How much salary can I expect as a Fraud Risk Analytics Team Member in Kotak Mahindra Bank Limited in Mumbai/Bombay?

You can expect a minimum salary of 0 INR. The salary offered will depend on your skills, experience and performance in the interview.

What is the eligibility criteria to apply for Fraud Risk Analytics Team Member in Kotak Mahindra Bank Limited in Mumbai/Bombay?

The candidate should have completed the required education and people who have 1 to 31 years are eligible to apply for this job. You can apply for more jobs in Mumbai/Bombay to get hired quickly.

Is there any specific skill required for this job?

The candidate should have sound communication skills and sound communication skills for this job.

Who can apply for this job?

Both Male and Female candidates can apply for this job.

Is it a work from home job?

No, it's not a work from home job and can't be done online. You can explore and apply for other work from home jobs in Mumbai/Bombay at apna.

Are there any charges or deposits required while applying for the role or while joining?

No work-related deposit needs to be made during your employment with the company.

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Go to the apna app and apply for this job. Click on the apply button and call HR directly to schedule your interview.

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Fraud Risk Analytics Team Member

Kotak Mahindra Bank Limited

Fraud Risk Analytics Team Member

Kotak Mahindra Bank Limited

Mumbai/Bombay

Not disclosed

Work from Office

Full Time

Min. 1 year

Job Description

Team Member-Fraud Risk Analytics-SUPPORT SERVICES-Fraud Risk Management Unit

Conceptualize and implement early warning triggers & strategies from fraud perspective in both assets and liabilities
Develop analytics to identify suspected frauds in both credit and non-credit areas
Monitor efficacy of the analytical / predictive models implemented and advise updations/modifications
Monitor effectiveness of triggers and rules set for fraud identification and suggest refinements/additional rules to improve efficacy and accuracy
Design fraud monitoring framework through data analytics and collaboration with first line of defense
Analyze historical data on EWS, RFA and credit frauds across industry to develop and implement EWS triggers
Interpret data and present actionable insights to key stakeholders
Lead collaboration between stakeholders – RCU, product, analytics, IT, BSG & business to design/implement solutions w.r.t. Fraud identification and monitoring