Overall process

Deduplication is the task of finding records in a data set (MPI) that refer to the same Person. In order to guarantee data quality also should be make task of fraud defining. In case there are different persons with same document number/tax_id etc such cases won't be duplicated and it's a scope of fraud defining task.

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• data cleaning and preparation 
• blocking and finding possible pairs
• calculating of variables for each pair
• probability linkage using model
• finding master persons in a pair and deactivation of person(s) which are not masters
• fetch declaration(s) which belongs to deactivated person(s) and declaration termination 

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The WOE/IV framework is based on the following relationship:

• logP(Y=1|Xj)P(Y=0|Xj) = logP(Y=1)P(Y=0) (sample log-odds) +log(Xj|Y=1)f(Xj|Y=0) (WOE)
• WOE = ln (% of non-merge/ % of merge)

After decoding each variable we can apply model and calculate probability

Probability linkage using model

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Make a record into merge_candidates:

{"person_id" 
 "candidate_id" 
 variables}

For person_id in status 'NEW'  from  and score>=0.9 from merge_candidates find declaration in status 'VERIFIED' and change status to 'TERMINATED' and change persons.id.status to INACTIVE

OPS kafka consumer should be used for the declaration termination. Declaration termination and person deactivation should be done at the same time.
Change merge_candidates.status from `NEW` to `MERGED`