Machine learning in taxation

1. Save taxes without breaking laws using ML
Novel use cases for ML in the
accounting and tax space

2. Intro
• Chartered Accountant and former tax analytics director
at EY
• Co-founder at a data sciences solutions startup
• Currently building GST solutions with data sciences

3. Why ML in taxes?
• Finding tax savings options without breaking the law is
the holy grail in tax consulting. There are differences in
impact of taxes, therefore opportunities, for e.g
– The effective tax rate for a company making a profit up to Rs 1
crore was 30.26% in 2015-16 while the corporate tax rate was
25.90% for those with profits greater than Rs 500 crore
– Drugs and pharmaceuticals paid tax at 24.2%, electronics paid
tax at 35.5%
Source: Indiaspend.com

4. Tax laws are not really English
The major input variables are not simple:
A. Laws are unstructured text data and are continuously changing
B. Legalese is not exactly English
C.Financial statements are a mix of structured and unstructured
information
D.The level of precision required in tax decisions is high

5. Our method to the madness
• Tokenization
• Stemmers / Lemmatizers
• String distance algorithms
• LSTM models
Combined with
• Tax and accounting domain knowledge

6. Our key learnings
• Domain knowledge trumps ML results in ultimate
decision making
• Kaggle style ensembling and blackbox solutions are
much harder to sell
• Feedback and reinforcement learning is critical to
achieve higher accuracy
• Feature engineering is very important

7. Thankyou
Twitter: gsj2
Email: jay@vyakya.com
Linkedin: https://www.linkedin.com/in/jayendrangs