Market Recommender System using machine learning by applying Stochastic gradient descent method

Tracking #: 630-1610

Authors:
NameORCID
Gurumurthy SwaminathanORCID logo https://orcid.org/0000-0001-6293-8668


Submission Type: 

Research Paper

Abstract: 

The insurance broking, mainly driven by suggesting the right market/carrier for the product where the client would like to cover for, by carefully making calculus on their history of data (like placements, bind, quotes and its ratios., etc ) these calculations help to evaluate the suggested market is the right fit for the client and it increased client retention (renewals). However, the current system may not a primitive enough to handle this case. This paper intended to analyze various machine learning algorithms to check if it has a primitive role in this area and to analyze how much the side data influences on deciding the scores.

Manuscript: 

Tags: 

  • Reviewed

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Date of Submission: 

Wednesday, April 22, 2020

Date of Decision: 

Friday, April 24, 2020

Decision: 

Reject (Pre-Screening)