# Machine Learning in Finance-Emerging Trends and Challenges

arXiv: https://arxiv.org/abs/2110.11999 · HTML: https://mlsanity.com/paper/2110.11999/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 31 references that are in the map.
- First posted on arXiv 8 Oct 2021.

## Builds on (most cited first, 13 of 13)

- [Convex optimization](https://mlsanity.com/paper/2106.01946/) (2021)
- [Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology](https://mlsanity.com/paper/2003.05155/) (2020)
- [Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models](https://mlsanity.com/paper/2009.10819/) (2020)
- [A Robust Predictive Model for Stock Price Prediction Using Deep Learning and Natural Language Processing](https://mlsanity.com/paper/1912.07700/) (2019)
- [Stock Price Prediction Using CNN and LSTM-Based Deep Learning Models](https://mlsanity.com/paper/2010.13891/) (2020)
- [A Time Series Analysis-Based Stock Price Prediction Using Machine Learning and Deep Learning Models](https://mlsanity.com/paper/2004.11697/) (2020)
- [Accurate Stock Price Forecasting Using Robust and Optimized Deep Learning Models](https://mlsanity.com/paper/2103.15096/) (2021)
- [Stock Price Prediction Using Convolutional Neural Networks on a Multivariate Timeseries](https://mlsanity.com/paper/2001.09769/) (2020)
- [Learning Undirected Graphs in Financial Markets](https://mlsanity.com/paper/2005.09958/) (2020)
- [Robust Analysis of Stock Price Time Series Using CNN and LSTM-Based Deep Learning Models](https://mlsanity.com/paper/2011.08011/) (2020)
- [Profitability Analysis in Stock Investment Using an LSTM-Based Deep Learning Model](https://mlsanity.com/paper/2104.06259/) (2021)
- [A Financial Service Chatbot based on Deep Bidirectional Transformers](https://mlsanity.com/paper/2003.04987/) (2020)
- [A neural network-based framework for financial model calibration](https://mlsanity.com/paper/1904.10523/) (2019)

## Built on by (most cited first, 2 of 2)

- [The Role of Federated Learning in Improving Financial Security: A Survey](https://mlsanity.com/paper/2510.14991/) (2025)
- [A Comparative Analysis of Portfolio Optimization Using Mean-Variance, Hierarchical Risk Parity, and Reinforcement Learning Approaches on the Indian Stock Market](https://mlsanity.com/paper/2305.17523/) (2023)

## Abstract (arXiv)

The paradigm of machine learning and artificial intelligence has pervaded our everyday life in such a way that it is no longer an area for esoteric academics and scientists putting their effort to solve a challenging research problem. The evolution is quite natural rather than accidental. With the exponential growth in processing speed and with the emergence of smarter algorithms for solving complex and challenging problems, organizations have found it possible to harness a humongous volume of data in realizing solutions that have far-reaching business values. This introductory chapter highlights some of the challenges and barriers that organizations in the financial services sector at the present encounter in adopting machine learning and artificial intelligence-based models and applications in their day-to-day operations.