Most of us are familiar with data-centric verification methods, although we probably haven’t heard that term used to describe these methods.
For the longest time the only way to verify customers involved verifying information reported by them on an application form. Earlier, these forms used to be paper-based, i.e customers would fill out a form and present them to verifying officials.
A perfunctory amount of digitization then led to these forms being “digitized”. Customers would then provide identifying data on a device, usually through a form using a browser or an application, which would be verified using a standard database.
Both these methods of verification are data-centric. This means that the data provided by customers is at the centre of the process and the veracity of KYC performed in this way is tethered to this self-reported data.
This data-centric approach to verification is, of course, advantageous in a few ways –
- it doesn’t cost businesses much to verify data
- it’s relatively frictionless, i.e verification can take place in the back while the customer fills up the application
- It’s a legacy technology, which means that it’s been in use for a long time and hence businesses are comfortable with this way of doing things
However, data-centric KYC is riddled with serious problems.
What are the problems with data-centric verification?
Businesses have undergone a period of rapid digitization over the last few years, particularly in the previous months owing to the COVID-19 pandemic. Industrial sectors are employing automated means to verify customers, conduct KYC and ensure compliance.
These efforts have been further buoyed by the regulatory sector’s implementation of video-based verification for financial institutions, securities intermediaries, and most recently the insurance industry.
This rapid pace of digitization has additionally exposed lacunae in certain methods of verification, one of these being the data-centric approach to KYC.
Security has always been a major cause for concern with data-centric verification. This issue is exacerbated by recent increases in cyber-attacks where hackers have acquired access to large swathes of customer data.
The issue is this – In any method of verification involving just data, there is no test to determine whether the person possessing the data is, in fact, the person to whom that data originally belongs to.
Therefore, any hacker with access to someone’s data can pass themselves off as that person and wreak havoc by taking loans in their name, obtaining insurance or even investing in securities using that person’s identity.
This sole problem has been responsible for countless cases of identity theft, fraudulent documentation and online fraud.
Deloitte’s 2018 Indian Banking Fraud Survey reports that fraudulent documentation makes up 15% of all fraud in the banking sector. RBI reports that Indian banks lost Rs. 109 crore to online fraud and theft in FY 2018, and Experian reports that among South-Asian countries, Indian banks have seen the highest increase in online fraud losses at 65%, with identity theft making up 28% of these cases.
How then can this problem be fixed?
A feasible identity verification system will always involve the “reduction” of a person into certain verifiable quantities.
In the case of data-centric verification, the customer is reduced to their data, which is in turn verified. We have seen that this data can no longer be considered an exclusive and unique identifier of the customer. Therefore we must now turn to something that is not as vulnerable as a customer’s data.
We must also be reticent of the fact that any new method of verification must also be feasibly implementable, and not too much of a far throw from the present systems of verification.
While data, as an abstraction, is no longer an accurate means for verification, the documents which are a record of this data, certainly are much more secure. Data can often be stolen, physical documents are much less likely to be.
Document verification, however, has (or used to have) its own set of problems. These issues have traditionally held back document-centric methods and tacitly been responsible for the advent of data-centric methods, but recent advances in technology have smoothed over the folds. Here’s how –
- Forged documents: The gripe with using documents for verification has usually been that physical documents can be manipulated and forged, rendering them obsolete as identifiers. Advances in machine learning have given us a way around this problem. SignDesk uses trained ML systems to detect forged and fraudulent documents, thus ensuring the veracity of document-centric verification.
- Too much friction: Data-centric methods, as we’ve seen, are quite frictionless. Document-centric methods, in contrast, involve the capturing of document images and selfies, making the verification process fragmentary. However, these problems have since been allayed using AI-powered workflows and smart application design. Our video KYC and digital verification solution is particularly seamless, using smart dashboards and intuitive workflows to ensure that the verification process is completed with minimal drop-offs.
- Cost-effectiveness: The cost-benefit balance has often tilted against document-centric methods. After all, document verification makes use of cutting edge ML & AI, which have traditionally been out of reach for most businesses. However, with the rising cost of fraud-related costs and compliance fines that businesses have had to shell out, this pendulum has now shifted. Document verification is more secure and faster, thus resulting in a significant lowering of KYC costs SignDesk’s video-based verification solution has provided banks with a 90% reduction in KYC costs and lowered the turnaround time for onboarding by 99%. Our solution is aimed at businesses across the board and is therefore an extremely cost-effective alternative to data-centric verification.
Now that we’ve seen how document verification solves the problems that data-centric verification is plagued by, let’s see how it stacks up.
Document-centric vs Data-centric
|Data-centric verification||Document-centric verification|
|Immune to data breaches||✔️||❌|
|Lower fraud & compliance costs||✔️||❌|
The only important point of contention here is the current ubiquity of data-centric methods.
Since data-based verification is a legacy method, businesses are more comfortable with its usage. However, new trends are quickly replacing this way of functioning.
Gartner estimates that by 2022, 80% of organizations will be using document-centric verification.Regulatory bodies are also shaping this trend towards document verification: RBI’s VCIP, SEBI’s VIPV & IRDAI’s VBIP all place a strong emphasis on verifying either the Aadhaar documents or other officially valid documents (OVDs) of customers via capturing an image of these documents and then verifying them.
Therefore, document verification looks to be the next frontier of KYC and businesses will have to quickly get onboard with this new & secure trend of verification.
But what provider of document verification should businesses trust with this task?
Safe & secure video KYC
Our video-based verification product uses ML-powered filters to fortify the document verification process and smart AI to make the entire process seamless.
Are you ready to lower your KYC costs & give your customers a smooth & secure onboarding experience? Book a demo with us now to verify your customers’ documents digitally!