Recently, AI has spread its impacts on various fields and finance is not an exception. With over 15 years working in banking industry, Mr Le Cong Binh brought to VFS not only the theories but also the practical use case that reflected the best how AI was affecting this industry.

1. Artificial Intelligence in
Finance
Le Cong Binh, MBA
Vietnam Frontier Summit 2019

2. LE CONG BINH, MBA
Applied Mathematics and Informatics, VNU-HUS
MBA, NEU
Advanced Data Science with IBM
15+ years in banking industry
10+ Data warehouse, 3+ Data mining experience
binhlc@gmail.com

3. Data science methodology
Data science algorithm
Use case in banking sector
CRISP-DM: cross-industry process for data mining
Time series, Machine and Deep learning
Risk, sales and customer insight
TABLE OF
CONTENTS
01
02
03
Want to hear your question
04 Discussion

4. Harvard Business Review
“Data Scientist the sexiest job of the 21st Century ”

5. Foundational methodology
Business acumen
Communication skills
Data processing
Data visualization
Mathematical
Statistical
Machine Learning
Deep Learning
Programing

6. DATA VISUALIZATION
Business acumen
Communication skills
Data processing
Data visualization
Mathematical
Statistical
Machine Learning
Deep Learning
Programing
“The most of time in
data science is Collect,
Cleaning and
Organizing Data”

7. Business acumen
Communication skills
Data processing
Data visualization
Mathematical
Statistical
Machine Learning
Deep Learning
Programing
“Python is the top of programing
language”

8. DATA VISUALIZATION
Business acumen
Communication skills
Data processing
Data visualization
Mathematical
Statistical
Machine Learning
Deep Learning
Programing
Data
Visualizations make
big and
small data easier for
the human brain to
understand,
and visualization also
makes it easier to
detect patterns,
trends, and outliers in
groups of data

9. Data Science
Algorithm
02
Input + Rules => Target
Input + Target => Rules

10. ALGORITHYM AR MA SMA
ARIMA ARIMAX
VAR VARMA
A series of values of a quantity obtained at successive times, often with
equal intervals between them
Holt Winter’s
Exponential

11. ALGORITHYM Supervised
Unsupervised
Reinforcement
Data is the “new oil” that intelligent algorithms consume: the more data
is given in input, the more accurate the prediction output is.

12. ALGORITHYM
Algorithms tree

13. DEEP LEARNING FRAMEWORK
Convolution network
Sequential
RNN
LSTM /GRU
RBMs
Neutral
Epoch
Dense
Layer

14. LONG SHORT TERM MEMORY

15. 15
MODEL
EVALUATION
ESTIMATORS = {
'KernelRidge': KernelRidge(alpha=1.0),
'BayesianRidge': BayesianRidge(compute
score=True),
'SVR': svm.SVR(),
'GPR': GaussianProcessRegressor()
}
X train, X test, y train, y test, X pred =
CreateTrainTestDataset()

16. Banking use case03
By design, intelligent algorithms are good at solving specific problems
and cannot deviate from what they were designed for. An algorithm
trained to detect suspicious payments would not be able to detect any
other suspicious activity related to trading, for instance.
In addition, algorithms are purely rational and lack essential factors
such as emotional intelligence and the ability to contextualize
information, unlike human beings. That’s why banking Chabot's often
disappoint: they are “smart” but lack empathy.

17. USE CASE
Source:
https://emerj.com/ai-
sector-overviews/ai-
in-banking-analysis/

18. BASIC USE
CASE

19. USE CASE

20. SUMMARY
1. Financial institutions may need to consider restructuring their
business models in order to harness this new technology.
2. There will be a need to create job positions in relation to AI
3. However, proceed with some caution due to the existing
challenges in terms of trust, privacy and data issues.
4. They must also keep an on RegTech (Regulatory Technology) to
better address new regulatory requirement.
5. Overall, firms should embrace AI now or face the possibility of
being left behind

21. 21
FOR
BEGINER
Roadmap reference:
https://medium.com/ml-research-lab/data-scientist-
learning-path-2018-a82e67d49d8e
Online Training:
https://www.coursera.org/professional-
certificates/ibm-data-science
https://cognitiveclass.ai/learn/data-science

22. Does anyone have any
questions?
binhlc@gmail.com
THANKS!