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Smart Startups like Roadrunnr, Commonfloor verifying on-demand services staff

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Smart Startups like Roadrunnr, Commonfloor verifying on-demand services staff.

Mumbai | By Shashwati Shankar, ET Bureau | 26 Dec, 2015, 09.06 AM IST.

Tanvi Jadwani, a 24-year-old social worker living in Delhi, is wary of travelling home alone in a taxi, or calling a serviceman to fix a plumbing issue through on-demand services.

“After the Uber incident, I think it’s not unusual to feel a bit unsafe or wonder about the security measures that are in place before recruiting these professionals,” says Jadwani.

Identification, address and court record checks are mandatorily carried out by background verification firms that are tying up with on-demand home service startups. But are these checks foolproof, or are there any technological upgrades or any additional checks being done to ensure that the end consumer is safe?

A slew of background verification service startups claim to reduce the turnaround time for identification checks to a matter of seconds, introduce visitor manager applications, conduct continuous monitoring by repeating address and court record checks every 3-6 months, among other such measures. “On the arrival of a delivery executive, visitor manager applications will immediately notify the on-demand service startup about his presence in a building or home,” says Pravin Agarwala, founder of BetterPlace. He explains that this is done to ensure the safety of women and children at home.

Startups like TimeSaverz, Roadrunnr, Housejoy, Commonfloor verifying on-demand services staffThe visitor manager application eliminates the need for a delivery executive or service professional to enter their details into a log book in a building. If the individual has already gone through the verification process, his profile is registered in a matter of seconds on the application, automatically notifying the recruiter about his presence in that particular location. According to Agarwala, many on-demand services, depending on the category, experience a 7-15 per cent revenue loss due to side deals that are made with a consumer.

“Beauty services are on the higher end, while electrical and plumbing are on the lower end of the spectrum. When it comes to service executives cutting side deals with the end user, the visitor manager application could help identify this issue,” says Agarwala.BetterPlace, which recently tied up with Swiggy, includes TimeSaverz, Roadrunnr,Housejoy and Commonfloor in its clientele list. The firm also repeats its checks every 3-6 months to update its information.

“If you are a cab company and need your driver to go through a background verification check, it needs to be done very quickly,” says Ajay Trehan, founder of Authbridge. “We created an application where you can identify a passport, pan card or Aadhar card in a matter of seconds. We are continuing to improve the speed in other areas of verfication.”

According to Trehan, who counts Ola Cabs as a major client, their physical verification checks do not last more than 24 hours, but it’s the police record checks that are tedious. The criminal record check is a two-step process: one is checking through criminal databases which are made electronically available through law enforcement websites — Authbridge claims to complete this within four hours. The second involves a formal report coming in from the police department, which could take anything between 10 and 90 days, depending on the state.

“In 2016, big data analytics could play a huge role in expediting the police verification system,” says Nikhil Mulchandani, founder of InstaVeritas. “They have taken an initiative by introducing the Crime and Criminal Tracking Network System (CCTNS).” The CCTNS, if used regularly by the police, would ensure that all FIRs are stored in the data registry, possibly making it more effective to track potential criminals.

Ashok Hariharan, founder of IDfy, claims their criminal court record checks are done automatically, by using an intelligent algorithm system that can find an accurate match for common names that are spelt the same way or differently. “We keep learning algorithms, natural line processing to read different languages and statistical modelling,” says Hariharan, whose clients include LocalOye, UrbanClap and Servify.

According to Agarwala, since 10-15 per cent of blue-collar workers are showing a digital presence, 2016 could mark the emergence of mobile applications being used by workers to upload identification documents, leading to immediate verification results.

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