Prague based Resistant AI has nabbed a $2.75 M seed round. The insurance startup’s machine learning technology is designed to be deployed on top of AI structures used for monetary decision making to protect purchasers in markets such as financial services and ecommerce from attempts such as targeted manipulation, adversarial machine learning and advanced fraud.
The seed round was co-led by Index Ventures( Jan Hammer) and Credo Ventures( Ondrej Bartos and Vladislav Jez ). Seedcamp also participating, along with Daniel Dines, CEO of UiPath; Michal Pechoucek, CTO of Avast and other unnamed angel investors. Bartos attaches the board of directors on behalf of the investors.
The startup sells an additional layer of protection that’s dealing specifically for stiffening certificate around automated performs such as credit risk tallying and anti-money laundering by employing tech to spy forge the documentation that feed such systems. Its tech is also aimed at uncovering questionable blueprints of deals which are likely to reveal a tactical attack on the modeling itself or an attempt to forgery sensitive data.
” Historically, all systems that determine high-value business decisions become targeted. This is already happening with the automated arrangements deployed by our fintech and monetary the consumers and we are to protect them ,” said Martin Rehak, founder and CEO, in a statement.
The seed round is Resistant AI’s first tranche of external fund, with the founders bootstrapping the company since starting up in February 2019.
” We have onboarded the first purchasers in 2019 and the funding will help us scale our auctions organisation to meet the rising demand from banks and fintechs ,” Rehak told us.” We are protecting the AI& ML plans used in monetary automation from manipulation or misappropriation by smart-alecky attacks .”
Resistant AI has two products it offers its customers at this stage: First, record inspection. It offers a machine learning system that’s designed to signal and reject” malicious documents” to put forward automated treating.” Bank evidences, payslips, statements, purchase orders and KYC documents submitted to fintechs and banks are routinely influenced or totally falsified ,” asked Rehak.” Resistant Documents, our first service, relates and scorns the suspicious or malevolent inputs .”
A second offering — Resistant Transactions — exerts AI to recognise problematic event patterns.
” We work with the fact that most assaults on AI arrangements ask lengthy interaction to discover the vulnerability ,” he said.” Our system is distinct by inspecting all the customer inquiries( which can take form or pays, fund carries-over or credit employments assessed by the system we protect) in framework of same queries. By looking at the stream of inquiries statistically, we can recognise and block the attacks that seek to steal the information embodied in the prototype( intelligence stealing) or, worse, aim to nudge the system into constituting the wrong decision by exploiting the existence of the bias in the system .”
Resistant AI isn’t broke out purchaser lists more but Rehak said it onboarded its first customers last year.” The funding will help us scale our auctions organisation to meet the rising demand from banks and fintechs ,” he computed, saying too that it will be spending on building out produce features and extending functionality, as well as on beefing up the sales and go-to-market team.
” Right now, our target purchasers are business and fintech startups, as well as other business deploying the automated process( both software and RPA) in their financial process ,” he lent.” The financial systems are our current focus, but the two attacks on machine learning are relevant in many other areas: process automation, e-commerce, manipulation of’ trend identification’ algorithms in social media and other opportunities .”
It’s using a SaaS model — preferring a quality approaching to pricing, per Rehak.” Our problem and approaching is new, and we be considered that the evaluate pricing pose aligns the incentives between us and the customer in the optimal direction ,” he said on that.
Asked who he sees as the main competitors for the business, he quoth Google Brain plus the tech giant’s activities in adversarial machine learning.
The majority of work in this area is currently done in-house by the large tech fellowships building their own proprietary arrangements — such as Google and Microsoft, he added.
Other adversaries he mentioned were Inpher, which is enabling machine learning on encrypted data; Sentilink, which is doing detection of synthetic identities in the US; and Bullwall( Denmark) and YC-backed Inscribe( US/ Ireland) which are focused on document forgery.
Resistant AI’s founders have a background in machine learning applied to cyber security problems having founded Cognitive Security, an earlier startup which they subsequently sold to Cisco in 2013. Over some 12 times working in the security industry Rehak said they saw how attacks targeting AI plans were getting increasingly sophisticated in avoiding detection — which granted them the relevant recommendations for their latest business.
Commenting on the seed fund in the following statement, Jan Hammer, general collaborator at Index Ventures, added:” Automation, efficiency and reliability are cornerstones of financial innovation. As machine learning takes more and more nuanced monetary decisions, it needs to be protected. And this is not true simply in busines, but the attacks will rapidly spread to other orbits as well. More of our act today takes place online, current trends intensified by COVID-1 9, and one we repute will last. With felons ready to take advantage of every vulnerability, the need for solutions such as those from Resistant AI has never been greater .”
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