Video + AI = the future of finance

The financial services sector is rapidly walking up to the potential of video to transform the customer experience, but adding AI into the mix takes it to a whole new level, says David Fulton, CEO of computer vision leaders WeSee.

The most forward-thinking banks, finance houses and insurance companies are deploying video to dramatically improve both customer service and operational efficiency. A recent report by media management company Imagen reveals that many of the traditional giants like Barclays now offer remote face-to-face banking via video call, while in wealth management, high-end video conferencing is being deployed to offer personalised services globally.

Unsurprisingly, the disruptor digital banks are taking this a stage further, harnessing video to accelerate customer onboarding and verification. Carrying out customer checks traditionally takes on average 26 days, says the Imagen report, which reveals that smartphone-only bank Monzo is aiming to slash this to just five minutes using video. These market challengersare also making video a key part of their secure ID and sign-in process, as well as for biometric identification. Starling, for example, asks customers to record a short video of themselves reading out a specific phrase, which is then used for biometric identification if they get locked out of the bank’s app.

However, this is only scratching the surface of what is possible across the financial services space with video. Add artificial intelligence (AI) into the mix and a new raft of exciting options opens up. The problem with video to date is that it has been notoriously difficult to categorise. So, for example, if you film a meeting – something that’s happening more and more in finance – it would be difficult to search for a specific part without scrolling through the entire video. This is where the latest developments in AI-driven deep learning computer vision come in, which can understand every multi-layered element within images and videos in the same way humans do, only multiple times faster. This enables videos to be categorised and searched quickly and easily. With more and more client video footage being taken, this could prove critical when a company is asked to disclose the data it is holding on a particular client, as required under GDPR, helping avoid a large fine.

Combining computer vision with video also has significant potential in terms of safety and security. AI is being used increasingly to identify individuals through facial recognition, but now it’s possible to take this a significant stage further and detect human emotions through the analysis of facial micro-expressions, pupil dilation, eye movement and gaze. By combining this information with speech patterns and tone of voice analysis, it’s possible to identify seven key human emotions. What’s more, the technology only requires low resolution video footage – namely that frequently used for CCTV and other identification purposes.

By viewing someone’s face live or on recorded video in real time, this technology cannot only identify an individual, but also assess their emotional state more deeply than any human is able to. Rather than simply spotting whether someone is happy or sad, it can gauge integrity – essentially, the likelihood that someone is being truthful. It can also categorise scenes in real time through streamed video footage, detecting unrest, disturbances and conflict, or whether someone is stressed or anxious, as well as suspicious behaviour. In fact, it has already being deployed in the security sector for validation and real time analysis.

Applied to the financial sector, it could be used to tighten safety and security at the cash point, in store, or on the trading floor by assessing people’s emotional state in real-time. In insurance, meanwhile, this deep learning computer vision has the potential to significantly reduce claims fraud by providing assessors with key insight into a claimant’s trustworthiness at point of application or first notice of loss in real-time via video or mobile phone app.

Video innovation may have arrived in banking and finance, but it’s the latest developments in computer vision that will enable companies to squeeze the maximum value out of it, transform the employee and customer experience, and create a safer, more secure environment for all parties.

David Fulton is CEO at computer vision pioneers WeSee. 

WeSee.com

The financial services sector is rapidly walking up to the potential of video to transform the customer experience, but adding AI into the mix takes it to a whole new level, says David Fulton, CEO of computer vision leaders WeSee.

The most forward-thinking banks, finance houses and insurance companies are deploying video to dramatically improve both customer service and operational efficiency. A recent report by media management company Imagen reveals that many of the traditional giants like Barclays now offer remote face-to-face banking via video call, while in wealth management, high-end video conferencing is being deployed to offer personalised services globally.

Unsurprisingly, the disruptor digital banks are taking this a stage further, harnessing video to accelerate customer onboarding and verification. Carrying out customer checks traditionally takes on average 26 days, says the Imagen report, which reveals that smartphone-only bank Monzo is aiming to slash this to just five minutes using video. These market challengersare also making video a key part of their secure ID and sign-in process, as well as for biometric identification. Starling, for example, asks customers to record a short video of themselves reading out a specific phrase, which is then used for biometric identification if they get locked out of the bank’s app.

However, this is only scratching the surface of what is possible across the financial services space with video. Add artificial intelligence (AI) into the mix and a new raft of exciting options opens up. The problem with video to date is that it has been notoriously difficult to categorise. So, for example, if you film a meeting – something that’s happening more and more in finance – it would be difficult to search for a specific part without scrolling through the entire video. This is where the latest developments in AI-driven deep learning computer vision come in, which can understand every multi-layered element within images and videos in the same way humans do, only multiple times faster. This enables videos to be categorised and searched quickly and easily. With more and more client video footage being taken, this could prove critical when a company is asked to disclose the data it is holding on a particular client, as required under GDPR, helping avoid a large fine.

Combining computer vision with video also has significant potential in terms of safety and security. AI is being used increasingly to identify individuals through facial recognition, but now it’s possible to take this a significant stage further and detect human emotions through the analysis of facial micro-expressions, pupil dilation, eye movement and gaze. By combining this information with speech patterns and tone of voice analysis, it’s possible to identify seven key human emotions. What’s more, the technology only requires low resolution video footage – namely that frequently used for CCTV and other identification purposes.

By viewing someone’s face live or on recorded video in real time, this technology cannot only identify an individual, but also assess their emotional state more deeply than any human is able to. Rather than simply spotting whether someone is happy or sad, it can gauge integrity – essentially, the likelihood that someone is being truthful. It can also categorise scenes in real time through streamed video footage, detecting unrest, disturbances and conflict, or whether someone is stressed or anxious, as well as suspicious behaviour. In fact, it has already being deployed in the security sector for validation and real time analysis.

Applied to the financial sector, it could be used to tighten safety and security at the cash point, in store, or on the trading floor by assessing people’s emotional state in real-time. In insurance, meanwhile, this deep learning computer vision has the potential to significantly reduce claims fraud by providing assessors with key insight into a claimant’s trustworthiness at point of application or first notice of loss in real-time via video or mobile phone app.

Video innovation may have arrived in banking and finance, but it’s the latest developments in computer vision that will enable companies to squeeze the maximum value out of it, transform the employee and customer experience, and create a safer, more secure environment for all parties.

David Fulton is CEO at computer vision pioneers WeSee. 

WeSee.com