Artificial Intelligence, Machine Learning, and Deep Learning are revolutionizing the financial technology industry.
Machine Learning and Deep Learning are growing and diverse fields of Artificial Intelligence (AI) that studies algorithms that are capable of automatically learning from data and making predictions based on data. Machine Learning and Deep Learning are two of the most exciting technological areas of AI today. Each week there are new advancements, new technologies, new applications, and new opportunities. It’s inspiring, but also overwhelming. That’s why we created this guide to help you keep pace with all these exciting developments. Whether you’re currently employed in the fintech industry, working with Produvia, or just pursuing an interest in the subject, there will always be something here to inspire you!
AI Research in FinTech
In order to take advantage of the exponential power of artificial intelligence, research is the first place to look. Luckily, we have done the hard work and compiled our favorite research papers as it relates to the financial industry.
- Predict daily stock prices based on historical stock prices using Support Vector Machines (SVMs) (Trafalis et al. 2000)
Financial Return Volatility
- Classify and select stock using Data Mining, Decision Tree and First Order Inductive Learner (Tan et al. 2006, Quinlan, 1996)
- Predict financial bankruptcy using Artificial Neural Networks and Support Vector Machines (SVMs) (Wong et al. 1997, Cristianini et al. 2000)
Sentiment Analysis of Financial News
- Determine sentiment of financial news headlines using Bidirectional Long Short-Term Memory (BLSTM) (Moore et al. 2017)
- Determine sentiment of financial news headlines towards a target company using Lexicon, Word Embeddings and Convolutional Neural Networks (CNNs) (Mansar et al. 2017)
- Offer client recommendations for bonds using Natural Language Processing (NLP) and Latent Dirichlet Allocation (LDA) (Hendricks et al. 2017)
Financial Microblogs and News
- Predict sentiment polarity and intensity based on tweets and financial news headlines using Word Embeddings (Saleiro et al. 2017)
- Predict mortgage risk based on housing prices, average incomes, and zip-code-level foreclosure rates, national-level prime and subprime mortgage rates using Deep Neural Network (DNN) (Sirignano et al. 2016)
Pratical AI In FinTech
There are many companies that are already using AI, machine learning, and deep learning in their products and services. Here are some of our industry favorites.
- Predict daily S&P 500 closing values based on historical S&P closing values, European and Asian/Oceanian indices using Deep Learning (Google)
Access Student Affordability and Creditworthiness
- Determine the creditworthiness of new and temporary international student arrivals using Machine Learning (SelfScore)
Credit Score & Loan Analysis
- Process data and make decisions (such as credit-related) quicker and efficient (Affirm, ZestFinance, BillGuard)
- Detect fraudulent patterns by analyzing historical transaction data (Feedzai, Nymi, Eyeverify, Biocatch)
Building Trading Algorithm
- Create chatbots, aka Robo-advisors, that calibrate financial portfolio based on goals and risk tolerance of the user (Betterment, Wealthfront)
- Create more secure user authentication security systems using Facial Recognition, Voice Recognition, and Biometrics (Facefirst, Cognitec)
Sentiment / News Analysis
- Understand how account holders are spending, investing, and making their financial decisions (Venmo)
AI Ideas for FinTech
Want to explore your own fintech models? There are many artificial intelligence technologies that can be applied in the financial industry. Here are some ideas for your next data science project.
- Predict the stock market based on S&P500 daily resolution using Deep Neural Networks (DNN)
- Offer product or service recommendations by weighing previous account activities against current data provided by the client and from elsewhere using Machine Learning
- Predict the effectiveness of a marketing strategy for a given customer by analyzing web activity, mobile app usage, response to previous ad campaigns using Machine Learning
- Generate financial reports using Natural Language Generation (NLG)
Sales / Recommendations of Financial Products
- Create robot-advisor to suggest portfolio changes or a particular car or home insurance plan using Natural Language Processing (NLP) and Natural Language Understanding (NLU)
- Detect financial fraud using Anomaly Detection
- Predict if a sharp move in one asset affects another asset using Impulse Response or Granger Causality
- Predict if an asset diverges from other related assets using One-vs-Rest Multiclass Classification
- Predict what factors are driving asset pricing using Principle Component Analysis (PCA) or Independent Component Analysis (ICA)
- Predict if an asset will revert after moving excessively using Principle Component Analysis (PCA) or Independent Component Analysis (ICA)
Financial Event Occurrence
- Determine the most common signs of market stress using K-Means Clustering
- Predict volatility based on a large number of input variables using Restricted Boltzmann Machine (RBM), or Support Vector Machines (SVMs)
- Understand the sentiment of an article or news source using Bag-of-Words Models
- Understand the topic of an article or news source using Term Frequency–Inverse Document Frequency (TF–IDF)
Financial Execution Speed
- Understand the optimal execution speed using Partially Observable Markov Decision Process (POMDP)
- Adjust portfolio allocations by clustering certain assets into classes that behave similarly using K-Means Clustering, Balanced Iterative Reducing and Clustering Using Hierarchies (BIRCH), Ward’s Method, or Spectral Clustering
- Optimize investment portfolios in quant finance using Reinforcement Learning (RL)
- Predict creditworthiness by analyzing the applicant’s financial status, current market trends, and relevant news items using Machine Learning
Do you work in the financial technology industry? Are you interested in developing artificial intelligence technologies to solve fintech problems?
Schedule a call with Slava Kurilyak, Founder/CEO at Produvia.