In Asia Pacific (APAC), artificial intelligence (AI) and machine learning (ML) are increasingly being deployed in credit and risk functions for improved credit assessment, credit scoring and fraud detection. Moving forward, AI will no longer be an option for banks and financial institutions but rather a necessity, enabling them to meet rising customer expectations, tap new business opportunities, and address the rapidly evolving fraud landscape, data specialists and top finance executives said in a recent webinar. During Fintech Fireside Asia's latest panel discussion, C-level executives representing Union Bank of the Philippines, credit bureau TransUnion, lending startup Funding Societies and data solutions provider Mobilewalla discussed the state of AI adoption across APAC's financial ecosystem, delving into how predictive modeling and ML are now being used in the lending process. For Anindya Datta, Founder, CEO, Chairman, Mobilewalla, AI offers an opportunity to deliver innovative business models that can leapfrog traditional solutions and reach the unbanked, a potential that's particularly relevant in Southeast Asia considering that more than 70% of the region's adult population remain either unbanked or underbanked today. "A major part of decision making in lending is around figuring out how likely a person is going to pay back and whether they will pay back in time. Why it's so interesting In emerging markets, especially in APAC, is because the credit footprint is small [and a lot of people don't] have credit scores," Anindya said.

Predictive models are rarely static -- operationalized models typically have an update cadence. At Mobilewalla, for instance, our models are updated every 30–180 days. At the end of each update period, the model is revised based on assessing the fidelity of its output since the last update. This is an important component of standard model maintenance practice, and is known as the feedback loop. A degenerate feedback loop (DFL) occurs when this prior output unfairly impacts future outcomes.

If you marched in recent Black Lives Matter protests in Atlanta, Los Angeles, Minneapolis or New York, there's a chance the mobile analytics company Mobilewalla gleaned demographic data from your cellphone use. Last week, Mobilewalla released a report detailing the race, age and gender breakdowns of individuals who participated in protests in those cities during the weekend of May 29th. What is especially disturbing is that protestors likely had no idea that the tech company was using location data harvested from their devices. As BuzzFeed News explains, Mobilewalla buys data from sources like advertisers, data brokers and ISPs. It uses AI to predict a person's demographics (race, age, gender, zip code, etc.) based on location data, device IDs and browser histories.