SPOTLIGHT CANADA
All-you-can-eat data, but who’s using it? The credit sector still largely relies on crowdfunders, digital-only banks and fintech firms for innovation. But what will the ‘new normal’ in lending look like? Neil Ainger asked Armada Labs’ Chairman Ralph Ayala, CEO Nick Varnitski and COO Eugene Pratasenia “The more data one can collect on the consumer or corporate, the better educated a loan decision will be,” says Ralph Ayala, chairman at Armada Labs, which provides white-labelled credit score data and analytical systems to financial institutions (FIs) and the new disruptive financial technology firms that are keen to shake up their marketplace. North America is its home market, but Armada sees the same trends in the supremacy of data and the rise of fintech innovation in Europe, too, as banks struggle to overcome their silos. Established FIs are increasingly looking outside their own bespoke software, data centres and legacy IT, to find new solutions in the Cloud and among more nimble collaborative fintech partners. Ayala cites unstructured ‘big data’ and the investigation of multiple sources – not just an Experian score, as a bank would traditionally use – as the key success factors in maintaining a risk profile that lending
firms are comfortable with, without unnecessarily turning away business because you don’t have the systems to quickly analyse, accept or reject applicants from online or mobile channels. Younger millennial customers, in particular, want a digital service. “Armada Labs understands that every company – whether an established FI, crowdfunder or challenger bank – has its own philosophy and ideas about who to approve and for how much,” says Ayala. “Internally, we call this the ‘secret sauce’ and are confident we can build a flexible system that can accommodate firms’ different risk profiles and niche target audiences. “What is distinctive about the newcomer fintechs is that they use a lot of different data to determine their decisioning factors.” Unstructured ‘big data’ from social media and other sources can be mined for useful information, particularly using artificial intelligence (AI) machine-learning techniques or more standard business intelligence (BI)-type analytical tools. Even just un-siloed information on a new bank’s data-centric systems can be used to approve loans in the atypical fintech-based fashion. “For instance, a Harvard
graduate with an engineering degree but no credit history will often automatically get turned down by a traditional bank,” says Ayala. “A fintech neo-challenger bank wouldn’t do that, nor indeed would a fintech-enabled traditional bank that is overhauling its digital platform. They’d be more savvy and knowledgeable because they’re using more varied, deep data.” According to Nick Varnitski, CEO at Armada Labs and a managing partner alongside Ayala, there is no document collection or presentation headache with the fintech-based approach to loans, risk and decisions, either. This makes the process less stressful for the end consumer. “There is no painful credit check and, because it’s all online, no need to collect a whole bunch of documents to prove ‘hey, here’s my income and how I’m spending it and where I live via my electricity bill, and so on’. All you really have to do is give access to your US or Canadian current account,” says Varnitski. “Then our technology goes in and grabs all the transactions and does its analysis, understands what your cashflow is,
Not had their fill yet: Appetites for lending are determined by the quality of the data
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Spring 2017