Hi FF,The whole extract below is interesting:
Tim Llewellynn
Tim Llewellynn
CEO/Co-Founder of NVISO Human Behaviour…
Published Jun 20, 2017
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We are so proud to announce that our AI-specialist company nViso with our Financial Services lead product “EmotionAdvisor” has been accepted into the excellent FCA Innovation Sandbox in UK! If you missed it here is a quick overview of who got in.
Our application was focused around testing our Artificial Intelligence behavioural and emotion-recognition technology to prove whether we can help enhance financial services customers’ profiles for use in banking and insurance.
Innovation Sandboxes
But first of all, what's an Innovation Sandbox? Just from my personal view, it's the regulator helping catalyze industry with start-ups to innovate faster around core issues. As we are new to this journey I can so far say it's been super helpful even during the application process to get a better feeling for how the regulator works, and what they're looking for.
As a white-label software provider, it's important we know the applicable rules and stand ready to answer financial services companies myriad processes and questions from their legal, compliance and regulatory as well as business and IT functions. As a CEO I run a team who face long lead times and a shadow of healthy scepticism in every meeting - so having started a process directly with a sharp regulatory team gives me much more confidence that we have all our ducks in a row headed into such a challenging environment.
I’ll be giving you more real-time updates here out of the Sandbox as we begin the testing process in late summer.
What Inspired us to Apply?
Until now, customer profiling and risk assessments have relied on static questionnaires and dogmatic questions around financial ability and appetite to withstand loss. Whereas we know from leading academic research that client behavioural reactions to loss and finance more generally are also correlate to other more intimate characteristics such as thinking style. Our technology can “read” and interpret such thinking styles by observing pre-emotional expression reactions in response to a series of stimuli, for example a short video. It's important to note we are not measuring fully processed emotions, but what happens in the 20-40 milliseconds before a person thinks through and expresses a reaction to another human.
"This is a critically important point - computers can read true emotional reactions better than humans can."
My goals out of the pilot are to further explore the use cases across Financial consumers’ life cycle with any given provider. We believe AI-driven emotional recognition has a number of important applications including prospecting for suitable customers, login and authentication, client profiling, creating active recommendations for products/services, and even as a more complete feedback loop to a client advisor and firm.
Emotion and Customers Financial Decisions are Highly Connected
As cited in the FCA’s RDR finalized guidance (2012), client profiling using automated tools must be reviewed carefully by a firm and enhanced where necessary to make a complete picture.
EmotionAdvisor is a set of skills we are developing for banks and insurers, asset and wealth managers to enhance their client profiles with behavioural finance relevant information in order to make sharper product, offering or advisory recommendations.
Our core belief is the better you know your client, the more accurate your recommendations and the more you can prove you aligned to their best interests.
EmotionAdvisor may be just what you're looking for to help plug that important gap between static MiFid profiling and true behavioural finance inputs.
About Us...
We're not your average early stage start-up talking about AI and machine learning. I've been CEO of nViso since 2009, we have 30 employees and are a spin-off and are still based out of EPFL (often called the MIT of Europe) and are an official partner with IBM Watson for machine learning and data analysis techniques development. We are now launching our fourth major client with our mainline Financial Services SaaS called EmotionAdvisor.
I also head up the European Union’s front-end offense as organizer of BONSEYES, the EU open marketplace for AI which has a budget of double-digit millions to build our Europe’s offensive capabilities and use cases across industry verticals such as Finance, Automotive, Consumer Retail and IoT among others. Our team is largely made up of PhDs and business people who know how to build and shape a product set.
Want to Learn More about AI and Finance
● FCA’s RDR Finalised Guidance on Independent and restricted advice
● FCA’s FARM final report
● EmotionAdvisor prospectus on nViso website
● Paul Ekman history
Are you a Head of Strategy, Digital, Innovation or Products & Services at a bank, insurer, asset or wealth manager, or a FinTech with a B2C offering? Send me a DM and I'd be happy to walk you through in more detail how our product set works and the results we've been able to achieve on behalf of our clients to date.
Please comment below with a question or opinion and I look forwards to answering and providing additional insights to all queries.
Tim
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LinkedIn User
Ben Robinson interesting read!
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Richard Sheroff
We are only scratching the surface. The culmination of real time data analytics on truly "big data" with predictive abilities is the disruptive technology that is far past due. It requires a new computing paradigm since the fundamental algorithms involved in handling sparse data is not suitable for Von Neumann architecture with their macho flops running at. 5% peak.
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Tim Llewellynn
Completely agree we haven't even got to a stage where we have "fit-for-purpose" hardware for AI and data-driven software - we are still running around with legacy hardware repurposed. Once a stream of new hardware solutions can into the mainstream there will major disruption and capabilities available that weren't imaginable before.
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LinkedIn User
Patrick Barnert nViso.... and interesting about the FCA Sandbox...
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Priyanka Pawar
Congrats Tim!
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Igor Shaposhnikov
Very good, Tim! Congratulations!
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Denyse Drummond-Dunn
Great news. Perhaps now UBS will realise what they missed last year?!
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LinkedIn User
Congrats Tim & team, this is a huge step to learning the Finance vertical - he who learns most fastest wins!
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Michael O'Sullivan
Kevin Knull, CFP® Anthony Clark-Jones Hester Turton Andreas Bolli Christian H. David Bruno Martin Weis
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Just an update:
In 2017:
Tim Llewellynn
Completely agree we haven't even got to a stage where we have "fit-for-purpose" hardware for AI and data-driven software - we are still running around with legacy hardware repurposed. Once a stream of new hardware solutions can into the mainstream there will major disruption and capabilities available that weren't imaginable before.
In 2023:
https://nviso.ai/en/news/nviso-s-la...l-neuromorphic-processor-platform-at-ces-2023
NVISO’s latest Neuro SDK to be demonstrated running on the BrainChip Akida fully digital neuromorphic processor platform at CES 2023
The SDK release supports the latest advancements for analysis of complex emotions:
Following the recent NVISO Neuro SDK milestone release, including two new high performance AI Apps from its Human Behavior AI App catalogue, Gaze and Action Unit Detection, NVISO is pleased to announce that the SDK can be seen running on the BrainChip Akida platform by visitors to the Socionext CES 2023 stand located at the Vehicle Tech and Advanced Mobility Zone in the Las Vegas Convention Center, North Hall, Booth 10654.
...This latest release of the SDK for use by solution developers will support implementation across an increased range of use case scenarios providing for deployment of a wide selection of NVISO’s existing range of real-time, deep learning-based AI Apps, such as those used for face detection, gaze, head pose recognition, facial analysis, emotion recognition, object detection, gesture recognition and body pose analysis along with its recently announced implementation of state of the art graph-based facial analysis applicable to the analysis of complex emotions.
Implementation of complex emotion analysis using state-of-the-art graph-based facial analysis. As one of the most important affective signals, facial affect analysis (FAA) is essential for developing human-computer interaction systems. Early methods focussed on extracting appearance and geometry features associated with human effects while ignoring the latent semantic information among individual facial changes, leading to limited performance and generalization. Recent work attempts to establish a graph-based representation to model these semantic relationships and develop frameworks to leverage them for various FAA task.