BrokerSense Marketplace – Better connecting underserved mortgage borrowers with the specialist lenders who can serve them.
Lead Participant:
LAZY DOG SOFTWARE LTD
Abstract
There is a clear existence of a bias in the mortgage market that is affecting people whose mortgage application is considered non-standard, be it either related to their income situation (self-employed, bad credit history, etc.) or to the property for which they are requesting a mortgage loan (Large Concrete Panel construction, knotweed on property grounds, etc.).
Indeed, while a number of specialist lenders exist to serve this market, their offer often does not meet demand due to the existence of multiple lending criteria that render such applications very complex.
In the context of COVID-19, this issue will affect a growing proportion of applicants, as the labour markets are facing a strain with 7.5 million employees on furlough and a clear increase in zero-hour contracts, all the while lenders are becoming more risk-averse and the house mortgage market is seeing a contraction.
Mortgage brokers are critical intermediaries in the industry. They support clients going through the process of finding a mortgage offer that suits their situation. However, mortgage brokers charge a proportion of the loan at completion, which reduces their incentive to support less time-worthy complex cases. Specialist brokers would accept difficult cases but typically charge fees that are 5 times higher.
In this project, Lazy Dog Softwares will build a first-of-class service able to suggest the most relevant lender for a given client, significantly reducing the time spent by brokers searching for a matching loan offer. Lazy Dog Softwares is thus planning to transform its existing solution, BrokerSense, to do so. BrokerSense is a SaaS platform allowing UK-based brokers to search mortgage lenders based on their affordability. In this project, BrokerSense will be transformed into a two-sided marketplace linking brokers and lenders on one tool through data on their clients. Using this data, we will develop a solution able to significantly reduce time spent by brokers searching for mortgage offers specially in complex cases.
The results of our project will improve the capacity of the market to serve the needs of clients in complex situations while reducing the financial burden on them. It will therefore have a strong impact on the inclusivity and equity of the mortgage market that is critical for UK taxpayers in a context of economic contraction.
Indeed, while a number of specialist lenders exist to serve this market, their offer often does not meet demand due to the existence of multiple lending criteria that render such applications very complex.
In the context of COVID-19, this issue will affect a growing proportion of applicants, as the labour markets are facing a strain with 7.5 million employees on furlough and a clear increase in zero-hour contracts, all the while lenders are becoming more risk-averse and the house mortgage market is seeing a contraction.
Mortgage brokers are critical intermediaries in the industry. They support clients going through the process of finding a mortgage offer that suits their situation. However, mortgage brokers charge a proportion of the loan at completion, which reduces their incentive to support less time-worthy complex cases. Specialist brokers would accept difficult cases but typically charge fees that are 5 times higher.
In this project, Lazy Dog Softwares will build a first-of-class service able to suggest the most relevant lender for a given client, significantly reducing the time spent by brokers searching for a matching loan offer. Lazy Dog Softwares is thus planning to transform its existing solution, BrokerSense, to do so. BrokerSense is a SaaS platform allowing UK-based brokers to search mortgage lenders based on their affordability. In this project, BrokerSense will be transformed into a two-sided marketplace linking brokers and lenders on one tool through data on their clients. Using this data, we will develop a solution able to significantly reduce time spent by brokers searching for mortgage offers specially in complex cases.
The results of our project will improve the capacity of the market to serve the needs of clients in complex situations while reducing the financial burden on them. It will therefore have a strong impact on the inclusivity and equity of the mortgage market that is critical for UK taxpayers in a context of economic contraction.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
| LAZY DOG SOFTWARE LTD | £50,702 | £ 50,702 |
People |
ORCID iD |
| Stuart Phillips (Project Manager) |