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Consumers increasingly expect higher levels of personalization from their financial services providers. Whether it’s from a challenger bank or Bank of America, people are used to Netflix-level of recommendations. An entire industry is cropping up to help provide a consumer’s data from all her accounts so that a service provider can provide actionable advice when she needs it most.
Envestnet I Yodlee’s senior vice president of product, Brandon Rembe joins me on the podcast to talk about what leading financial services organizations are doing about best practices in personalization for their customers. Hyper-personalization, he says, presents an opportunity for FIs to provide insights that take into account and anticipate consumer behavior based on their savings, investing, and spending habits.
Especially in crazy times like we’re experiencing today, aggregating financial data and creating insights with these tools ultimately enables consumers to have a more complete understanding of their financial health and empowers people to improve their long-term financial wellness and reach their goals.
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The following excerpts were edited for clarity.
Moving from Tamarac to Yodlee
After moving over from the Tamarac side of the business to Yodlee, it's a lot of the same data and types of technologies. But we're asking different questions. If someone has $20 million in their account, their problems and questions are very different from someone who has $20.
I've spent a lot of my time over the past two years going really deep in the retail space, making sure we've understood the problem segment that's being solved through different financial cohorts, like someone who's saving for an emergency fund versus saving for a house. I wanted to understand how we can assist in the complete financial journey.
Changing consumer demands
Consumer expectations have absolutely changed. Neobanks are changing the way people want to interact with their finances.
We also acquired Abe AI early in 2019. They do conversational UI for the bank vertical. People are much more willing to work with a chatbot or a virtual assistant on their finances, but they want their questions answered right away and tailored to them. They don't want general information.
We've seen a huge pivot in customer demand becoming much more real time and hyper-personalized.
Incumbent FIs and personalization
If you look at it as ROI to the consumer, the initial trend was setting up personalized alerts for consumers. If you have a bill coming up or have a payment overdue -- banks were telling people things they probably already knew. That's not a lot of value add.
It's also a little too generic. I remember signing up for this at my bank and I got like 50 alerts the first day. I'm like, nope, I'm turning that off because most weren't meaningful to me. Most institutions are probably at this general alert stage.
Some banks, like Bank of America with Erica, have taken the next step to provide more insights to customers, saying here are some spending trends or some predictive cash flows. To take it to the next level is to take those insights and alerts and make them fully actionable. There are very few cases of helping consumers move down that path to create better financial outcomes.
Next steps in personalization
Right now, banks should understand that they need to look at their customers' complete financial picture. It's one thing to say, based on the data I'm seeing, that you should save more for retirement. But if I don't know that the customer has $500,000 in his 401(k), the advice isn't as relevant. Yodlee and other aggregators play a big part in this, so a consumer can connect all her financial data into a single location.
That data also needs to be normalized and enriched. The data needs to make sense. If you look across the Yodlee network, there are 272 different ways credit card companies classify Starbucks. You have to understand how much a consumer spends at Starbucks to be able to provide any type of insight or advice. Then you can begin to provide holistic insights that are hyper-personalized to a consumer to take action on.
Creating personalized, actionable advice
Institutions are at different stages. The ones that have gone far down the path are seeing much higher consumer engagement. The last piece is actionable insights. A lot of people are reviewing their recurring subscriptions right now. One of the things I looked at when I ran my data through Yodlee was that I was still paying for two gym memberships in California that I forgot to cancel. I now live in Washington.
Imagine if that was a one-click, seamless process, instead of calling up and negotiating cancellations. One gym was trying to get me to come in to the gym to cancel. A bank could tell me that with this $100 month I saved, I could now add it to my underfunded retirement fund. Those are the types of experiences we're working with financial institutions to create now.
Quarterbacking insights
It's a combination of multiple data providers. In the case of a financial institution, they have their own held data. They combine that with held-away data from other institutions. You combine that with insights from Yodlee and in some cases, Yodlee can provide insights that a single institution can't. We have peer benchmarking insights, where we have a much broader view because we have tens of millions of users we can pull this data from. We can provide broad trend analysis to tell someone how their spending on Amazon compares to peers with similar income and demographics.
With COVID-19, a lot of people have questions about their spending and are making changes. They want to compare themselves to other peer groups. We can allow individuals to slice and dice their peer networks to see if they're spending more on groceries than people similar to them or whether their debt to income ratio is way higher than it is for others in their peer group.
Yodlee product pipeline
Data aggregation has been at the core of what we do at Yodlee for the past 20 years. We connect to 23,000 financial institutions across the world. We are now upleveling the data we get. Being able to normalize and enrich that data so I can identify that you spent $27.36 at Starbucks at this store on this date. That helps us provide great insights to consumers. We use very large AI models for the data cleansing and enrichment.
We take these trends and can do predictive analytics to see if a customer can pay all his future bills given current spending and a large recurring expense he has coming up.
We're continuing to create more peer groups and cohorts within our peer benchmarking analysis. Lastly, we want to provide more actionable insights, using 3rd-party demographic data to help users better analyze their spending to make better outcomes. Given our assets at Envestnet, we can look at what others have done successfully through their financial journeys to provide retail consumers with the type of insights they need to succeed.