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VERIDOS | FASTER NEW PASSPORTS THANKS TO MACHINE LEARNING

This is how passport applications can be validated automatically

Apply for a passport from home

In many countries, anyone wishing to apply for a passport must expect not only a processing time of several weeks, but also several visits to government offices. With Veridos’ identity solutions, this process can be reduced to a matter of days or even hours. A key component of this is the digital application process via an online platform: citizens submit their details and documents online, book an appointment and thus save valuable time.

The challenge is that the application data entered often differs from the existing records, meaning that staff at the relevant authorities have to manually correct the data, which is a labour-intensive process. This is where iteratec’s expertise in machine learning (ML) comes into play.

Greater transparency, less effort

Through the proof of concept, our team of software developers and machine learning specialists has demonstrated that the manual effort involved in validating application data can be significantly reduced. By using ML algorithms, the number of applications validated automatically can be significantly increased, thereby speeding up the passport application process.

Another key requirement of the project was the transparency of the decisions made by the ML model when verifying application data. These decisions are made transparent within the system and presented in a way that is comprehensible to staff.

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The requirements

When an applicant enters their details on the website to apply for a passport, these are cross-checked against the records held by various authorities. This often results in discrepancies, which necessitate manual follow-up work. The requirements set for us were:

As a first step, the data should be analysed to identify the most common causes of rework, in order to evaluate effective ways of increasing the number of cases processed automatically.

Based on the decisions made by case officers to date, a machine learning model has been developed that predicts the results of manual checks. The model serves as the basis for further automation of the decision-making process.

The country-specific circumstances posed a challenge: names can be transliterated into the Roman alphabet in various ways. This leads to inconsistencies, which the model must either allow or reject accordingly.

It was particularly important to rule out false positives – that is, applications containing invalid data – as these would necessitate rework due to invalid data at the latest when the passports were issued.

Validation of application data using machine learning

None of the methods used to date have been able to provide satisfactory support for the automated verification of data. Our proof of concept demonstrated how the use of machine learning can significantly increase the number of automatically validated application data records. Furthermore , in the prototype we developed , the decisions made by the machine learning models were presented to staff in a transparent and comprehensible manner.

Both the agile project approach and the prototype we developed form the basis for the system’s further development and deployment in production.

Digital Champions – that’s why

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The amount of manual work can be significantly reduced.

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The processing time for passport applications can be reduced.

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We support the digitalisation of public administration.

Working with iteratec on this proof of concept was excellent. The team quickly got to grips with the subject matter and was able to provide valuable input in no time at all. The agile approach enabled us to achieve rapid results, which were continuously refined. We look forward to the next steps!

Michael Schalk, Senior Product Manager at Veridos GmbH