The article was written by Amber Zhou, a Financial Analyst at I Know First.

5 AI Fintech Companies That You Should Know

Highlights:

• Growing Presence of Artificial Intelligence in Financial Service Industry
• Overview of the AI Fintech Landscape
• 5 AI Fintech Companies That You Should Know

Growing Presence of Artificial Intelligence in Financial Service Industry

Artificial Intelligence (AI), was once the domain of fanciful science fiction books and films. But now the drive to eliminate human fallibility makes the technology stormily take the world across all industries, from self-driving cars to virtual assistants like Siri. Companies are significantly benefited from the cost saving from a variety of automated processes. Now programmers and data scientists are setting their sights on financial services. Applications for AI technologies exist across nearly the entire spectrum of business, from algorithmic stock trading applications, credit card fraud detection to auto investment advisors.

According to Accenture (NYSE:ACN) analysis of data from CB Insights, a global venture-finance data and analytics firm, global investment in financial technology (Fintech) ventures rose 18% to US$27.4 billion and reached another all-time high in 2017, buoyed by a surge in funding for startups in the United States, United Kingdom and India.

Exhibit 1: Global Fintech Financing Activity by Region (2010-2017)

Exhibit 2: Global Fintech Financing Activity by Segment (2010-2017)

Over the year 2017, AI has become a major driver of innovation in the Americas, particularly in the US and Canada where investors have recognized the massive opportunities presented by AI to automate business processes. Canada continues to make strides to become a global player in AI, driven by Canadian government support and the presence of strong AI innovators at several Canadian universities. According to PwC Global Fintech Report, 30% of large Financial Institutions are investing in AI.

Exhibit 3: Technological Areas of Investment

In essential, AI and finance are no strangers to each other. Traditional banking and finance have relied heavily on algorithms for automation and analysis. However, these were exclusive only to large and established institutions. Fintech nowadays is being aimed at empowering smaller organizations and consumers, and AI is expected to make its benefits accessible to a wider customer base. As we are entering into the big data era, with the sheer volume of data that humanity is generating and available, AI is undoubtedly making a major impact in Fintech now and in the near future.

Overview of the AI Fintech Landscape

According to CB Insights, companies on the AI Fintech market map fall into 9 main categories, offering service for front-, middle- and back-office:

1. Credit Scoring / Direct Lending: Companies using AI for robust credit scoring and lending applications.
2. General Purpose / Predictive Analytics: Companies using AI for general purpose semantic and natural language applications as well as broadly applied predictive analytics.
3. Quantitative & Asset Management: Companies employing AI algorithmic trading and investment strategies or tools.
4. Insurance: Companies using AI to quote and insure.
5. Market Research / Sentiment Analysis: Companies using AI to efficiently research and measure sentiment.
6. Debt Collection: Companies using AI to improve creditor collection of outstanding debt through personalized and automated communication.
7. Business Finance & Expense Reporting: Companies using AI to improve basic business accounting, including expense reporting.
8. Assistants / Personal Finance: Companies relying on an AI chat bot and mobile app assistant applications to monitor personal finances.
9. Regulatory, Compliance, & Fraud Detection: Companies using AI to detect fraudulent and abnormal financial behavior, and/or use AI to improve general regulatory compliance matters and workflows.

5 AI Fintech Companies That You Should Know

As illustrated previously, the entire AI Fintech market has been growing rapidly in recent years. Apart from having unique ideas, a successful Fintech company leveraging AI nowadays is the one that has concretely imposed its idea and apply the technology to a real business problem. Here we are sharing 5 most interesting AI Fintech companies, ranging across 5 different categories elaborated above. It should be noticed that 3 of them are in the annual AI 100 for 2018, a list of 100 of the most promising private companies applying AI algorithms across 25+ industries provided by CB Insights. Not surprisingly, each of them has a clear market application and follows a solid business model and hence earns good investor profile and growing opportunities.

Credit Scoring / Direct Lending: ZestFinance

 [Source: Britizen.com, May 30, 2018]

Being one of the fastest growing Fintech startups in the United States, ZestFinance applies its AI-based credit-decisioning technology platform to help lenders increase revenue, reduce risk, and ensure compliance. In 2017, the company launched the Zest Automated Machine Learning platform (ZAML), which quickly and accurately identifies good borrowers by analyzing both traditional and non-traditional credit variables. For example, it takes into account how a customer fills out a form, how they navigate a lender’s site, and more. Machine-learning based underwriting will open a new revenue stream for lenders. Through the implementation of ZAML, data is analyzed more deeply and in more detail over time. Thereafter, companies are able to increase approval rates and make smarter credit decisions with lower risks, particularly for thin-file and no-file borrowers. Ultimately, the company aims to expand the availability of fair and transparent credit.

Up to now, the company has licensed its ZAML Platform to companies across many industries and countries. Specifically, with more than half a billion people having no credit history, China has been a major market for the company. China’s dominant search platform Baidu is one of the primary investors for ZestFinance since the platform would be developed based on its search data. They also partnered with the largest online direct-sales company in China, JD.com. The platform is helping to create credit histories from scratch for these people and makes it easier to determine credit risk in China.

