AI B2B payments automation firm Tipalti raises $150mn
San Mateo, California-based Tipalti provides a solution for automating manual supplier payment processes.
Since its foundation in 2010, the company has raised across seven funding rounds. Its latest raised $150mn from lead investor Durable Capital Partners, alongside Greenoaks Capital and 01 Advisors. The funding resulted in the company’s ascent to the status of tech unicorn (a startup valued at over $1bn).
In , Chen Amit, CEO and Co-founder of Tipalti, said: “This new round of investment will allow us to further accelerate our innovation edge as a leader in the payables automation space and expands our solution to the larger market. Tipalti is clearly needed and this enables us to be ready for all that demand.”
Tipalti says it encompasses the many steps in the payables process such as supplier management, tax compliance, fraud controls and invoice processing, using a machine learning implementation known as Tipalti Pi to reduce errors (such as duplicate bills and invoice entries) and streamline processes, while ensuring that a human is ultimately in control of all financial actions.
The platform also features an open API architecture allowing connections with other systems such as Oracle, Xero and Microsoft Dynamics GP. Its customers include the likes of Amazon Twitch, Medium, Twitter and GoDaddy.
The company said it would use the funds to accelerate growth, expand its global presence and continue to develop its products.
“The accounts payable automation space has an extremely large total addressable market with significant growth potential,” explained Henry Ellenbogen, Founder, Managing Partner and Chief Investment Officer of Durable Capital Partners LP. “We believe that Tipalti has the potential to become a much larger company within the Midmarket space due to its differentiated holistic platform, superior global capabilities and management team. This has resulted in leading retention and customer satisfaction.”
ICO warns of privacy concerns on the use of LFR technology
“I am deeply concerned about the potential for live facial recognition (LFR) technology to be used inappropriately, excessively, or even recklessly. When sensitive personal data is collected on a mass scale without people’s knowledge, choice or control, the impacts could be significant,” said Elizabeth Denham, the UK’s Information Commissioner.
Denham explained that with any new technology, building public trust and confidence in the way people’s information is used is crucial so the benefits derived from the technology can be fully realised.
“It is not my role to endorse or ban a technology but, while this technology is developing and not widely deployed, we have an opportunity to ensure it does not expand without due regard for data protection,” Denham added.
The Information Commissioner’s Office has said it will work with organisations to ensure that the use of LFR is lawful, and that a fair balance is struck between their own purposes and the interests and rights of the public. They will also engage with Government, regulators and industry, as well as international colleagues to make sure data protection and innovation can continue to work hand in hand.
What is live facial recognition?
Facial recognition is the process by which a person can be identified or recognised from a digital facial image. Cameras are used to capture these images and FRT software measures and analyses facial features to produce a biometric template. This typically enables the user to identify, authenticate or verify, or categorise individuals.
Live facial recognition (LFR) is a type of FRT that allows this process to take place automatically and in real-time. LFR is typically deployed in a similar way to traditional CCTV in that it is directed towards everyone in a particular area rather than specific individuals. It can capture the biometric data of all individuals passing within range of the camera indiscriminately, as opposed to more targeted “one-to-one” data processing. This can involve the collection of biometric data on a mass scale and there is often a lack of awareness, choice or control for the individual in this process.
Why is biometric data particularly sensitive?
Biometrics are physical or behavioural human characteristics that can be used to digitally identify a person to grant access to systems, devices, or data. Biometric data extracted from a facial image can be used to uniquely identify an individual in a range of different contexts. It can also be used to estimate or infer other characteristics, such as their age, sex, gender, or ethnicity.
The security of the biometric authentication data is vitally important, even more than the security of passwords, since passwords can be easily changed if they are exposed. A fingerprint or retinal scan, however, is immutable.
The UK courts have concluded that “like fingerprints and DNA [a facial biometric template] is information of an “intrinsically private” character.” LFR can collect this data without any direct engagement with the individual. Given that LFR relies on the use of sensitive personal data, the public must have confidence that its use is lawful, fair, transparent, and meets the other standards set out in data protection legislation.