AI and the Pocket-Sized Financial Assistant
In my last piece, Banking in the Age of Millennials, I wrote about the rise of a digitally-native generation, representing an immense opportunity for financial institutions. I also mentioned how Millennials differ from older age groups: they maintain low trust in banks, have a mobile-first expectation for financial products, and are more willing-to-try new products and services that take aim at a broader set of their financial needs.
These findings led to 3 recommendations for developing Millennial products: hyper-personalization, build to rebuild, and the pursuit of value-add integrations and partnerships.
I originally framed these tactics as a means for veteran financial institutions to rethink their product development. However, I spent most of my time at the Tech Crunch Disrupt Conference in September searching for startups that were leveraging the recommended approach.
It was hard to ignore the immense number of startups with artificial intelligence (AI) solutions that attended the conference. AI technology was particularly salient among FinTech companies at the conference, which is unsurprising given the unprecedented number of AI ventures backed this year.
Of the 25+ FinTech companies I spoke with at the Conference, two stood out among the pack: Clear and Olivia. Both companies are combining Natural Language Processing (NLP) backed chat bots with machine learning capabilities to deliver powerful and personal financial management platforms.
Clear
An AI-powered solution, Clear combines business financial management (BFM) with a credit card to deliver a next generation financial manager for Millennial small business owners.
In chatting with company co-founder Michael Rangel, I learned that Clear aims to solve a pain point cited by many small business owners related to mainstream financial management tools. Current BFM software is misaligned with both the expertise of the average Millennial, and with Millennials’ preferred method for engaging with business software solutions. “Quickbooks is built for accountants, not small business owners,” Michael mentions. “They just dump CSV files of data onto you, without highlighting what or where you should be focusing.”
With this in mind, Michael and the Clear team built a solution that provides “passive guidance,” front-loading only important budgeting insights.
For example, in asking Clear for a financial summary below, the Small Business owner is provided with not just sum-total of their monthly spending, but also a warning of above-average travel-spend and a flagging of unusual transactions.
The power of Clear rests in only tapping the small business owner on the shoulder when necessary, with the determination of “necessary” becoming more precise as the machine learning-backed platform uses behavioral data to continually improve the quality of its financial insights.
Olivia
Aiming to help Millennial consumers stretch their paychecks, Olivia is an everyday financial assistant that, like Clear, is powered by artificial intelligence. With her chat bot interface, Olivia seamlessly walks you through connecting your financial accounts. The more connectivity you provide, the more powerful the insights she delivers in return.
Exemplifying that ability, Olivia’s Safely Spend feature assesses your spending patterns to provide a daily amount you can safety spend in pursuit of your monthly savings goals. These recommended daily maximums evolve as the month progresses, and take into consideration how your spending trends by both day of the week and time of year. The benefits of machine learning are particularly salient here, with Olivia’s recommendations becoming more aligned with your natural spending as you spend more time on the platform.
Olivia and Clear are still in their early stages of launch, with both currently in private beta (only open to a limited number of users). Their ability to grow into widely-adopted platforms hinges on their development approach, which can be assessed using the 3 recommendations previously mentioned.
- Hyper-personalization: how big is your data?
The AI components of both platforms humanize the experience. But this personal touch is worthless without providing financial insights and recommendations on par with those delivered by actual, human financial experts.
Key in being able to deliver those insights is access to a large quantity of data. In that regard, I chatted with Olivia co-founder Lucas Moraes about an ever-improving Olivia feature that will map consumer spending patterns against alternatives to provide the user with money saving opportunities. As a specific example, Olivia could see that you traditionally shop for groceries on Saturdays, the day of the week with the highest shopper traffic. She could compare that against how much you would end up spending on groceries if you shopped on different nights, and recommend the least expensive alternative. Such a recommendation would be hyper-personal, but entirely contingent on the Olivia team’s ability to access real-time geo-based grocery pricing data by day of the week, and to process it into a consistent and reliable database.
2. Build-to-rebuild: iterate, and then iterate some more.
From location and spend-based saving insights and offers to budget management tools, Clear and Olivia can and should experiment with the immense array of features that could be built into their platforms. But key to their success is an ability to rapidly pilot, collect feedback, and either double down on features with traction or abandon those without it. This approach will enable a steady stream of financial features that continually delight users and sustain their engagement.
3. Value-added integrations and partnerships: Scale. Scale. Scale.
From lightweight marketing partnerships to outright strategic purchase of their platforms by a partner, Clear and Olivia need to engage veteran financial institutions in quickly ramping up adoption of their services. Banks with foresight should jump at this opportunity, understanding that such services layered on top of their core products would drive customer loyalty to a degree that they could not achieve working alone.
The road forward is clear, with powerful AI solutions poised to displace the traditional tools used to manage personal finances. Clear and Olivia are leading this charge, delivering hyper-personalized, real-time advice through platforms that place Millennial needs at the heart of their solutions. Veteran financial institutions, like consumer banks and advisory shops, would be smart to follow suit.
