Yup very true! Traditional banks are far more risk averse and generally have larger budgets for compliance. Whereas fintechs/neobanks have smaller budgets for these things as most of their capital is poured into growth.
In the case of Revolut, I'm sure they will build something similar in-house, if they haven't already since I left!
That's shocking! I guess regulators haven't loosened up in Sweden. Curious how a business plan is relevant for opening a bank? (loans make sense ie feasibility/risk to repay etc.).
Each review doesn't count as a single business entity, there are several checks within a business case which each require manual review. Plus often there is a lot of back and forth with customers, which is a multiplier.
UK is a poor example as yes indeed companies house is a central registry. In the UK the manual review is generally proving operating address and operations in general.
A good example for incorporation is Delaware in the US which has no information on the status of a company, so it could in-fact be inactive/dissolved. In this situation an additional proof of operations or good standing certificate is needed to verify the entity is active. In other jurisdictions the registry data is not even present so a certificate is needed. In most US states registries take a while to update so a brand new business would need a certificate.
AI is needed to evaluate proof documents, websites, web presence, social profiles. The list goes on.
I wish it were as easy as just using data + rules! If it were, you wouldn't have fintechs with teams of 10s or even 100s of compliance analysts doing this stuff!
Fintechs often still have humans review docs, websites, perform web due diligence etc. Efficacy has vastly improved at these validation steps with the assistance of LLMs.
Interesting to hear that your previous bank has automated all of low/medium risk already, from what we have seen more traditional banks are far behind fintechs and are more risk averse in using new technologies. Nice to see that's not the case with all traditional banks.
> Efficacy has vastly improved at these validation steps with the assistance of LLMs.
Is that "efficacy" as the (customer-hostile) bank defines it, or is this more holistic interpretation that also factors in false-positives?
i.e. can you assert that things are better now for everyone, including the completely innocent people who often get caught-up in Kafkaesque KYC ("KKYC?") loops?
Yup exactly that! One of the benefits of what we're building is that fintechs/banks can now approve good customers quicker. So the innocent ones benefit greatly from Arva.
What about people who get disapproved because they were flagged by some automated screening? ...they end-up getting stuck in limbo because they were flagged, so they can't even (for example) close-out and withdraw any other accounts they have with the same institution - and they can't get any help because of the "we-can't-tell-you-how-to-evade-KYC" rules.
Decision making is also more accurate, human analysts often deviate from procedure. Also why banks/fintechs often spend so much on QA teams just to observe how the human analysts have performed.
Transaction monitoring is different, that's post account opening.
When people are going through an onboarding flow it is their first account!
Yes rightly pointed out, the regulators are the ones that crack down/fine/impose restrictions.
I'd say there are varying levels of automation, where even to this day within low/medium risk, ~30% of cases get to manual review, and with some that number can be even higher!
Yes sanctions is one area where the human touch is very important! Definitely a high risk category
It is certainly a tough balance for banks/fintechs -- fear of accountability vs. a clear value add. From our interactions, using AI to automate low/medium risk is welcomed. The solution can perform in a robust way and often is more accurate and better than a human (note we're improving it all the time!).
For those that are more risk averse there is another option: the Agent can just surfaces all the relevant information and then a human has to sign-off on the last onboarding action, hence making their jobs 10 times easier.
It'll be interesting to see how AI adoption unravels in the space but it's certainly showing good signs!
