ExCreLo - RWA Movement Analyser

[#1]

Team Name	ExCreLo
Track	Banking
Use Case	RWA Movement Analyser - With Abstraction capability to "any" number; "any" domain - due to standardisation concepts introduced across base data profiling, Modeling Data preparation, Model Build (ML techniques) and Visualisation based on model drivers per modeling outcome. Bias analysis included.
Technology	Viya (Hackathon23)
Region	EMEA
Team lead	M Ayerst
Team members	@jacques.Venter3@absa.africa; @David.Logan@absa.africa; @Dewald.Fourie@absa.africa; @Ndiafhi.Madamalala@absa.africa; @Ivan.Ruhinda@absa.africa; .@JohannesJoachim.Labuschagne@absa.africa;
Social media handles	NA
Is your team interested in participating in an interview?	Y
Optional: Expand on your technology expertise	Various competency levels and broad historical sas application coverage.  Novice VA user managed with distinction to build the Visualisation in SAS Viya.  Utelised Information Catalogue with success.  Wrangled a 5 GB data set with ease through Jupyter and SAS Hackathon environment.

Jury Video: 

Pitch Video: 

[Atabarut]

Can be productized fast, good job!

[alexkwiatkowski]

Great work! I like what you've created here. Well done. 

Alex

[davidlogan]

Thanks Atabarut and Alex for the comments, the team worked well together, it's notable that 1 of the team members started working with SAS in Jan 23 (only 3 months experience) but did great work using the Data Explorer and got up to speed very quickly. He also did the data anonymisation and auto-variable reduction as general solutions which speaks to the flexiblity of SAS.

[JVenter4Absa]

Thanks @alexkwiatkowski and @Atabarut for the positive feedback. We are very keen to productionalise this within our environment. We've demonstrated to business stakeholders what can be done and what benefits can be achieved. As a result, business stakeholders have allocated resources to this for further productionalisation. So the Hackathon was a great success for us 🙂