AI + Human: Machine Learning Investing
Factors and portfolios at your fingertips, augmented with machine intelligence
Portfolio Toolbox
For Investors,
Advisors
Signal DB
For Quant,
Financial Analyst
Machine Learning Solutions
For Institutions,
Asset Firms, Partnerships
What you get
Research backed and validated equity factors and signals, delivered as automated data-feed to systematic and quantitative investment professionals, that are timely and cost effective.
K Score, a Predictive Equity Rating
Make buy/sell decisions with confidence
A derived equity rating score between 0 and 9 with high K Scores indicating higher probability of out-performance. Quantitative buyside firms overlay K Score with their investment models as buy/sell signals.
We applied machine learning methodologies and ranking algorithms of over 200 factors and signals including fundamental, price/volume and alternative data.
Latest Factors, Validated Research
Access insights at a fraction of your current cost
Access the newest researched factors, anomalies, and signals in minutes rather than weeks.
Save time and money to conduct research and validate factors in-house.
Delivered as automated data-feed, long history, and broad coverage, all at your finger-tips.
Passive Plus Active is the New Edge
Combine ETF with direct indexing
The benefit of an ETF with more control. Partner with Kavout to design index enhancing portfolios, or whether sector specific or cross-sector.
Your customer and fund management experience combined with our expertise in research and machine learning means new market and opportunities.
The 3Ds of why we apply machine learning
Deep Data
Data silos need to be connected, data relationships evolve from N to N², forming a network effect which in turn produces greater correlation value.
Deep Learning
The requirements for processing complex nonlinear data relationships cannot be handled by statistical modeling. This calls for machine learning techniques for deep mining of data.
Deep Discovery
Uncover relationships, signals, anomalies, and insights to increase alpha, predict trend, and reduce risk exposure by combining fundamentals and alternative data with the help of new tools.
Customers and partners
“Kavout has a proven system for generating alpha and coverage of a wide base of listed equities that makes them a market leader in providing the latest AI driven tools for the Investment Management industry.”
“Kavout’s strength is their ability to develop systematic and quantitative equity strategies and research. K Score, their equity rating and ranking product, is innovative, and they are especially unique in their knowledge of the China A-Share market.”
Over two decades of big data and machine learning expertise.
Kavout features a world-class team of finance and data science experts and engineers, with collective experience at high tech and finance companies like Google, Microsoft, Baidu, Thompson Reuters and other Wall Street companies.
Nvidia Inception 2017
Best Early Stage AI Startup Top 5
FINCON 2016
Fintech Startup Competition Winner
Benzinga 2017
Best Finding Alpha Finalist
Create 33
A place for founders by founders
Kavout’s Differentiation
Research-Driven
Our method is grounded in fundamental finance principles, rigorous quantitative research with tested models and strategies, and domain knowledge in FinTech, compliance and operations.
Our team is comprised of seasoned investment professionals, university professors and researchers in applied math and quantitative finance.
Track Record in AI & Big Data
Close to 20 years of experience developing big data, natural language processing (NLP) and machine learning at a large scale at Google, Microsoft and Baidu.
Developing Kavout’s suite of machine learning and deep learning products and services since 2016.
World-class Engineering
Decades of combined engineering know-how, developing information and commerce platforms at the scale of billions of search queries per day, and more than 10,000 purchase transactions per second.
Experienced in the development of large-scale cloud computing architecture, data storage and processing, and algorithms and decision engines processing at 40,000 QPS per second.
Thesis
In the financial markets, over the past 150 years, many alpha sources have come and gone. In the 1950s, it was the invention of long/short equity strategies by the very first hedge funds. In the 1980s, mathematics and computers held an edge over calculators. In the early 2000s, it was high-frequency trading. These were all strategies or tools that gave those who had access to them an advantage. But as they became more and more widespread, their advantage dissipated. Investors are looking for the next big thing.
At Kavout, we believe that the application of artificial intelligence (AI) and machine learning (ML) is the next transformative force to change the investment and wealth management landscape.
Gartner predicts that in the next five years, AI and ML are increasingly a foundational component of all of the applications, services and things around us.* Financial markets are one of the early adopters, with companies such as BlackRock and Fidelity integrating ML in their investment strategies and process.
Meanwhile, job roles that require decision science and analytics skills (including data science, ML, and big data) are projected to grow at the highest rate yet are the most difficult to fill**. Unlike BlackRock and Fidelity, whose assets under management (AUM) is $6 trillion and $2.5 trillion respectively, most investment firms face insurmountable challenges on many fronts.
- They may sit on a vast amount of data but not know how to tap into it.
- They may lack an in-house AI/ML team or the know-how and experience to run it.
- Even if they start building capabilities today, training machine models and algorithms require time and tuning, which Kavout has been doing since 2015.
On top of that, robo-advisory firms such as Betterment and Wealthfront are slowly chipping away AUM from traditional investment firms, offering lower fees while driving massive inflow to passive funds such as ETFs***. Companies are under pressure to demonstrate value to clients while lowering cost-to-income ratio.
Kavout’s mission is to democratize AI and machine learning, empowering institutions and investors with augmented intelligence to generate alpha, manage wealth, and do more with less.
Source: *Gartner Top 10 Strategic Predictions for 2018 and Beyond, 2018
** IBM, Burning Glass Technologies and BHEF joint research, The Quant Crunch, How the Demand for Data Science Skills Is Disrupting the Job Market, 2017
***Bloomberg Intelligence, Aug 2018
Our Values
Be Collaborative
With shared knowledge, experience and skills, we are able to think more holistically and scale broadly with the support of our employees and our partners.
