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Launch HN: Arva AI (YC S24) – AI agents for instant global KYB onboarding
Hi HN! We’re Rhim and Oli, and we’re building Arva AI (https://arva-ai.com https://arva-ai.com). Arva uses an AI agent to automate the manual verification that every banking/fintech does when they get a new business customer. This is called “Know Your Business” compliance (KYB for short) and it’s a royal pain.
There’s a demo video here: https://www.arva-ai.com/loom https://www.arva-ai.com/loom , and if you’re curious to try it out for yourself, you can onboard onto ‘Arva Bank’ and see what happens when you upload some fake documents: https://platform.arva-ai.com/demo https://platform.arva-ai.com/demo (but please don’t upload any sensitive documents!)
What’s this about? When a business onboards onto a bank or fintech (i.e. applies to be a customer), a human analyst has to conduct extensive manual verification a lot of the time. This causes long onboarding times, and there are huge costs in maintaining compliance teams and in fixing mistakes—because human analysts often deviate from procedure.
I (Rhim) formerly led the FinCrime product team at Revolut Business. There were hundreds (!) of KYB analysts conducting tens of thousands of manual reviews per day! Turns out this is the same across pretty much all fintechs in all jurisdictions around the world, and it’s a problem that can now largely be solved by a combination of AI, data and business logic.
Most of the manual verification work falls into three categories: document verification (e.g. articles of incorporation); figuring out the business activities (e.g. does the business do things that are allowed); and communication with the customer (to make sure they provide the correct pieces of information).
Handling all of this for a customer is time consuming. It leads to huge compliance overheads from having a manual team, which can also often make scaling very difficult. Days of back-and-forth over email with customers creates a terrible experience, leading to drop off and hence revenue loss. In fact, in the US, slow customer onboarding costs fintechs $10B annually in lost revenue (https://resources.fenergo.com/newsroom/poor-customer-experience-costs-financial-institutions-10-billion-per-year https://resources.fenergo.com/newsroom/poor-customer-experie...)!
The interesting thing is that this domain is so highly structured and formalized that it turns out to be a good match for the current generation of AI tools.
Enter Arva AI. We've built a highly compliant AI agent that instantly handles all low/medium risk manual KYB work in real-time as a customer is onboarding, cutting reviews to seconds and ops spend by 80%. Arva AI’s agent can operate globally and can either be used as standalone KYB agent, or layered into already implemented compliance stacks. We focus on reviewing documentation, websites and social profiles in realtime and then communicating with the customer so that they can rectify bad information whilst they’re in the onboarding flow.
Check out (https://www.arva-ai.com/loom https://www.arva-ai.com/loom) for an overview and try it out yourself if you want, at https://platform.arva-ai.com/demo https://platform.arva-ai.com/demo.
We’d love your feedback, especially if you’re connected to the fintech space, and we look forward to everyone’s comments!
- jannes 2y agoWould this hold up in court as actually "knowing" your customer if you let an AI handle it?
- OliverWales 2y agoOur agent implements every step of the procedure that a human compliance analyst would follow, step by step. As a result, every individual check that makes up the overall decision is documented with the reasoning and evidence the agent used. You can also choose to bucket your customers by risk level and require manual review for higher risk customers (e.g. certain business activities like crypto or gambling, complex ownership structures or foreign UBOs). Ultimately the level of automation vs review is up to the risk appetite of the customer, as they are the one that has to answer to the regulator.
- Lionga 2y agoSo a long way of saying "Nope" to the actual question?
- rhimshah 2y agoIt would hold up with the regulator as each decision and outcome is stored and has explainability, so it is in fact even more auditable than a human!
- whiplash451 2y agoSaid differently: they are a data processor, not a data controller, and as such leave the legal burden on their customers, while promising some level of automation / cost reduction. It sorts of makes sense, the main challenge being profitability for Arva.
- threeseed 2y agoCourts aren't the issue. It's regulators. And at least at banks >99.9% of KYC/AML interactions have been automated for many decades now. The rest are things you wouldn't want an LLM anywhere near e.g. sanctions evasion for which require significant expertise and lots of care.