Everyone must be able to use his or her rights. Therefore, Appjection strives to improve access to the law. At Appjection, they noticed that people were too lazy to challenge their traffic fines, even when the fines were unjust. This lead to their idea: an app where people can easily challenge unjust traffic fine on their smartphone.
In 2016, three students from Leiden University founded Appjection. At the start of their business, they managed to win the ‘De Brauw Legal Innovation Challenge’ in 2016 for which they received €25.000 euros of financial support for their business and free legal advice of De Brauw lawyers (Potjewijd, 2016).
Appjection makes it easy to file an objection against fines and other administrative decisions. According to the founders, only 2.5% of the submitted objections are currently officially wrongly declared (Arag, 2018). However, the actual number of unjustified fines is much higher according the founders of Appjection (Arag, 2018). A possible reason for this, is the lack of knowledge on how to draw up an objection and how to appeal after a rejection. Mostly, people think it is a waste of time and they just pay their fine because they do not think it is worth it to make the effort to object.
How does it work?
By using artificial intelligence, Appjection can handle large numbers of fines. The process starts by people taking a picture of their fine and uploading it to Appjection. The system automatically extracts all the information from the fine that is necessary. This is done by using text recognition from Google Vision (Koot, 2018). The software recognizes the words on the fine which are then converted into digital text. After uploading the fine, the system asks to answer several questions about the fine and the moment it happened. The customer also needs to indicate why he or she does not agree with the fine. Submitting the fine will only take a few minutes. Based on the information provided, the system searches the database for previous similar cases and generates a customized objection for every fine uploaded (Koot, 2018). Moreover, it checks whether there is a reason to make an objection and whether this objection has an actual chance of success. When there is no opportunity of success, Appjection makes no objection. If there is a reason to make a successful objection, the system automatically completes the process and files the objection.

After the system processed the fine, the customer will receive an acknowledgement with the reference number. One of the lawyers of Appjection will tell the customer within a few days whether the objection has a chance of success (Appjection, n.d.). If there is a chance of success, the system will file the objection either digitally or by post. If there is no possibility for an objection or chance of success, they will tell the customer why. As soon as something changes in the status of customers’ objection, they will be informed by e-mail (Appjection, n.d.).
Business model
Appjection is offering their service for free. It does not matter if Appjection wins or loses, the service is always free of charge. This is possible because they receive a compensation from the government when the objection is successful. In the Netherlands, there is a law which states that if professional legal aid is provided, and it is proven that a fine was deemed unjust, a compensation will be provided by the government (Zorab, 2018). The compensation they receive from the government contains a legal costs allowance, which is intended as a compensation for the costs of lawyers who provide legal assistance. Therefore, if the customer would have filed the objection himself, he or she would not receive this compensation (Appjection, n.d.).
Moreover, Appjection also partnered with some companies. This is a good initiative to be able to grow their platform as their business is dependent on the number of customers submitting traffic fines. They started a cooperation with legal assistance insurer Arag and Leaseplan, an international Dutch company that is specialized in car leasing (Arag, n.d.; LeasePlan, n.d.). Because of the cooperation with Appjection, their customers have the possibility to object unjust fines in a simple way.
Efficiency of the Model
The system works well for rather simple fines as the database is filled in manually by the founders until now. However, filling in this database will go automatically in the future through deep learning, where the software learns from the outcome of the cases and automatically updates the database (Koot, 2018). For now, this might be a drawback of the App, as it can mainly be used for rather simple fines.
Furthermore, as stated before, Appjection receives a compensation when they file an objection that turns out to be successful. Therefore, their business model is dependent on the number of fines that are submitted by customers. When customers only submit fines that have no chance of success or when they do not submit fines in general, the business model will not be sufficient. Their business model, or the value they create, is therefore dependent on customers. They create value from customers sending in their fines.
Future Plans
To build a bigger market, Appjection is planning to use the system for other areas as well. One of the founders, states that he sees opportunities in various other categories, such as taxes, UWV and flight delays (Mr. Online, 2017). Right now, Appjection consists of a team of 4 people including a Chief Technical Officer (Mr. Online, 2017). They believe that their business has a high potential to grow, not only in the Netherlands but throughout the whole world. Although the law in the Netherlands makes it easier to gain revenue, the founders do have plans to move abroad (Zorab, 2018). By building new partnerships and getting offered an investment of €100,000 euros recently in a Get In The Ring initiative, they might be able to realize these future plans (Get in the Ring, n.d.). By using this system, customers just need to sit and relax, while a robotic lawyer challenges their fines. What more do they want?
References
Appjection. (n.d.). Onterechte boete? Check binnen een paar minuten kosteloos of je bezwaar kunt maken. Retrieved March 6, 2019, from Appjection: https://www.appjection.nl/
Arag. (2018, September 14). LegalTech startup Appjection slaat met ARAG handen ineen in strijd tegen onterechte verkeersboetes. Retrieved from Arag – Persbericht: https://www.arag.nl/medien/pdf/persbericht_-_onterechte_boetes_aanpakken.pdf
Arag. (n.d.). In beroep gaan tegen verkeersboete. Retrieved March 6, 2019, from Arag: https://www.arag.nl/particulier/reizen-en-verkeer/verkeersovertredingen/bezwaar-verkeersboete/index.html
Get in the Ring. (n.d.). 600k investment offers live on stage at Get in the Ring Netherlands 2019. Retrieved March 6, 2019, from Get in the Ring: https://getinthering.co/600k-investment-get-in-the-ring-netherlands/
Koot, J. (2018, October 25). Robot vocht al 2000 Nederlandse boetes aan. Retrieved from Financieel Dagblad: https://fd.nl/futures/1274924/robot-vocht-al-2000-nederlandse-boetes-aan#
LeasePlan. (n.d.). Informatie voor leaserijders. Retrieved March 6, 2019, from LeasePlan: https://www.leaseplan.com/nl-nl/mijn-leaseauto/
Mr. Online. (2017, November 7). WHIZKIDS BESTORMEN LEGALTECHMARKT. Retrieved from Mr. Online: https://www.mr-online.nl/whizkids-bestormen-legaltechmarkt/
Potjewijd, G. (2016, June 6). De Brauw announces three finalists of its Legal Innovation Challenge. Retrieved from De Brauw Blackstone Westbroek: https://www.debrauw.com/newsitem/de-brauw-announces-three-finalists-legal-innovation-challenge/
StartupDelta. (n.d.). Dutch Tech to Watch – Appjection: Automated Professional Legal Aid. Retrieved March 6, 2019, from StartupDelta: https://www.startupdelta.org/dutch-tech-to-watch-appjection-automated-professional-legal-aid/
Zorab, J. (2018, February 5). Max Heck: Legal Geek of the Week. Retrieved from Legal Geek: https://www.legalgeek.co/read/max-heck-legal-geek-week/