Original article can be found here (source): Artificial Intelligence on Medium
Artificial Intelligence Applications
The AI wave has been riding for the past two decades. All the major companies have an R&D facility set up to boost their abilities in the realm of AI. Artificial Intelligence has been in high demand lately for two reasons:
a) The high degree of automation it provides
b) Economic advantage to the companies
Also Read: What is AI? How It Works?
Let us look at some applications of AI in the finance sector.
In stock markets, the decisive component for thriving is the ability to make quick and accurate decisions. Therefore, using a tool to accomplish the same can cause a huge competitive advantage. Stock markets are complex mathematical models that vary with respect to different factors. What better than an AI system to model the same? These systems achieve several orders of magnitudes greater than the best human in the trading field. They can also achieve a very large number of accurate tradings in a day when compared to humans. Currently, large organisations and banks are investing in such systems to derive the optimum portfolios for their customers.
Market analysis and data mining
Understanding the market needs and delivering products according to what the customer wants is a challenging task. Therefore, many financial institutions have invested heavily in building a strong base in the AI sector. Some companies and their AI engines are as follow.
a) BlackRock — Aladdin is the AI engine. It is used to help clients with investment decisions.
b) Deutsche Bank — Sqreem, which stands for Sequential Quantum Reduction and Extraction Model. It can mine data to develop consumer profiles and match them with ideal products for optimum growth.
c) Goldman Sachs — Kensho. Uses NLP to assess the effect of world events on stock markets. Smart AI algorithms are used to collect and understand raw data from the huge pool of resources on the Internet.
Ever wondered where all the money that you earned went? What if you could still enjoy and at the same time make room for savings? This again is an optimisation problem, and thus AI is best suited for the job. There are many products in the field of personal finance to help you achieve the same.
Let us look at a few examples:
a) Digit: An AI-powered app that helps customers optimise their spending and savings based on their own personal habits. Therefore, it’s a personalised engine keeps track of your spending habits and suggests the optimum way to do so.
b) Wallet.AI — They analyse the data that a consumer leaves behind on the social media and smartphone check-ins. This data is used to inform the user about their spending behaviour.
The portfolios are designed by AI agents to suit the users needs. If the investor is looking at short-term gains with low risk or long term with maximum profitability. Whatever the need is, the AI agents can suggest investment portfolios. These are called Robo-advisors. They are becoming more widely used in the investment management and portfolio management industries. With the least human intervention, the algorithms provide accurate portfolios with the capability to accommodate real-time changes with respect to the changes in the market.
The process of assigning credit scores to users is a challenging task. Therefore, using AI, many companies have come up with algorithms to assign credit scores to users. Let us look at two such companies.
a) Upstart — Analyses vast amounts of consumer data and uses machine learning algorithms to develop credit risk models that predict a consumer’s likelihood of default. These algorithms are licensed to banks which makes it easier and safer to give loans.
b) ZestFinance — Zest Automated Machine Learning (ZAML) Platform for credit underwriting. This platform utilises machine learning to analyse tens of thousands traditional and nontraditional variables (from purchase transactions to how a customer fills out a form) used in the credit industry to score borrowers. The platform is useful to assign credit scores to those with limited or no credit history, such as millennials.
Also Read: Types of Artificial Intelligence
In this article, we understood the various applications of AI in the finance sector. In the future articles, we can consider applications of AI in the field of science and technology, manufacturing and more.