Axis Bank AI Challenge

78 Registered Allowed team size: 1 - 5

This campaign is over.

starts on:
Dec 14, 2018, 11:30 PM
ends on:
Dec 15, 2018, 11:30 PM


Welcome to the offline hackathon for Axis Bank AI Challenge :)

Axis Bank is one of the first new generation private sector banks to have begun operations in 1994.

Today it the third largest bank of the country, providing a wide spectrum of financial services to multiple customer segments – Retail, SME, Agri & Corporate.

Axis has always been forward in technology adoption and using tech in the creation of customer-centric products & services. This Hackathon is an initiative by Axis Bank to promote innovation in the country and help Startups/Developers and Student entrepreneurs to think out of the box and come up with great solutions for the bank. Purpose of this hackathon is to identify the talent and engage with them for co-learning and co-creating tech & business applications in a collaborative and fun way.

Phase III: Finale at Thought Factory Office, Bangalore: December 15th to 16th

You have made it to the finale!

Welcome to Axis Bank’s Innovation Lab, Thought Factory, for this 24-hour exciting hack. You are accompanied by Bank’s tech leaders & data scientists in the final refining of your solution. The final solutions, on submission, will be executed by our mentors and judged for accuracy, scope coverage, usability, experience, and novelty.

Finalists will get an opportunity to present and talk about their solutions before the senior-most management of the Bank.

Hackathon Agenda

  • 11.00 am: Registrations and Participants arrive at the venue.

  • 12.00 - 12.30 pm: Welcome talk and Mentor introduction

  • 12.30 - 1.30 pm: Lunch is served!

  • 1.30 - 8.00 pm: Time to Hack!

  • 4.00 - 6.00 pm: Mentor interaction with participants

  • 6.00 - 10.00 pm: The hack continues

  • 8.00 - 10.00 pm: Dinner

  • 10.00 pm - 11.00 pm: Code collection and submission closure

  • 12.00 - 7.00 am: Presentation continues

  • 9.00 am: Announcement of top-10 teams

  • 9.00 - 10.30 am: Presentation dry-run

  • 7.00 - 10.00 am: Breakfast

  • 11.00 am - 01.00 pm: Announcement of final shortlists

  • 01.00 pm- 01.30 pm: Final judging

  • 01.30 pm - 02.00 pm: Prize distribution.


Signature Recognition

A person’s signature is a representative of his identity. For us at the Bank, a signed document by a customer is an instruction from him for carrying out an approved transaction for him.

On on-boarding a customer we capture an image of his signature in our systems, and on receiving a signed document (Cheques, DDs and others) from him we match the signature on the document with the one recorded in the database before proceeding with the instruction.

In the case of skilled forgeries, it becomes very difficult to verify the identity of the customer.

We want you to build a system that can help us distinguish forgeries from actual signatures. This system should be able to study signature parameters as strokes, curves, dots, dashes, writing fluidity & style, in a Writer-Independent manner and create features for identification of the signature.

The system should not use any existing APIs and should be completely self-developed.

How should it work?

The system shall work in 2 steps:

  • Step 1: Accept & Store Genuine Signature Image: Take actual signature scanned image of the on-boarding customer and store it in a database against a unique Customer ID
  • Step 2: Accept & Compare Signature Images: Accept inputs of Customer ID, and corresponding signature image. Compare with the signature stored in DB against the given Customer ID, and return a Confidence Match Score between the two signature images

Download Sample Datasets

Table Reading & Understanding in Documents/Images

With advent of AI-RPA, document reading and analysis are on their way for becoming mainstream. Tables in documents help represent information in a structured way. For a comprehensive document analysis, it is important to be able to identify, read and understand tables present in documents. This step, although despite a successful OCR, may become difficult, as tables vary a lot in their layout, formats and encoding.

The problem at hand is to build a solution that can detect tables in given documents, then make sense of the information they present.

For this problem too, you cannot use any existing APIs.

How should the system work?

  • Step 1: Accept document input, read tables: System should have an input mechanism for accepting documents (PDFs, MSWord) or document images (TIFF, JPEG). The document may have one or more tables.
  • Step 2: Step 2: As an output, system should return the table content in an excel format,same as that in the sample data sets
    Download Sample Datasets

Prizes INR 5,00,000 in prizes

Apart from the prize money, participants will get:

  • POC opportunities with Bank for start-ups.
  • Internship opportunities for students.
  • 1-month free space for 4 member team at Axis Social
Main Prizes
First Prize
INR 2,50,000
Second Prize
INR 1,50,000
Third Prize
INR 1,00,000
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