APPROACH
Arialytics offers AI Research-as-a-Service solutions that help institutional investment clients analyze and make discoveries in their structured and unstructured datasets using advanced statistical methods like Artificial Intelligence and Machine Learning.
AI Research-as-a-Service
We believe a rigorously scientific approach to investing provides the best means of reducing uncertainty and achieving superior outcomes. Our cloud-based AI Research-as-a-Service solutions help you quickly apply AI/ML methods your data, allowing you to discover actionable investment insights quickly and with minimal coding.
STRIVING for PURE SCIENCE
At the core of Arialytics approach to investment research services are carefully structured methods for making and validating discoveries in data in as scientific a manner as possible. Our cloud-based systems seek to understand how the systematic application of AI/ML methods will perform in the real world of the future. We employ artificial intelligence and proprietary algorithms to increase the value of insights from data.
RESEARCH and DISCOVERY
Our AI-based algorithmic approach emphasizes rapid discovery of patterns in data and encourages the rapid formulation and testing of many ideas. Through the rapid ideation and testing that we enable, you can make new connections and discoveries that contribute to your investment process.
Our approach to research draws not only on AI but also economic, financial, statistical, and high-speed data processing technologies to identify explanatory variables and risk factors which could provide the foundation for profitable investing. Our research systems can evaluate massive amounts of data across asset classes, regions, countries, industries and thousands of individual securities.
UNDERSTANDING LIKELY OUTCOMES
The objective of our discovery approach is not to find the best performing model over past years, but rather to identify the best models for prediction going forward. We use proprietary inference technologies to robustly understand the likely future performance of models. This capability is especially valuable for the management and mitigation of model risks.
TRANSPARENT, EXPLAINABLE SOLUTIONS
One of the weaknesses of complex AI/ML models is that they are often not explainable. Models developed with our Research-as-a-Service solution are transparent and explainable. This allows you to quantify with certainty mow much any one or a group of factors influence a particular outcome, no matter how complex the model. Explainability gives your analysts a powerful tool for iterating their ideas and explaining their models to colleagues, investors and regulators.
AI and MULTI-FACTOR RESEARCH
Artificial intelligence (AI) is one tool in an expansive analytic toolbox embedded in our research technology. Multi-factor investing – basing models on risk factors – offers one way to structure research programs in a way that is transparent and understandable. We combine over ten years of experience with AI/ML and economically motivated investing tools in a best-of-both-words approach to research and uncertainty reduction.
SYSTEMATIC RISK MANAGEMENT and REDUCING RISK
We understand that the objective of research is often a systematic risk management program. Discovering patterns in data that can be used to achieve better risk management is an essential capability of our research technology.
Our Research-as-a-Service approach allows you to discover your own risk management solutions and quantify their value – quickly and with minimal coding.
MAXIMIZING YOUR TIME and EXISTING RESOURCES
Artificial intelligence and Machine Learning are relatively new additions to the investment research toolkit. Demand for skilled AI/ML resources far outstrips supply. Hiring and training these resources is expensive and time-consuming. Arialytics Research-as-a-Service approach helps you obtain the advantages of advanced AI/ML driven research immediately. Because interacting with our research platform involves little or no coding, you get more productivity and ideas out of your existing people.
AN END-TO-END APPROACH
The linkage between the discovery and implementation of a research solution must be seamless. Any difference among testing and real-time implementation methodologies has the potential to introduce unwanted deviations from expected performance. Accordingly, our development and operations systems are tightly integrated at the algorithmic level, ensuring that operations are as systematic as development.