Projects / Top Talent Project

Building a Recommendation System to Improve Mortgage Lending Process

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This is a paid opportunity. In order to be eligible to apply for this project, you need to be part of the Omdena community and have finished at least one AI Innovation Challenge.

You can find our upcoming AI Innovation Challenges at https://omdena.com/projects.

The problem

In the mortgage sector, there exists a disconnect between banks and lenders and the people who use their services. Mortgage applications are evaluated by financial institutions such as banks and lenders based on several criteria; nevertheless, the most important consideration is whether or not the individual will be a reliable client for the organization. To put it another way, they want to make sure that the consumer is trustworthy with the money and that they will keep making payments during the duration of the loan. As a result, financial institutions want to ensure that every applicant is well-competent. It is difficult for the customer to know the results of such an evaluation so that they may work to enhance their profile and increase the likelihood that their applications will be accepted.

The described problem is addressed in this Omdena-My Home Pathway project. This project aims to build a proprietary algorithm and recommendation engine that can assess the customer’s current qualification status and deliver ongoing recommendations and guidance to improve the customer’s grade and put them on the path to loan approval and homeownership.

The project goals

This project will be focused on building a recommendation/rules-based engine to provide suggestions to the users on where they need to make improvements to buy their target home.

Some recommendations may be user-action-oriented, where the users have to take specific actions to improve their ‘risk profile’, and others may be items the user has to pay attention to as no specific action is required.

Project Scope:

1. Implementing a Rule-based engine and recommendation engine

2. Key Target Segments for Underwriting Target include the following: Top 3 Categories will be the primary areas of the recommendation engine with a focus on

  • Credit Score
  • Debt to Income Ratio (DTI)
  • Downpayment and Closing Cost (Cash to Close)
  • Income

**More details will be shared once the project is joined.

Why join? The uniqueness of Omdena Top Talent Projects

Top Talent opportunities come as a natural next step after participating in Omdena’s AI Innovation Challenges.

Everyone in the community is eligible to participate once they have shown the relevant skills based on the merit of involvement in past Omdena challenges and the community.

If you are looking for the next challenge after participating in one or more Omdena AI Innovation Challenges, then we believe you have made the right choice! With a healthy, pressured environment, you will be pushed to contribute, learn and grow even more.

Find more information on how an Omdena Top Talent Program works

First Omdena Project?

Join the Omdena community to make a real-world impact and develop your career

Build a global network and get mentoring support

Earn money through paid gigs and access many more opportunities



Eligibility to join an Omdena Top Talent project

Finished at least one AI Innovation Challenge

Received a recommendation from the Omdena Core Team Member/ Project Owner (PO) is a plus



Skill requirements

Good English

Machine Learning Engineer

Experience working with Smartphone Sensor Data is a plus.



This project is hosted with our friends at


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