The BizBaz team
Last year, the global lending industry incurred approximately US$800 billion in losses due to bad consumer loans. To put it in context, this is more than the GDP of many countries combined.
This incident indicates there are severe chinks in the armour of the traditional credit scoring models adopted by banks and other lenders.
“Traditional credit scoring models are not effective as they look only at the past transactions of the loan seeker, such as whether he defaulted on a loan or credit card payment 15-20 years ago. These models don’t take into account the individuals’ current situation,” says Vincent Choy, co-founder and Chief Business Development Officer of BizBaz. “We have developed a predictive AI solution that could effectively assess the creditworthiness of an individual and save banks from bad loans.”
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Launched in 2020 by Choy and Hayk Hakobyan (CEO), BizBaz offers a SaaS solution to help lenders with credit scoring, especially for the unbanked and underbanked. It uses voice analytics to help establish a person’s creditworthiness based on behavioural patterns and claims it can predict his risk behaviour with 80 per cent accuracy.
Credit scoring depends heavily on transactional data. Unfortunately, about 2.4 billion people in the world don’t have transactional data or credit scores because they’re excluded from all forms of financial transactions. This means traditional models cannot be used to assess the creditworthiness of an unbanked individual.
“Unlike traditional credit scoring solutions, BizBaz can determine an individual’s creditworthiness from his 50-second speech or interview. Our proprietary AI solution can analyse whether an individual is genuine, emotionally and mentally stable, impulsive, conscientious, and worthy of a loan. We can then extract physiological biomarkers and biometric information from that voice to predict his behaviour,” he adds. “It means BizBaz can create creditworthiness for almost everyone, whether unbanked, underbanked or banked. ”
BizBaz works with banks, financial institutions, and buy-now-pay-later companies. The fintech startup has 22 clients in 10 countries, mostly in Asia and Southeast Asia, including Singapore. “With more than seven out of ten of Southeast Asia’s 680 million population unbanked and a huge 67 per cent mobile phone penetration rate, we can empower financial services providers by offering them comprehensive customer intelligence and risk assessment solutions and thus enabling them to acquire and serve unbanked and underbanked populations in the region whilst also allowing them to reduce their costs, Choy says.
Vincent Choy
BizBaz doesn’t restrict itself to the financial services industry. It also works with HR and recruitment companies to help them understand the psychometric analysis of a person being hired. The firm also looks for more use cases in matchmaking, mental wellness and monitoring industries.
In September 2022, BizBaz secured US$4 million in a seed funding round led by HSBC Asset Management, the investment arm of Britain’s HSBC Group. Vynn Capital, SOSV, and existing and new angel investors also participated.
The company is currently looking to raise pre-Series A funding for expansion. This year, BizBaz looks to foray into the Philippines and Indonesian markets. It also sees opportunities in Thailand, Vietnam, and Cambodia. “We will also enter the Latin America and African markets in the near future,” he says.
Also Read: Accelerating financial inclusion with AI: Unleashing potential with prudence
BizBaz was the winner in the fintech category at the Elevator Pitch Competition (EPiC) organised by the Hong Kong Science and Technology Parks Corporation (HKSTP) last month.
The significant losses faced by the global lending industry due to bad consumer loans underscore the critical need for more advanced and accurate credit scoring models. BizBaz, with its innovative AI-driven solution, offers a promising alternative to traditional methods by evaluating creditworthiness through voice analytics and behavioural patterns. This approach not only helps lenders make more informed decisions but also opens financial opportunities for the unbanked and underbanked populations worldwide.
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