AI (ARTIFICIAL INTELLIGENCE) AND ML (MACHINE LEARNING) IN THE FINTECH INDUSTRY
Almost every industry, especially finance, is discovering new opportunities to use AI and ML beneficially. Artificial intelligence and its subfields solve problems, save time, and give organizations the advantage of automating manual processes involving data and decision-making.
What is Artificial Intelligence (AI)?
Artificial intelligence (AI) is a wide-ranging computer science that mimics human intelligence and behavior and is capable of performing tasks, solving problems, and triggering actions without human interference.
What is Machine Learning (ML)?
Machine Learning (ML) is a type of AI that allows software applications to predict outcomes based on previous data input. Examples are e-mail spam filtering and online fraud detection.
The purpose of AI and ML
The field was first introduced in military science and statistics with the help of philosophy, math, cognitive science, and psychology. The original purpose of developing artificial intelligence was to create computers that can reason on input and explain the output. That would consume less time and effort than the manual process.
The benefits of AI and ML
More sources of data input
Increased operational efficiency
Better, faster decision making
The Future of AI and ML
A study by Oxford University and Yale University estimated that in the next 120 years, artificial intelligence could replace all human jobs. Experts expect AI and ML to transform scientific methods, lead foreign policy, enable next-generation consumer experiences, address the climate crisis, and create personalized medicine in the next ten years.
How AI and ML are reshaping the Fintech industry?
The global market value of AI in the Fintech industry reached USD 6.67 billion in 2019 and is estimated to reach USD 22.60 billion by 2025. Fraud detection, data-driven trading, automated claims, virtual banking assistance, and reliable credit decisions can be improved by the AI and ML in the Fintech industry.
“Almost all fintech use data and most analyze it through AI. Know Your Customer (KYC) and Anti Money Laundering (AML) are areas where AI-powered robots can rapidly screen massive amounts of information and find links between globally distributed information sources. When dealing with customer data or making decisions that may impact your customers, we should follow the key regulations that foresee a risk-based approach towards AI" says Andreas Braun, the Director of Artificial Intelligence and Data Science at PwC Luxembourg.
Following are a few examples of how AI and ML are used in the Fintech industry:
Security and fraud detection by detecting suspicious activities and notifying the users. Like cybersecurity in cryptocurrency and block chain.
Customer support such as chatbox would give an immediate response.
Loans through money lending apps are faster and more efficient with the client risk profile.
Insurance companies are using AI and ML to calculate someone’s level of risk by analyzing their activities.
AI and ML development in Mongolia
Although Mongolia has many mathematically skilled technical experts, we are fresh ground for artificial intelligence and machine learning. One of the leading organizations of AI and ML in Mongolia is Machine Learning UB (MLUB). The community has been operating since 2019 and consists of artificial intelligence and data science professionals. MLUB aims to collaborate with international experts and organizations to promote AI and DS in Mongolia and creates opportunities for Mongolian data scientists to learn from international experts.
To mention some of the AI projects done by Mongolian experts, ChewBe, an application dedicated to promoting healthy eating habits. The artificial intelligence counts bites and chew rates with 85 percent accuracy through a mobile phone camera. Another one is the recognition system of the vehicle registration plate. With the help of a camera, the algorithm can identify the plate number of vehicles. The system is developed to be more stable.
AI in fintech is becoming a global trend. In the finance and banking industry, AI and ML are adapted to satisfy customers' needs and save time and money for organizations by making predictions and solving problems.