FirstHomeCoach is a UK-based fintech company whose product navigates buyers through the complex steps of purchasing a property and connects them with trusted advisors to help them secure a mortgage, get insurance, and handle all the legal paperwork.
FirstHomeCoach is a UK-based fintech company whose product navigates buyers through the complex steps of purchasing a property and connects them with trusted advisors to help them secure a mortgage, get insurance, and handle all the legal paperwork.
Our client’s service needed a custom algorithm and the recommendation engine that analyzes loads of data to automatically plan the individual property buying process.
Sensitive user data gathered by the system had to be secured with the help of a security-driven architecture and data segregation. In addition, our client wanted to make modules including the mortgage calculator and deposit builder accessible for partners as separate products in white label format.
When the client actively participates as CTO and manages all technical aspects on their's side, our project management team come in handy in people management. In this case, nearshore project managers work as people partners, helping to reduce turnover, coach engineers, and speak with them on the same level and with the same cultural values.
While working on FirstHomeCoach, we were conducting various team-building events and workshops, both technically and socially-oriented, such as needs assessment workshops, performance reviews and 1-1 meetings.
Our project manager helped speed up the recruitment process, including covering part-time positions and accelerate the onboarding of new members, including business model knowledge sharing.
Our team selected the technology stack, designed the app’s security and architecture, and built the system and algorithms from scratch. Moreover, we paid the utmost attention to how the system stores users’ personal data, ensuring tight security.
Guides users to buying a desired property in a certain timeframe and informs how much to save each month.
Provides projections on the maximum loan size, mortgage interest rate, and monthly payments based on a user’s income, location, and savings.
Recommends savings accounts a user can benefit to save as much as possible for a deposit to get a property sooner.
App integrates with banks, real estate companies, credit reporting agencies, and open banking solutions.
Enables the necessary isolation between the application server and business processes.
TypeScript improves readability, speeds up development, and makes the system more stable.
A Node.js-based cluster module allows the app to use the full power of CPU.
Functional, integration, confirmation, and regression testing were performed in order to gain a cloud perimeter and IT infrastructure security assessment.
Grey-box penetration testing was used to detect possible security defects missed during manual examination and automated source code scanning.
Prevents data leaks and backdoors by automatically detecting and locating security flaws in the source code.
In the end, we provided our client with a solution that helps potential homebuyers create a personalized plan, analyze costs, and track every stage of the property buying process.
In its first year, FirstHomeCoach helped more than 5,000 users plan property purchases by processing over 40,000 data points. Apart from that, 1,000+ people enjoyed the mobile application.
PROPERTY PURCHASES PLANNED
ACTIVE USERS
DATA POINTS
We needed a flexible, reliable partner that could turn our idea into reality, one who could quickly provide a team of experts that could design and build our product and infrastructure. Meeting with some of the Relevant team in London, we were impressed by their approach. The Relevant team’s quality and approach left a favorable impression on us, so we proceeded with them.
Relevant was critical to designing and building the app and its infrastructure. The site went live last year, and we continue to work with Relevant to enhance the product. They made experienced team members available to show us what our solution would look like and how our cooperation would flow. This showcased their reliability and established transparent processes and regular communication.
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