Quantitative & Asset Management:  Numerai

 [Source: Wikimedia Commons, May 30, 2018]

Founded in late 2015, Numerai is a new type of hedge fund which manages an institutional grade long/short global equity strategy for the investors. It hosts weekly stock market prediction competitions for global community of anonymous data scientists of any background. By synthesizing thousands of uncorrelated financial models and individual predictions, it utilizes crowdsourcing knowledge through a massive network of hedge funds. In other words, Numerai essentially transforms and regularizes financial data into machine learning problems for more than 35,000 data scientists who compete to win Numeraire, the company’s own cryptocurrency. Incorporating the algorithms submitted through the crowdsourced community, Numerai builds their own financial models.

The issuance of the new virtual currency successfully makes the incentives of data scientists further aligned with that of Numerai and gives it an edge over the market. Users would be willing to share their models, technique and data since better models will improve the hedge fund’s performance and hence return more wealth to its anonymous workforce.

To date, Numerai has a series of notable investors on its cap table, including Renaissance Technologies’ Howard Morgan, Union Square Ventures (USV), Coinbase cofounder Fred Ehrsam, and Polychain founder Olaf Carlson-Wee, raising a total of $7.5 million.

Insurance: Cape Analytics

 [Source: inman.com, May 30, 2018]

Cape Analytics was established in 2014 to revolutionize the way information about the built environment is created and consumed. The company’s principal value proposition is improving insurance data, which until now, has been relied on outdated tax records or costly in-person inspections. It utilizes their Mountain View-based data analytics technology to provide the most accurate and up-to-date property data for insurers and reinsurers to facilitate their quoting and underwriting process. The company leverages geospatial imagery, computer vision, and machine learning to instantly extract proprietary property data, ranging from nearby hazards to building footprints to roof condition. With that, comprehensive data and analytics solutions are delivered instantaneously via API .

In April 2018, Cape Analytics announced a major milestone: the launch of its data coverage for the entirety of the continental United States. Now, insurers can access data on over 70 million buildings across the country, allowing them to instantly pre-fill property information at the time of quote, choose better risks, price policies more accurately, and reduce post-binding adjustments and cancellations. Further, more accurate online quotes with fewer time-consuming questions are being developed to accelerate home insurance application process for consumers.

Market Research / Sentiment Analysis: Dataminr

[Source: porttechnology.com, May 30, 2018]

Founded by Ted Bailey in 2009, Dataminr is headquartered in New York and has over 300 employees. As the world’s realtime information discovery company, the company discovers high-impact events instantly and critical breaking information long before it’s in the news. It achieves to do so by first detecting the earliest indications of high-impact events and critical breaking information from massive data on real-time public social media. Then it transforms these early signals into real-time alerts, aligned with their clients’ top priorities and integrated directly within their workflow.

Their clients range across various sectors including Corporate Security, Finance, the Public Sector, News, and PR / Communications. Their client list includes most of the biggest US investment banks and at least half of the top hedge funds, overseeing a collective $1 trillion in assets. The software is also used by the public sector and emergency services to receive the earliest possible warnings of disasters and other major incidents in order to better protect citizens and help save lives. In 2014, Dataminr launched a tool for journalists, identifying and flagging up tweets sent on Twitter relevant to users’ interests, helping ensure they are the very first to breaking news.

Up to now, Dataminr has raised $180M in capital and is backed by the world’s leading venture and growth technology investors, including Venrock, IVP, Fidelity, Wellington, Credit Suisse, and Goldman Sachs. It has also been recognized as one of the world’s leading businesses in AI and Machine Learning Innovation, pioneering groundbreaking technology for detecting, qualifying and classifying public information in real-time. In 2016, CNBC recognized Dataminr as one of the world’s 50 most disruptive private technology companies. In 2017, Dataminr was designated as the 69th fastest growth company in North America, with 2318% revenue growth between 2013-2016.

Predictive Analytics: I Know First

Founded in 2009 in Tel Aviv, I Know First is a Fintech company that provides state of the art AI-based self-learning algorithmic forecasting solutions for the capital markets to uncover the best investment opportunities.

The underlying technology of the algorithm is based on artificial intelligence, machine learning, and incorporates elements of artificial neural networks and genetic algorithms through which we analyze, model, and predict the stock market. The algorithm is adaptable, scalable, and features a Decision Support System (DSS) to optimize the information produced by the years of data inputted.

The algorithm generates daily market predictions for stocks, commodities, ETF’s, interest rates, currencies, and world indices for the short, medium and long term time horizons.

The I Know First algorithm is designed for large financial institutions, banks, and hedge funds in the capital market as well as private investors looking for an advanced algorithmic support system. The algorithm is currently tracking and predicting a growing universe of over 10,000 financial assets.

Also, it serves as a decision support system and develops systematic trading. Forecasts are produced daily with signals and predictability indicators. The system also outputs the predicted trend as a number along with a wave chart that predicts how the waves will overlap the trend. This helps the trader to decide which direction to trade, at what point to enter the trade, and when to exit.

I Know First is adaptable and scalable, allowing comprehensive, customized algorithmic solutions including integration of additional markets according to client needs. Its uniqueness also lies in its accessibility to all types of people apart from professional investors. The company is working with a loyal and growing client-base, including wealth management firms, hedge funds, fund management partnerships, family offices, financial advisors and professional investors from around the world.