UmojaHack Nigeria: AXA Vehicle Insurance Claim Challenge by UmojaHack Africa
Can you predict if a client will submit a vehicle insurance claim in the next 3 months?
Prize
NGN 750,000
Time
Ended almost 2 years ago
Participants
204 active ยท 287 enrolled
Helping
Nigeria
Prediction
Insurance
Description

This is a private hackathon open to UmojaHack Nigeria participants. If you are a university student in Nigeria and would like to participate, contact Zindi Ambassador Femi Azeez.

When providing insurance, there are very few points of contact between customers and the insurance provider. Because of this, AXA Mansard needs to make every point of contact count; one of the most valuable of these is filing and settlement of claims.

AXA Mansard believes that to achieve better service level standards, they need to anticipate future demands in terms of claims request volume. This will allow them to better manage their resources while keeping the customer experience positive and the levels of satisfaction high.

The objective of this hackathon is to develop a predictive model that determines if a customer will submit a vehicle insurance claim in the next three months. This solution will help streamline financial planning at AXA and allow them to better serve their customers by understanding which customers are likely to submit a claim.

How to prepare for UmojaHack

  1. Add your university to your profile. Watch this YouTube video.
  2. Practice on a challenge and make your first Zindi submission. Watch this YouTube video.
  3. Make a team in preparation for UmojaHack. Watch this YouTube video.

About AXA Mansard (axamansard.com)

AXA Mansard is a member of the AXA Group, the worldwide leader in insurance and asset management with 166,000 employees serving 107 million clients in 64 countries.

AXA Mansard Insurance plc is rated B+ by A.M. Best (2016) for Financial Strength. The Company is also certified ISO 9001:2008 compliant by the Standard Organisation of Nigeria (SON) for quality management systems.

AXA is present in geographically diverse markets, with operations concentrated in Europe, North America and Asia Pacific. AXA is also present in Central and South America, Middle East and in Africa via operations in Cameroon, Gabon, Ivory Coast, Morocco, Senegal and Algeria. AXA has more than over 20 years continuous presence in Africa.

About DSN (datasciencenigeria.org)

DSN's mission is to build a world-class Artificial Intelligence (AI) knowledge, research and innovation ecosystem that delivers high-impact transformational research, business use applications, AI-first start-ups, support employability and social good use cases. We are committed to raising one million AI talents in 10 years and thus position Nigeria as one of the top 10 AI talent/knowledge destinations with 20% GDP multiplier impact. We are poised to accelerate Nigeria’s socio-economic development through a solution-oriented application of machine learning in solving social/business problems.

About H2O.ai (H2O.ai)

H2O.ai is leading the movement to democratize AI for Everyone. Their approach is to be open, transparent and push the bleeding edge. Their philosophy is to create a culture of makers: community, customers, partners, entrepreneurs and our own “makers gonna make”. Their vision is to democratize AI for everyone. Not just a select few. They enable this with their award winning, H2O Driverless AI, the platform that uses AI to do AI to make it easier, faster and cheaper to deliver expert data science as a force multiplier for every enterprise. H2O.ai wants everyone to explore, learn, dream and imagine a new future.

About AI6 (aisaturdayslagos.com)

AI6 is an active learning community which promotes Artificial Intelligence (AI) in Lagos. They organize structured study groups around core AI fields like Machine Learning, Computer Vision (CV) and Natural Language Processing (NLP). As Artificial Intelligence is set to revolutionize the 4th industrial revolution, we need to be ready and prepared. AI6 wants the next billion AI practitioners rise from AI6 communities. AI6 share a belief that AI will transmogrify almost (if not all) industries and they want to be on the forefront of making that happen.

About Microsoft (microsoft.com)

This hackathon is sponsored by Microsoft (Nasdaq “MSFT” @microsoft). Microsoft enables digital transformation for the era of an intelligent cloud and an intelligent edge. Microsoft has operated in Africa for more than 25 years. In that time they have built strong partnerships across the continent, helped bridge gaps in infrastructure, connectivity and capability, and are working to empower countries in Africa to digitally transform while creating sustained societal impact. Earlier this year, Microsoft opened Africa’s first hyper-scale data centers in Johannesburg and Cape Town, South Africa. Most recently, the company also announced the opening of two Africa Development Centers in Nairobi and Lagos, where world-class African talent can create innovative solutions for local and global impact.

Rules

This is a private hackathon open to UmojaHack Nigeria participants. If you are a university student in Nigeria and would like to participate, contact Zindi Ambassador Karim Amer Femi Azeez (azeezfemi17937@gmail.com).

Teams and collaboration

You may participate in this competition as an individual or in a team of up to four people. When creating a team, the team must have a total submission count less than or equal to the maximum allowable submissions as of the formation date. A team will be allowed the maximum number of submissions for the competition, minus the highest number of submissions among team members at team formation. Prizes are transferred only to the individual players or to the team leader.

Multiple accounts per user are not permitted, and neither is collaboration or membership across multiple teams. Individuals and their submissions originating from multiple accounts will be disqualified.

Code must not be shared privately outside of a team. Any code that is shared, must be made available to all competition participants through the platform. (i.e. on the discussion boards).

