Release date:2022-09-23
HaveFund empowers loan syndication with blockchain and AI
HaveFund empowers loan syndication with blockchain and AI
Date：2020-06-19 14:18
Generally, professional money lenders who engage in loan syndication have to deal with a series of recurring pain points during every step of the loan syndication process. These include calculating credit scores manually, mitigating third-party risks, coping with limited fund negotiation abilities, and meeting rapidly evolving compliance demands.
COVID-19 and the global economic uncertainty are shifting loan market landscape, where lenders are increasingly looking to mitigate financial risks. Cyberport Smart-Space company MY Innovate, which runs a B2B loan trading platform called HaveFund, accelerates the development of its loan syndication product to help money lenders improve loan profitability and loan trading efficiency.
HaveFund’s smart platform lets money lenders trade loans in a vast member-only marketplace, buttressed by cutting-edge technologies like blockchain, secure enclaves, AI, and machine learning.
What makes HaveFund stand out from the crowd is using the latest technologies to ensure a “Secure, Honest, Immediate, Fair, and Trusted” (S.H.I.F.T) auction process. The synergy combined from these technologies provide the three pillars of HaveFund: “Trusted Trade, a Secure Datastore and a Secure Execution Environment.”
The platform encrypts all data end-to-end and prevents fraud with an early detection system. It fosters honesty and integrity among the participants as it conceals the private data of potential buyers. By performing credit scoring automatically, business opportunities are presented in a timely manner and results are produced immediately to save time. All auctions are recorded on a distributed consortium ledger to ensure the fair and auditable transactions. Most importantly, HaveFund’s state-of-the-art technology instils trust throughout its processes.
Headquartered in Singapore with subsidiaries in Hong Kong and Japan, HaveFund is attracting more money lenders to join its platform, including a major non-bank mortgage market player in Hong Kong since its launch in March this year. HaveFund was awarded the Outstanding Business Idea Award at the FISCO-BCOS Blockchain Contest in 2018.
COVID-19 and the global economic uncertainty are shifting loan market landscape, where lenders are increasingly looking to mitigate financial risks. Cyberport Smart-Space company MY Innovate, which runs a B2B loan trading platform called HaveFund, accelerates the development of its loan syndication product to help money lenders improve loan profitability and loan trading efficiency.
HaveFund’s smart platform lets money lenders trade loans in a vast member-only marketplace, buttressed by cutting-edge technologies like blockchain, secure enclaves, AI, and machine learning.
What makes HaveFund stand out from the crowd is using the latest technologies to ensure a “Secure, Honest, Immediate, Fair, and Trusted” (S.H.I.F.T) auction process. The synergy combined from these technologies provide the three pillars of HaveFund: “Trusted Trade, a Secure Datastore and a Secure Execution Environment.”
The platform encrypts all data end-to-end and prevents fraud with an early detection system. It fosters honesty and integrity among the participants as it conceals the private data of potential buyers. By performing credit scoring automatically, business opportunities are presented in a timely manner and results are produced immediately to save time. All auctions are recorded on a distributed consortium ledger to ensure the fair and auditable transactions. Most importantly, HaveFund’s state-of-the-art technology instils trust throughout its processes.
Headquartered in Singapore with subsidiaries in Hong Kong and Japan, HaveFund is attracting more money lenders to join its platform, including a major non-bank mortgage market player in Hong Kong since its launch in March this year. HaveFund was awarded the Outstanding Business Idea Award at the FISCO-BCOS Blockchain Contest in 2018.
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