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How Financial Brands Create Virtual Assistants that Respect Users' Privacy

AI-powered 'concierge' services are on the rise in Canada

An interview with:
Hossein Rahnama
Founder, CEO
Flybits

As virtual assistants like Apple's Siri and Google Assistant become a bigger part of consumers' lives, companies in Canada are exploring how to move beyond chatbots and create predictive "concierge" experiences for their customers. But it's a challenge to build a service that adds value, and isn't just a flashy use of artificial intelligence (AI). eMarketer's Paul Briggs spoke with Hossein Rahnama, founder and CEO of fintech AI firm Flybits, about why financial brands are ahead of the pack, and how they're creating and measuring these services.

eMarketer:

What brand categories are well-suited for these predictive, AI-based concierge services?

Hossein Rahnama:

Our current focus is the financial services sector because these organizations have a lot of valuable data. They can use that data ecology to engage with their customers in a meaningful, micro-personalized fashion.

We see the same happening in other industries. Textile companies, for example, are getting into insurance because they're putting sensors in clothing, so they understand biological behavior and use that data to be relevant in the insurance business.

Data is also shifting these companies from one vertical to another. High-end retail brands like Louis Vuitton are getting into the hospitality business by building luxury hotels because they know their customers' purchasing patterns.

eMarketer:

What are the primary use cases of AI for financial services companies?

Hossein Rahnama:

They fall under three core areas of the financial sector. One of them is retail banking—under that is lending, mortgages, card services, fraud management and branch services. Banks are looking to add value through lifestyle customer engagement initiatives that go beyond just offering products.

Another vertical is asset and wealth management, which includes robo-advisors, bringing financial and investment data and applying it to the daily life of the customer to improve financial behaviors.

The third area is insurance—using AI data to make insurance products more understandable and usable.

Interview conducted on August 31, 2018
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