A USA fintech and research company approached ASD team to develop a Big Data search engine for one of their mortgage solutions.
The challenge was offering an ultimate user a search possibility to see the rates offered by the most popular lenders in the USA.
The client requested a search engine able to process as many parameters of mortgage loans as available from most lenders.
Big Data search engine widget had to:
- Include all parameters which are mentioned in rates, adjustments and matrices of loans.
- Process a huge amount of data in the shortest possible time providing the most relevant results.
- Currently the search engine performs 5+ mln queries per day.
- The search engine widget transformed to a standalone web-page with white labeling opportunity. This page was launched for LendingTree. The entire infrastructure was moved to AWS.
- Also API was launched for the client’s research services. It’s implemented at Yahoo and MSN as well and performs 1+ mln queries per day.
ASD team developed Big Data search engine based on approximately 100 parameters able to find the most relevant bank providing:
- the best loan rate for a user;
- the highest interest for a broker.
The major version of the solution was released as a web page containing a search form based on the key banks data.
The supplemental element of the solution was a widget (actually, a few variations of widget) providing a real-time information about loan rates from different banks. This widget lead to the web page with the advanced search options providing the information about a bank and payments details. Also, the advanced options gave the opportunity to benchmark a few banks on the chosen parameters.