What factors does Iddiligence examine to validate the content in an ID card or a payslip
Validating legal or financial documents isn’t an easy task for companies which must deal with thousands of ID cards, payslips, payment receipts, direct debits, driving licences or tax declarations.
By: Alberto Iglesias Fraga, journalist specialized in digital economy.
Simply imagine manually examining each one of those documents: a worker must gather and organize all the information he needs to complete a task (approve a loan, an insurance, etc). Then, they must look for the exact data, crosscheck the information to validate it and introduce it in a system which allows its management further on. What does this imply? Hundreds of man-hours without added value and subject to errors which would put paid to all our compliance obligations.
Fortunately, new digital technologies have provided solutions specifically directed to meet these needs, such as Iddiligence. These tools, which have optical character recognition (OCR) systems integrated in their core, also combine automatic technologies to identify not only the type of document present, but also the data it contains and the presence of other elements, such as signatures or photographs. To draw an analogy, it would be like a scanner with artificial intelligence which first ‘guesses’ which digital document it has, to then examine, like a detective, all the sections which compose the file and extract the relevant data from it in the format required by the company.
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In this way, companies can obtain a complete analysis with all the information about the individual and their economic situation in a matter of seconds. We are referring to data so varied as the identity of a person (from their ID card or passport), their credit rating and financial history (thanks to the tax declaration, payslips, pensions or direct debit), current residence (through electricity, water or telephone bills) and even if they possess a car or not (driving license). Factors which, combined, practically provide a 360º vision of the subject: we will know who it is, how much they gain, how much they spend, where they are located and what their standard of living is.
We can also add another piece of information which is becoming more common in user identification in online services: biometric recognition. Through a facial recognition technology, these tools capture a client’s identity based on facial patterns, registered previously thanks to the image on our ID card. And, to clarify this: it doesn’t matter if we look good or bad (as it commonly happens) in our ID card photo: what this function measures are variables such as the distance between our eyes and the shape and general proportions of our face.
They are parameters normally required in quotidian situations such as asking for a mortgage (in which, as well as identifying the person, they need proof of our capacity to assume payments), subscribe to a service which by law requires a documentation review (such as a bank account, an insurance policy or activate a phone line) or simply to feed truthful information to the company’s Big Data systems to be able to offer more personalized services to our consumers.
However, these are only a few examples, as the application of an extraction and document
validation system such as Iddiligence is noted for having an enormous flexibility and capacity to adapt to different industries. In the case of Addalia’s solution, without going further, we are referring to around 60 preprogramed extractions from the most common documents managed daily in administrative offices and 90 other predefined validations in documents and various specific validations such as obligatory documentation review and information crosscheck between data and documents.