Intro: Shaping Nepalese Banking Sector With AI

Nepal has the GDP growth rate of around 6% as per the data of world bank in 2019, one of the major contributor of GDP is service sectors. Banking Business is largest service industry of Nepal. Banking sector is considered as the high tech adopting industry in Nepal and has adopted the banking practice of west. 

At the end of decade 2019, the big thing rose up is the use of Machine Learning and Artificial Intelligence. Nepal is far behind in adopting the changes and Banking industry has not changed the ground working platforms. The recent trend of increasing interest on deposit and creating unhealthy competition in the overall industry which created decline in GDP growth rate and has hit hard to small and medium sector business. 

Banking sectors should looks forward to add more dimension to the business rather than pulling and pushing each other customers. Banking industry should start from satisfying the customer from personalizing their services and adding more analytics to their data on the first hand. This blog contains few tools of Artificial Intelligence, Machine Learning Algorithms and Deep Learning. 


Deposit: 
Deposit is main ingredient of Banking Industry; Machine Learning Module should be used by banks to identify the behavior of depositor. Module well designed and trained based on banks own's past years data can help banks to answer questions like, what are the chances of adding deposit by same depositor? Whether or not depositor will transfer the deposit to other banks? How the behavior of depositor changes on the basis of Demography, Employment History, Family Pattern? What are the chances of Fixed deposit to be with drawn? These all and many more question can be answered.

Loan & Advances: 
Loans and Advances are basically outcome of the ingredient, which generates revenue. Modules which are trained and tested on banks own data can predict the customer behavior, the accuracy for such prediction can go beyond 90% if data are labeled properly. Modules like regression analysis on the basis of specific industry growth, and use of multi variable regression analysis can help predict banks to get answers on which industry to focus. 

Revenue Prediction:
Main source of revenue generation of Nepalese Banks are interest income, this is the place where loan defaulter can be predicted accurately, and measures can be initiated before interest due date. Recurrent Neural Network (RNN) can be used for creating Deep Learning Neural Module. 

Others Sectors where Machine Learning need to be used are:
i.   Map Pattern Analysis of Deposit & Loans (Companies Like ESRI and Near are world leaders).
ii.  Card fraud Detection.
iii. Personalize Financial Management.
iv. Consumer Spending Analysis.
v.  Generating Customer Satisfaction Index.


In the Nutshell, Banks need to lend money more on the basis of data analytics and need to identify the trend and have module deployed to get time series forecast. Banks need to understand their responsibility on nation building and need to keep interest rate on check. 

Thank you for reading, I will be blogging more detail analysis on Banks and other business and how AI can RE-Shape.







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