At a recent #FinTechMelb meetup event, Aris Allegos, co-founder and CEO of Moula, talked about how the on-line SME lender had raised $30m in investor funding from Liberty Financial within 9 months of launch, as evidence that their concept worked. In addition, Moula has access to warehouse financing facilities to underwrite unsecured loans of up to $100k, and has strategic partnerships with Xero (cloud accounting software) and Tyro (payments platform).

Moula is yet one more example of how #FinTech startups are using a combination of “big data” (and proprietary algorithms) to disrupt and disintermediate traditional bank lending, both personal and business. Initially, Moula is drawing on e-commerce and social media data (sales volumes, account transactions, customer feedback, etc.). Combined with the borrower’s cashflow and accounting data, plus its own “secret sauce” credit analysis, Moula is able to process on-line loan applications within minutes, rather than the usual days or weeks that banks can take to approve SME loans – and the latter often require some form of security, such as property or other assets.

So far, in the peer-to-peer (P2P) market there are about half-a-dozen providers, across personal and business loans, offering secured and unsecured products, to either retail or sophisticated investors, via direct matching or pooled lending solutions. Along with Moula, the likes of SocietyOne, RateSetter, DirectMoney, Spotcap, ThinCats and the forthcoming MoneyPlace are all vying for a share of the roughly $90bn personal loan and $400bn commercial loan market, the bulk of which is serviced by Australia’s traditional banks. (Although no doubt the latter are waking up to this threat, with Westpac, for example, investing in SocietyOne.)

We should be careful to distinguish between the P2P market and the raft of so-called “payday” lenders, who lend direct to consumers, often at much higher interest rates than either bank loans or standard credit cards, and who have recently leveraged web and mobile technology to bring new brands and products to market. Amid broad allegations of predatory lending practices, exorbitant interest rates and specific cases of unconscionable conduct, payday lenders are facing something of a backlash as some banks decide to withdraw their funding support from such providers.

However, opportunities to disintermediate banks from their traditional areas of business is not confined to personal and business loans: point-to-point payment services, stored-value apps, point of sale platforms and foreign currency tools are just some of the disruptive and data-driven startup solutions to emerge. That’s not to say that the banks themselves are not joining in, either through strategic partnerships, direct investments or in-house innovation – as well as launching on-line brands, expanded mobile banking apps and new product distribution models.

But what about the data? In Australia, a recent report from Roy Morgan Research reveals that we are increasingly using solely our mobile devices to access banking services (albeit at a low overall engagement level). But expect this usage to really take off when ApplePay comes to the market. Various public bodies are also embracing the hackathon spirit to open up (limited) access to their data to see what new and innovative client solutions developers and designers can come up with. Added to this is the positive consumer credit reporting regime which means more data sources can be used for personal credit scoring, and to provide even more detailed profiles about customers.

As one seasoned banker told me recently as he outlined his vision for a new startup bank, one of the “five C’s of credit” is Character (the others being Capacity – ability to pay based on cashflow and interest coverage; Capital – how much the borrower is willing to contribute/risk; Collateral – what assets can be secured against the loan; and Conditions – the purpose of the loan, the market environment, and loan terms). “Character” is not simply “my word is my bond”, but takes into account reputation, integrity and relationships – and increasingly this data is easily discoverable via social media monitoring and search tools. It stills needs to be validated, but using cross-referencing and triangulation techniques, it’s not that difficult to build up a risk profile that is not wholly reliant on bank account data or payment records.

Imagine a scenario where your academic records, club memberships, professional qualifications, social media profiles and LinkedIn account could say more about you and your potential creditworthiness than how much money you have in your bank account, or how much you spend on your credit card.

Declaration of interest: The author currently consults to Roy Morgan Research. These comments are made in a personal capacity.

Next week: Rapid-fire pitching competitions hot up…..