Datasets and packages

The solution must use publicly-available, open-source packages only. Your models should not use any of the metadata provided.

You may use only the datasets provided for this competition. Automated machine learning tools such as automl are not permitted.

If the challenge is a computer vision challenge, image metadata (Image size, aspect ratio, pixel count, etc) may not be used in your submission.

You may use pretrained models as long as they are openly available to everyone.

The data used in this competition is the sole property of Zindi and the competition host. You may not transmit, duplicate, publish, redistribute or otherwise provide or make available any competition data to any party not participating in the Competition (this includes uploading the data to any public site such as Kaggle or GitHub). You may upload, store and work with the data on any cloud platform such as Google Colab, AWS or similar, as long as 1) the data remains private and 2) doing so does not contravene Zindi’s rules of use.

You must notify Zindi immediately upon learning of any unauthorised transmission of or unauthorised access to the competition data, and work with Zindi to rectify any unauthorised transmission or access.

Your solution must not infringe the rights of any third party and you must be legally entitled to assign ownership of all rights of copyright in and to the winning solution code to Zindi.

Submissions and winning

You may make a maximum of 200 submissions per day. Your highest-scoring solution on the private leaderboard at the end of the competition will be the one by which you are judged.

Zindi maintains a public leaderboard and a private leaderboard for each competition. The Public Leaderboard includes approximately 50% of the test dataset. While the competition is open, the Public Leaderboard will rank the submitted solutions by the accuracy score they achieve. Upon close of the competition, the Private Leaderboard, which covers the other 50% of the test dataset, will be made public and will constitute the final ranking for the competition.

If your solution places 1st, 2nd, or 3rd in the final ranking, you will be required to submit your winning solution code to us for verification and you thereby agree to share all worldwide rights of copyright in and to such winning solution to Zindi.

You acknowledge and agree that Zindi may, without any obligation to do so, remove or disqualify an individual, team, or account if Zindi believes that such individual, team, or account is in violation of these rules. Entry into this competition constitutes your acceptance of these official competition rules.

Teams may win in one challenge category, and are encouraged to enter only one

  • Participants may compete individually or in teams of up to four people.
  • The teams will be judged based on their ranking on the dedicated Zindi leaderboard at the time of competition close.
  • All participants in the hackathon must be registered students (undergraduate or graduate) at the university they represent. Lecturers, University staff, and alumni may participate in a mentorship or advisory capacity.
  • Teams cannot collaborate or share information with each other.
  • All solutions must use machine learning, but teams are permitted and encouraged to use exploratory data analysis in building their solutions.
  • All solutions must use publicly-available, open-source packages only.
  • Solutions must use only the allowed and available datasets.
  • Participants caught cheating or breaking any competition rules will be immediately disqualified from the competition.
  • Universities caught cheating or allowing teams to cheat will be immediately disqualified from the competition.
  • The winning code must be submitted to Zindi for review and validation immediately at the close of the competition. In the interest of logistics, code review will take place only after the competition has closed and winners have been announced.

Please refer to the FAQs and Terms of Use for additional rules that may apply to this competition. We reserve the right to update these rules at any time.

Evaluation

The error metric for this competition is the F1 score, which ranges from 0 (total failure) to 1 (perfect score). Hence, the closer your score is to 1, the better your model.

F1 Score: A performance score that combines both precision and recall. It is a harmonic mean of these two variables. Formula is given as: 2*Precision*Recall/(Precision + Recall)

Precision: This is an indicator of the number of items correctly identified as positive out of total items identified as positive. Formula is given as: TP/(TP+FP)

Recall / Sensitivity / True Positive Rate (TPR): This is an indicator of the number of items correctly identified as positive out of total actual positives. Formula is given as: TP/(TP+FN)

Where:

TP=True Positive
FP=False Positive
TN=True Negative
FN=False Negative

For every row in the dataset, submission files should contain 2 columns: ID and target.

Your submission file should look like this:

ID        target
WGZRIT9     0
UOFLGFN     0
8F9K7D9     1
Prizes

In order to win, you must:

  • be a part of the UmojaHack Nigeria event on 28 November 2020
  • be currently enrolled as a student at a Nigerian university
  • have your affiliated university listed on your Zindi profile

1st prize: NGN 250 000 shared between members of the winning team

2nd prize:  NGN 200 000 shared between members of the winning team

3rd prize: NGN 150 000 shared between members of the winning team

4th prize: NGN 100 000 shared between members of the winning team

5th prize: NGN 50 000 shared between members of the winning team

Important to note: Only one team from each university will be allowed to win a prize. If more than one team from one university places in the top five, only the top team will win a prize and their university will also win only the one prize. The remaining prizes will be awarded to the next top team/university.

Timeline

09:00 – 09:30 Welcome and orientation (live video conference using Zoom)

09:30 – 10:00 Technical orientation to the platform and the challenges (live video conference using Zoom)

10:00 Competition opens (note that users can sign up for a competition and join teams before the time)

10:00 – 19:00 Students form teams and work on the challenge, questions and issues during this time can be addressed by local Zindi reps or via WhatsApp group

19:00 Submissions close

19:15 Private leaderboard reveal and announcement of local winners and prizes (live video conference using Zoom)