founder and managing partner of Trade-Ideas—an award winning AI and machine learning Fintech firm with a SaaS-based revenue model. How can these technologies directly impact the ability to generate performance and garner increased AUM? ]

Bill Hortz: “Making AI Accessible” is your motto and rallying cry on your investment professional website. How exactly are you doing that? What do you see as the key for accessibility?

David Aferiat:  What we learned, over our 16 year history of enabling our clients to make better decisions in the capital markets, was that building accessibility to AI comes from a focus on being impactful and relevant—a focus on providing impactful and relevant information to our clients.

As to impact, the analytics generated by our machine learning AI comes from long and short term trading simulations. Three years’ worth of AI decisions illustrates the AI’s ability to react to Black Swan events like Brexit and presidential elections. Those decisions also show an ability to forecast trend continuation and capture alpha as much as 20 days after each opportunity is identified. Each of the past three years has put the performance of the AI 25% or more above the SPY. That’s impact. We recently received the Best Machine Learning Development award by Fund Technology and WSL in their annual 2019 Awards Conference due mainly to our substantial 2018 outperformance results for our AI system, which we call “Holly.”

As to relevance, Trade Ideas allows for customization of the analytics produced so that results are relevant to each of our client’s preferences and covenants that, in some cases, dictate which areas of the markets and under what conditions AI decisions can be made. Some of these conditions include market cap, Long or Short positions, frequency of trading activity, etc. Ultimately each client decides whether to honor specific trade plans associated with each alpha capture opportunity generated by the AI system.

Hortz: Can you map out for us some of the strongest reasons and benefits behind actively employing AI and machine learning technology to the money management process?

Aferiat:  Whether you are an Individual or advisor or fund manager, everyone affected by decisions in the market desires reward under optimal risk conditions. We’ve known for a long time the days of set-ups based on eyeing charts are gone. Decisions that produce risk-adjusted positive outcomes require an ever-increasing amount of interpreted and processed data. Many market participants are not equipped with the tools to adapt to this new phase of the markets. AI enabled idea generation finds previously unseen trends using a screened selection of only those algorithms ascending in the probabilities of capturing alpha each day. Daily interaction with the AI system allows our clients to understand useful meta-information.

AI can be looked at as a virtual research analyst that never sleeps and provides fully formed investment opportunities. We are able to run tens of millions of simulated trades across over 40 different scenarios overnight using structured and unstructured data sets and deliver five to seven recommended strategies each day, designed to produce predictable alpha, and with risk guardrails against the strategies intraday.  

This also levels the playing field with large players, decreases cost, delivers efficiencies, enhances portfolio predictive capability and alpha, and mitigates risk. The adoption of AI and machine learning capabilities represents a great case study in its bottom-line impact on the industry of driving out costs and delivering efficiencies in their pursuit of capturing alpha. 

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