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4 Major Challenges that Lenders Face During Employment Verification

June 20th, 2018
Read Time : 7 mins

Whenever one applies for a loan, the lender has to validate a lot of information provided by the customer. This information would be their name, their address, their contact details, their income and their employment status. This is done by deploying different methods which is why the turnaround time for loan approval is high. But CreditVidya’s EVE makes sure that verification of employment status is not one of them.
Current Challenges:
Company-domain Mapping: One of the biggest problem faced by lenders today is verifying the customer’s employer’s name. In a lot of cases, companies have different names from that of their parent companies. So figuring out and identifying which companies belong together is tough.
Email & Domain Details: Even when one figures the company name, information like its age, history and domain life are not available. Another problem is dealing with dummy companies that are incorporated for specific purposes- usually with the intent of misleading.
High Cost: The average cost of customer acquisition for lenders in India is between 1500-2000 INR (approximately). 22% of the loans given out in India, are small ticket personal loans. So the cost of customer acquisition is huge number when compared to the ticket size of the loans. As a general practice, the cost of customer acquisition should not exceed 2% because there are other explicit costs like cost of capital and margin that also have to be recovered.
TAT: The age old process of sending a person to verify employment status of the customer takes a couple of days. Plus, there is also possibility of human error. 
CreditVidya’s EVE for Instant Employment Verification 
EVE is a cloud-based API solution that digitally verifies the employment status of the prospective customer.
With turnaround time of less than one minute and simple 1 click verification process, EVE is the go-to solution to verify loan applications of salaried individuals.
It validates the input data- email ID and company name instantly, flags if it’s incorrect and gives a decision depending on the rules configured. This helps you detect fraud (if any) at the loan application stage itself. Also, the exhaustive domain checks and company checks that are run in the background, give you more information about the company- domain’s age, ROC details, Directors of the company etc.
The decision about the customer could be either of these-
Low Risk – You can waive-off the CPV (contact point verification) or FI (field investigation)
Medium Risk – You can refer this applicant for further investigation
High Risk – You are advised to give the loan application a miss
The decision is processed based on the rules configured in the engine. These rules can be customized to measure, meet and match the company’s risk appetite and lending policy. 
How about you try it?
Simply request for a LIVE Demo of EVE here. 🙂

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