Introduction
Objective:
In following chapters, We will work through Data Science, Machine Learning and Deep Learning concepts.
Each chapter will introduce and help us learn a new Data Science AI/ML/DL concept for Finance by actually doing it with real-life examples. These blog's target audience and projects are focused on Small, Medium and Large Enterprise ERP Systems.
Oracle, PeopleSoft, SAP, Tally, Intuit, QuickBooks etc. I will cover examples from ERP Domains like GL (General Ledger), AP (Accounts Payable), AR (Account Receivables), B2P (Buy to Pay), Expense, Travel & Time, HCM Human Capital Management, CRM etc.
What is General Ledger
GL serves as core of any Financial Management system.
It's objective is to keep detail and summary accounting information and produce numerous financial reports for your organization.
Often Small businesses see GL as Luxury item and think, it’s only useful for Big organizations. However, Even Big Organization operate in small units and merge into to Corporate Ledger.
So having a system to read, write and understand your Finance books brings extraordinary benefits to any size of business.
Technical Analysis
is the process of forecasting future Organization growth or stock prices based on studying (using advance charting and applying mathematical formulas) past stock prices and trading volume.
Technical analysis strongly believes that at any given point of time, stock price and trading volume reflects it current value and charting accurately captures all factors which can cause upwards or downwards stock prices movement.
Fundamental Analysis
is the process of forecasting future Organization growth or stock prices based on studying company financial statements like Income Statements, Cash Flow and Balance Sheets.
Techno-Fundamental Analysis
In this notebook and all my follow-up GL notebooks, I am proposing 3rd type of analysis.
With the use of Machine Learning, I want to apply technical analysis /ML algorithms to GL and SUB Ledger (accounting entries) Books.
I make no magical claim that any of my GL AI Notebooks will predict Organization growth or stock prices.
I strongly believe,
A. Using ML Algorithms to predict Growth/Stock Prices or Organization growth is very difficult using past prices/volumes OR GL/Finance data alone.
B. Using ML Algorithms to predict Growth/Stock Prices or Organization growth is very easy using past prices/volumes + GL/Finance + SUB Ledger (accounting entries) data.
Provided all sub ledgers/accounting entries are available, it is possible to predict Organization growth and lots of Organizations are already doing that.
However, it is incredibly difficult to do this kind of analysis because Huge ERP systems are difficult to maintain, and it takes a village to read, write and understand Big Financial data in an organization and apply any ML or non-ML logic/algorithm.
In following chapters, I’ll share very high level AI notebooks to understand and get you started with General Ledger, Data Science operations and Machine Learning.