Understanding the Financial Challenges of Gig Workers
November 7, 2022 | 1 min read
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April 22, 2016 | 0 min read
FinovateSpring is off and running. Session 1 jitters are out and we are now on to Session 2. I’m up the press room surrounded by pictures of rock legends who have performed here; Tower of Power, Chicago, Jefferson Airplane. There is no picture of Dionne Warwick singing “Do you know the way to San Jose.” I need to get on that. Does anyone know her?
Many companies continue to innovate around the use of big data, ID verification, payments/payment processing, mobile wallets…and PFM!
After watching the Digital Insight and CuneXus I felt a sudden urge to run out and visit a car dealership. Both companies used the consumer car buying experience as a backdrop to frame the use case of their technology. Both companies are focusing on leveraging their deep customer data to empower the creation and distribution of special offers. At first this sounds very Cardlytics, but the use case is slightly different. The application is designed to present special offers around the best rate or terms for a car loan, mortgage, etc. The CUneXus presenter went as far as saying their solution creates “preemptive lending” opportunity.
This technology presents an opportunity for financial institutions to generate more revenue from their customer bases…by leveraging one of the biggest assets they have (besides the cash), customer data. As we know, the lending environment is tight and qualifying is tougher. However, the technology is very compelling and something financial institutions should look at closely.
I come from a personal finance management (PFM) background so I find any PFM presentation interesting. Why? Because PFM is hard to do. Customer engagement is tough and banks find it difficult to justify an investment in the technology. FlexScore strives to help consumers manage their money better. The standard mint.com-like money management tools are available in their application…including a FlexScore. A Flexscore is a branded “metric” that helps customers measure their financial health based on achieving financial goals. Not sure how well customers will attach themselves to this…don’t credit scores do this…and credit scores count?
The new “innovation” for FlexScore is the launch of a network of financial advisors to provide personalized financial advice to the end user. So…it’s PFM + financial advice from a live person. Hmmm…this is a tough space to play in. Finovate presenter, Alexa Von Toble and her team at Learn Vest are doing this really well…and they are gaining traction in a BIG way. However, to FlexScore’s credit, there is always room for other players…but they had better move fast and do it with a personal touch.
There continues to be a lot of action around the mobile wallet and mobile payments space. Please note that these spaces are frequently perceived as the same…but are very different. Quisk presented technology that strives to digitize cash….and enable cash payments from a mobile device from a customer to a merchant. This feels like a more merchant focused P2P play…with merchant focus. Again, Quisk will hit the same challenge (proverbial wall) of the other payment tools like PayPal and Square. Quisk will need to drive adoption of their payment processors to merchants.
However, Quisk may have a HUGE advantage here. Quisk is claiming to have relationships with major banks in the South American and Middle East markets. Assuming these banks provide payments machines and networks to small businesses, the Quisk platform could be widely distributed. The US market, as we know, is an entirely different story. Quisk will struggle breaking into the US.
Lastly, Interactions demonstrated great technology around the automated CRM space. It was very cool, I thought and automated much of the standard processes banks must manage with customers. The technology worked very smoothly during the demo too! Bravo! The big rub for me on this technology is that it’s not perfect and will stumble depending upon the consumer’s phone connections, voice volume, accents, etc.
Consumers will also use their own ways of saying and asking for things. This “natural language” challenge will throw any automated system for a loop. For example, many of us Californians start sentences with the word, “dude.” An automated system may not understand “Dude, I need to open up an account. Totes transfer me to a rep, brah.” In standard English this means “I would like to open up an account. Please transfer me to a representative.” No IVR can make this translation accurately.
Off to lunch…and then comments to Session 3.
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