Serving trust-on-demand through screening candidates
Tell us more about trust-on-demand? And who does it cater to?
We have been in the screening business for a little over a decade now and we have come to realize that one of the biggest domains that we were serving was employee screening. Typically it takes about 15 to 20 days to screen people and that is a long time, particularly in organizations that have high attrition. It is very difficult for them to wait for such a long time. As a result, only 6% of the organization or typically 6% of people in India get screened. 94% of the people find jobs without getting screened.
When food can be delivered to you instantly, a cab can come to your doorstep within a few minutes and medicines can be delivered on demand, why can’t we deliver trust on demand? You have an employee walking into your office for the first meeting. By the time he walks from the reception to your table, we would have background checked him. We put a trust infrastructure in place instantly and tell you within a few seconds, whether the guy is actually what he claims to be or not. This is called trust-on-demand.
What are the risks of not actually screening candidates? And why is solving this problem so important?
Great question. We have been looking at screening data since the last 10 – 12 years. We screen 14 – 16% of resumes every month, about 100,000 of them. Many of the resumes have discrepancies in them; either employment is being forged or an education claim is fake. And considering that only 6% of the population gets screened, it is a very scary thing. 94% of them are going into the system without a proper screening process because employers do not have the time to wait.
Tell us about the challenges that you faced in the last 4 years, doing this in India while creating that infrastructure. It is clearly a very difficult task. Tell us what has been the journey so far and where are you today?
When we started this journey 4 years ago, the challenge for us was “how do we get a unique identifier tag for an individual?” There are about 200 Million records in India. We built a machine learning algorithm which picks up a name within a few seconds, irrespective of how the person has written it. We have a team which services organizations to transform to a tech product company. It was a shift for us as an organization; the whole DNA had to be changed, where we had to get people who were thinking technology all the time.
I faced a very interesting situation. I took a cab ride in Mumbai where the driver asked me if he could work for me because we were looking for a driver. So, between the time he picked me up from Point A and dropped me off at Point B, I had my office do a background check on him, telling me by the time I reached Point B, that this guy had a criminal history in his hometown. I would obviously never look at the guy. On the face of it, he sounded like a good person. Somebody who has a physical assault history could be hired as a driver by anybody. It took us exactly 10 minutes to eliminate him from the list of people we looked at. Wherever you think there is a need for you to trust either a company or an individual and you do not have too much of time between your first meeting and your actual association with the person, that is where we fit in.
What is the vision for this product for the future?
I think the future is great. We are also helping banks and are able to tell them within a few seconds, whether a person has credit worthiness or not. Otherwise, it would have been almost impossible for them to find out, again using the same algorithms and the same entrants. We are talking to immigration authorities to see if we can do an authentication at the time of immigration of people leaving the country, of finding out if that person has a criminal record anywhere in the world.
An organization’s or a customer’s security is the driving force behind trust-on-demand. This cannot be compromised under any circumstances. Hence the importance of a comprehensive background screening process cannot be undermined.