In Pursuit of Excellence
We are not satisfied with status quo. A question you often hear us say is “how can we make it better”.
Be Data-Driven
We believe that making decisions based on evidence is far more reliable than ones based on instinct, assumptions, or human emotions which can be biased.
About Kavout
Kavout was created by ex-Googlers and the founding team used to work at Google, Microsoft, Baidu, and financial firms with a proven track record of building many mission-critical machine learning systems where billions of data points were processed in real-time to predict the best outcome for core search ranking, ads monetization, recommendations, and trading platforms.
Our mission is to build machine investing solutions to find alpha with adaptive learning algorithms and to create an edge by assimilating vast quantities of complex data through the latest AI and Machine Learning methods to generate signals to uncover hidden, dynamic, and nonlinear patterns in the financial markets.
Our Backgrounds
About Kavout
What is Kavout?
Kavout is a global InvesTech company committed to empowering institutions and investors to make smarter, faster, and better-informed decisions. We do that by redefining the frontier of investing with the application of cutting-edge and proven technologies, including machine learning, neural networks and deep learning.
What does Kavout mean?
The word Kavout comes from regional French and means “to find.” At Kavout, we are explorers of new territories that few have set foot on before.
Who are Kavout’s customers?
We serve the investment community and companies like hedge funds, institutional asset managers, portfolio and fund managers, Registered Investment Advisors, data buyers and distributors, quant funds, proprietary trading firms, and risk management firms.
What type of AI/machine learning methods is Kavout utilizing?
Our technology is built upon a variety of state-of-the-art machine learning models, including deep learning and Bayesian probabilistic models. Even though Kavout is using advanced models, our philosophy is still driven by core financial principles. Every factor and model Kavout build has an underlying financial thesis.
Why Kavout?
Why should I work with Kavout?
Here are three reasons you should consider working with us:
- We are pioneers in the field of AI investing. When Kavout was founded in 2015, we were one of only a handful of companies using AI for financial services.
- Rather than building their own in-house AI team, our clients find working with Kavout to be cost-effective. It also increases their time-to-market with new investment strategies.
- When our clients work with us, they don’t have to re-invent the wheel. They can leverage our pre-trained machine learning models and algorithms and access data sets that have been structured and cleaned.
What are some of the benefits of working with Kavout?
Kavout’s solutions and services can help you:
- Augment your team’s human intelligence with AI
- It enables you to service more customers and increase asset under management (AUM) by using new technologies.
- Increases your competitiveness and the ability to stay current on the latest solutions.
- Generate actionable insights from a sea of data. Kavout support our customers to separate signals from noise.
- Mitigate risks and reduce downside based on actionable insights.
- Increase operational efficiency while keeping cost-to-income ratio low
How are Kavout’s machine learning-based models different from traditional statistical models?
Below are a few of the ways these types of models differ.
- Capacity to learn: While traditional statistical models are static, machine learning-based models learn, adapt and improve their methods as they process new inputs.
- Number of variables: Traditional statistical models are only able to address a limited number of variables. Meanwhile, machine learning models can address thousands, even millions of variables thanks for advancement in computing power.
- Forgiveness to noisy data: Machine learning models are able to extract meaningful insights from noisy, unstructured data like social media, news, blogs while traditional statistical models simply cannot handle this.
What makes the Kavout team unique?
Kavout’s solutions and services can help you:
We have assembled a world-class data science, engineering, and finance team to research and build our platform. Our team come from backgrounds in AI, machine learning, big data, and quantitative financial analysis, with decades of professional work experience in high tech and quantitative finance companies like Google, Microsoft, Thompson Reuters, Baidu, and other Wall Street institutions. This combination makes Kavout uniquely qualified to help you integrate new and scalable technologies into the processes of your investment firm.
Working with Kavout
What can I expect in a consulting project?
The Kavout team partners with you every step of the way to ensure you feel clear and comfortable during your project. Our team can help you implement one of our out-of-the-box solutions, or develop strategies and customized solutions that meet your needs.
How do I purchase Kavout’s solutions or services?
Contact us if you are interested in purchasing our products. In addition, Kai as a Service (KaaS) is a service platform that you can subscribe to and leverage our pre-built models and algorithms.
If I provide data to Kavout to process and analyze, how will it be protected?
Client confidentiality and data privacy are of the utmost importance to us. All Kavout team members who work on a project sign confidentiality agreement with our clients to ensure their information is protected. In addition, all client data is stored on secure servers. We also use a login encryption process for particularly sensitive data items.
What type of AI/machine learning methods is Kavout utilizing?
Our technology is built upon a variety of state-of-the-art machine learning models, including deep learning and Bayesian probabilistic models. Even though Kavout is using advanced models, our philosophy is still driven by core financial principles. Every factor and model Kavout build has an underlying financial thesis.
AI and Machine Learning
What is artificial intelligence?
The term “artificial intelligence” is applied when a machine mimics cognitive functions that humans associate with other human minds, such as learning and problem solving.
What is machine learning?
Machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to learn from data, without being explicitly programmed.
Do you think AI solutions should replace humans? That they’re better than humans?
Not at all. At Kavout, we create AI and ML solutions to augment human intelligence. Because of its capacity to process large amounts of data at scale, there are some things that AI solutions are better at. Meanwhile, humans are better at higher-level strategic thinking. We believe in a hybrid model where AI solutions can support and empower humans by providing them with the information they need to make strategic decisions.
Locations
Seattle
Beijing
Shanghai
Contact us
Contact us today to learn more about Kavout's products or services.
