Early Risk Identification By Customer Consumer Profile Enrichment
Early Risk Identification for default behaviour in financial products, such as loans– cards/credits, can help lenders. With Segura, they will be able to utilize customer consumer profile identification based on income, psychographics, and product purchase behaviour patterns in all relevant categories.
Segura helps in customer risk identification.
Two applicants from the same area, PIN code 211006 Allahabad but having different incomes.
PIN code territories are too divisive in the profile of residing population to be judged as ‘one’ type of loan behaviour.
Today one can observe even different loan behaviour among ‘traditional’ negative PIN codes.
Typical PIN code ‘negative (sub-)areas, such as high crime, and difficult collection pockets, will be used by all players in the industry, and alone will not yield a competitive cutting edge.
Enhancement of applications by monthly household-level income based on residential building precise consumer data.
Add geospatial credit worthiness scores from traditional negative rated areas.
Breaking PIN code territories into homogeneous residential population profile pockets.
Monthly household-level income score
customer SEC classification
customer
lifestyle affinity segmentation score.
Finding the nearest branch/service station for the customer as per the custom distance criteria implemented custom distance criteria can be set upper regio-type based (Differentiated Urban Classes/Rural) city limits/custom distances for individual product lines.
A valuable mechanism for ‘New to Credit’ customer selection
EARLY WARNING SYSTEM FOR CREDIT CARD/LOAN DEFAULT PAYMENT BEHAVIOUR
Identifying risk clusters of specific customer lifestyle-income segments to default in
credit repayment
