Merge branch 'master' of https://github.com/pkiage/tool-credit-risk-modelling

README.md

@@ -61,10 +61,10 @@ python setup.py install
 streamlit run app.py
 
 ## Deployed setup details
-For faster model building and testing (particularly XGBoost) a local setup is recommended.
+For faster model building and testing (particularly XGBoost) a local setup or on a more powerful server than free heroku dyno type is recommended. ([tutorials on  servers for data science & ML](https://course.fast.ai))
+
+[Free Heroku dyno type](https://devcenter.heroku.com/articles/dyno-types) was used to deploy the app
 
-Free Heroku dyno type was used to deploy the app
-https://devcenter.heroku.com/articles/dyno-types
 
 
 Memory (RAM): 512 MB
@@ -181,3 +181,11 @@ code2flow src/models/util_predict_model.py -o docs/call-graph/util_predict_model
 ```shell
 code2flow src/models/util_model_comparison.py -o docs/call-graph/util_model_comparison.svg
 ```
+[A list of open problems in DeFi](https://mirror.xyz/0xemperor.eth/0guEj0CYt5V8J5AKur2_UNKyOhONr1QJaG4NGDF0YoQ?utm_source=tldrnewsletter)
+* Automated risk scoring of lending borrowing pools -> Increasingly important problem
+  *  One alternative way of looking at the problem would be, looking at a function for calculating the probability of default given the pool of assets you have.
+* Managing Risk for lenders and distributing risk/ Undercollateralized Loans
+  *  Tradfi is plagued by NPAs [(Nonperforming assets)] but still ultimately fall back to some sort of credit score establishment [[Spectral finance](https://www.spectral.finance/) solving this, but still an open problem].
+  *  But still, most credit score methods would rely on onchain history for credit establishment, we are moving towards privacy-centric defi is this approach extendable to that idea? [Homomorphic encryption could provide a solution]
+
+