InRiskable enables banks to evaluate SME credit risks with 80% less time and 97% accuracy.
In today’s dynamic financial landscape, banks face a significant challenge in accurately assessing credit risks linked with small and medium-sized enterprises (SMEs).
Addressing this challenge amidst ongoing financial expansion and increasing intricacies, Hong Kong-based startup inRiskable emerges with its AI-driven solutions.
Combining “invisible” and “risk,” inRiskable was founded in 2022 by Megan Chau with a mission to assist financial institutions in uncovering the concealed risks associated with SMEs scattered across the internet.
“Banks are consistently managing a large volume of SMEs, often in the thousands,” Chau explained to Asian Business Review.
“Our approach involves leveraging AI to automatically categorize SMEs based on risk levels, allowing analysts to streamline their evaluations.”
Through AI integration, the risk intelligence platform significantly reduces the time and resources required for due diligence on SMEs. “In our experience, we’ve seen an 80% reduction in time with a 97% accuracy rate,” she noted.
Given the increasing demand for efficient and accurate banking services, traditional credit risk assessment methods are becoming obsolete in today’s rapidly changing financial landscape.
The Challenge
Financial institutions face a significant challenge in fulfilling their obligation to thoroughly understand their customers and ensure security measures are in place.
In many cases, banks encounter a scarcity of reliable data and sources, particularly when assessing business information. For SMEs, shared information often boils down to financial reports, which may not provide a comprehensive picture of the company’s credit risks.
“The traditional approach relies heavily on SMEs’ financial data from their financial reports,” Chau explained. “However, these reports may not always be reliable or offer timely insights into credit risks.”
“In their quest for information, banks often turn to search engines like Google or Baidu,” she added. “But this process lacks structure, standardization, and reliability, consuming significant time and effort.”
InRiskable addresses this information gap by offering financial institutions a more efficient and accurate means of data gathering.
“We provide a SaaS platform to help financial institutions evaluate SMEs’ credit risks,” Chau stated. Their AI-powered solution is designed to uncover the hidden risks associated with SMEs, which often remain undetected until they escalate into significant financial crises.
Apart from data scarcity, banks also struggle with the absence of accessible platforms that can furnish the information they require. “There are few platforms offering this kind of data, as Moody’s or Bloomberg primarily focus on larger corporations,” Chau noted.
In bridging this gap, Chau envisions InRiskable as the next Moody’s for SME credit assessment. “SMEs seek financial services from banks, and banks need comprehensive insights into SMEs to conduct business safely,” she explained. “When they consider SME credit risk, we want them to think of InRiskable.”
Identifying Hidden Risks
Chau highlighted the scarcity of data available about SMEs, particularly concerning factors like litigation court cases or negative publicity.
Through AI technology, InRiskable streamlines the due diligence process for SMEs, significantly reducing the time and effort required.
Acting as a vital support system for banks, InRiskable aids in credit risk assessment. “If a bank needs to conduct business with an SME applying for a loan, we facilitate the approval process,” Chau explained.
The platform meticulously evaluates 23 risk categories to assign credit scores to SMEs. Those failing the risk assessment are flagged as “high risk,” accompanied by supporting information.
Chau likened InRiskable’s data gathering process to ChatGPT, leveraging freely accessible data while refraining from accessing paywalled content unless licensed by the client. “We provide access to around 800 new sources, offering a comprehensive data pool,” she added.
InRiskable offers two distinct services for enterprises: one focuses on fraud identification and prevention, while the other specializes in AML screening.
The AML screening service operates on an automated system without AI involvement and is available for subscription with monthly updates, tailored to the client’s preferences.
“We offer subscription plans with tiered pricing based on usage. The more searches conducted, the higher the tier and associated costs,” Chau clarified.
Expansion Strategies
In the coming year, Chau revealed plans to initiate a seed funding round, commencing in the third quarter of 2024.
“We’re set to join a pre-seed accelerator program in Singapore in March 2024, alongside our membership in the Science Park Incubation in Hong Kong,” Chau disclosed.
When queried about the allocation of future funds, Chau emphasized the primary focus on team expansion.
“We see abundant opportunities in engaging with SMEs across Southeast Asia, and our aim is to extend our operations into markets such as Singapore, Malaysia, and other Southeast Asian regions,” she explained.
Presently, the strategy entails harnessing InRiskable’s resources to construct a Software as a Service (SaaS) model.
Initially tailored for corporate use, Chau envisions democratizing access to the platform.
“It would be fantastic if individuals could easily access our platform to search for information about the companies they’re involved with.
With the upcoming funding, we intend to transition to a SaaS model, enabling broader utilization,” Chau remarked.
