Artificial Intelligence in Finance
The topic of digitalization of society, the development of Artificial Intelligence, online privacy, and data collection have been one of the most controversial to come in recent years. With people realizing not only how much data is gathered from each action taken online, but how much value it presents, the public uproar has been rapidly increasing in recent years.
With the giant technological leap, humanity has taken in the last decade, technology has been applied to every business unit, transforming the possibilities and processes evolving. Companies must adapt their businesses to new technologies. Otherwise, they would not be able to keep up with the rapidly rising level of competition.
If big data is the new oil, analytics is the combustion engine.
Artificial intelligence is the simulation of human intelligence processes by machines, that evolve around machine learning, reasoning, and correcting, with further self-development.
By using unstructured data to draw conclusions about causes and effects within data, AI can detect and deduce upon patterns, identify opportunities, and automatically act upon them.
Data collection, data evaluation, developing the strategy to act upon based on the data collected, and testing the validity and efficiency of the action taken.
Businesses are striving to integrate these solutions into their operations but are still in the process of figuring out the nature of AI. Nevertheless, it is clear, that AI is slowly taking over. According to a survey conducted by BrightEdge, Inc., the biggest trends in marketing are considered personalization, artificial intelligence, and voice search. These three trends heavily relate to the application of artificial intelligence and machine learning.
The value a data presents is not determined by the amount of data that has been collected, but by the analysis that is conducted on it. Only after it's transformed into valuable assent that can be monetized.
Without a doubt, the amount of data has increased drastically with the rise of online users, the development of data analytics solutions, including AI, that can be even applied to analyze and arrange unstructured data is crucial. There is no possibility for humans to analyze 70 trillion data points available on the Internet, but with AI, there is no such thing as data overload. Given the fact, that the Big Data market worth is estimated to grow from $35 billion up to $103 billion by 2027, analytics and Big Data have fundamentally changed business practices in their sales and marketing functions.
What are the possibilities? How will AI shape the finance industry?
According to a global survey by the Cambridge Centre for Alternative Finance (CCAF) at the University of Cambridge Judge Business School and the World Economic Forum suggests, which interviews 151 financial institutions, including both incumbent firms and FinTech’s hailing from more than 30 countries, AI is a crucial business driver across for them in the industry. Around 64% expect to become mass adopters in a span of two years. The possible AI applications must always be considered as part of a broader strategic objective. It has extraordinary potential for positive effect if organizations adopt it with adequate ingenuity, judiciousness, and care.
Financial Advisory Services
AI collects and analyzes data and can easily predict user behavior and generate individual experience for customers. Therefore, an AI-driven personal financial assistant will be able to process a client’s quality data and create risk profiles, as well as offer the best solutions for triggers related to taxation, debt, and investment. Advisory will allow the user to assess their overall financial status and assign it the appropriate rating. The end-user thus receives a number of benefits — firstly, full analytics for all their operations; secondly, it assists the client in improving their financial position. For example, by shifting a low-yield deposit into a bonded ETF, refinancing a mortgage loan in a partner bank, or obtaining a credit card on better terms.
Fraud Detection And Management
Fraud is an extremely serious issue in the financial field. And here is where AI saves the day. It can use past spending behaviors on various platforms and detect odd behavior, such as using a card from another country just a few hours after it has been used elsewhere, or an attempt to withdraw an unusual sum of money. Since the system learns from experience, it will make even more sophisticated decisions about what can be considered fraud and what cannot in the future. For example, if it detects a transaction as a fraud and a human being corrects that as not a fraud, the AI will learn from that experience and develop new decision making.
Customer services
AI-based robots are replacing humans in customer services and the trend for using bots for services is increasing. Whether in healthcare, finance, or shopping, there have been various bots integrated, that perform a task that varies from handing queue ticket to giving out full on service on the matter. Chatbots have proven to be a powerful tool for customer satisfaction and help drastically save time and money for companies. The further development will the AI to go through thousands of personal financial records to come up with a solution in just a few seconds. Artificial intelligence allows creating heterogeneous investment portfolios and giving recommendations analyzing technical indicators, fundamental indicators, and macroeconomic statistics.
Regulations
There has been a rising awareness of data privacy and media exposing scandals surrounding the risk of exposing data among the public. No matter how transparent companies try to be with data collection, the news surrounding the topic speaks volumes. A simple google search with keywords «Facebook» and «Data privacy» immediately give out articles that present controversial information on the topic.
On May 25, 2018, the European Union presented the GDPR- General Data Protection Requirements. This is a new set of standards created for bigger protection of personal data. It covers the trade of data outside the EU zone. The main idea of the regulation is to give the users power over their personal data and how it is used and spread back. This regulation is quickly reshaping the way companies use data in their operations now, particularly in marketing. The new data permission law requires the companies to firstly receive direct consent from a person for their data to be used. The second aspect to comply with is data access. It is directly company responsibility to ensure that the person can access any data collected and remove the consent for collecting it. With this regulation, companies will need to achieve the utmost transparency with their actions evolving data collection. Last but not least, the companies will have to adopt data focus. This means that the data collected on a person needs to be justified as to why and for what purposes it was collected.
We are putting machines into more and more positions of making decisions. You can’t guarantee the particular intelligent system that is engaging in lifelong machine learning in a complex environment that is poorly understood.
When it comes to AI has and the data it can analyze, the possibilities of what it can do with that data once unleashed from any supervision are really in fact endless. This created a certain threat to the industry, relying solely on data collection, that has already faced a fair amount of backlash and controversies.
Transparency, trust, and accountability, as well as creating a mutually beneficial relationship with the users is the key to successful integration.
