|FinTech companies, financial enterprises, and financial advisors
|Quovo is a financial data platform, which empower its clients with account connectivity and insight tools delivered via its API and user interface widgets
|Lowell Putnam, Cofounder, CEO
Niko Karvounis, Cofounder, CPO
Michael Del Monte, Cofounder, CTO
Quovo is a fast-growing startup that enables fintech companies and enterprise-level financial services providers to connect to consumer financial accounts. The company is based right in the heart of Manhattan and has an open-space office where everyone is within arm’s reach of each other. I was happy to get the chance to talk to Lowell Putnam about Quovo and its offerings.
The inception of Quovo
Lowell came to wealth management from the investment banking space. He worked at Lehman Brothers and Barclays Capital, where he worked in the Financial Institutions Group with a specialization on consumer lending. In 2008, Lowell started trading stocks and became an active personal investor. This is when he faced problems tracking his own investments over time.
Then, Michael Del Monte, who is CTO at Quovo today, began working on pulling data from websites or APIs where people had retail brokerage accounts, and then doing performance reporting for those working in the retail sector.
“This [data] seemed to be a real problem. People didn’t seem to know how they were doing. And obviously in a crisis and post-crisis world it seemed very important.”
This data-pulling, which started as a hobby, coincided with the start of the robo-advisor trend and the explosion of innovation in the wealth space. Once Lowell and Michael realized that they had built an interesting new platform for pulling outside account data into other platforms, which they anticipated would become a much bigger trend, they decided to join forces with Niko Karvounis, CPO of Quovo, and make a business out of it.
“We actually thought we would be B2C [a consumer-facing business] at first. Right then, there were so many new robo-advisors starting. Trying to move into the space we realized, instead of competing with this new batch of startups, why don’t we actually service them? Why don’t we become an infrastructure player as opposed to a B2C company?”
Quovo has raised more than $20M in total funding over four rounds.
In 2013, the startup raised $1.4M in Series A funding for investment analytics; the investment drive was led by Long Light Capital. At that time, Quovo had the platform in beta with users ranging from sophisticated hedge funds down to retail investors with an E*Trade account.
In 2015, Quovo closed a $4.75M funding round led by Fintech Collective. Long Light Capital participated again. Quovo offered a full-stack platform that provided aggregation and business intelligence analytics; its dashboard tools made complex data insights intuitive.
Two years later, in 2017, Quovo raised $10M in Series B funding. F-Prime Capital and Napier Park Financial Partners co-led the round. Quovo used the funds to accelerate the growth of its suite of data analytics offerings, including the bank authentication API and Quovo Connect module.
In May 2018, the company obtained $4M in investment from Salesforce Ventures and Portag3 Ventures. With partial support from the investments, Quovo has begun to partner with Canadian FinTech companies and institutions to replicate their US success in the Canadian market. Quovo’s vision is to build a regional team and accelerate innovation in Canadian FinTech. Lowell Putnam says,
“We wanted to make sure that we moved into the market with expertise, so we hired a head of Canadian strategy who’s been there for a long time and knows the market well.”
In the US, there are a number of data aggregators that help financial advisors, institutions, and FinTech companies provide their users with access to all their banking and investment data, enabling them see their finances, portfolios, and performance in one place. Quovo’s competitors include the following companies:
- Finicity, which has developed more than 16,000 bank integrations and provides a suite of APIs for financial management, payments, and credit decision making.
- Yodlee, which offers financial applications and personal financial account information for banks, entrepreneurs, and individuals. In 2015, Yodlee was purchased by Envestnet and is focused on investment data.
- Plaid, which aggregates bank transactions and provides APIs to help financial applications connect with user bank accounts.
- Morningstar’s ByAllAccounts, which provides a data-aggregation system that gathers, transforms, and delivers financial account data.
Lowell Putnam has a great deal of respect for the incumbent technology providers in the space:
“Yodlee is very competitive in the market. They’ve been around for about 20 years. They really invented the space.”
However, Lowell thinks that Quovo has a slightly different focus than the competition.
“We’re totally agnostic to what you want to use customer account data for. The more different use cases there are, the more excited I am to have our service out there.”
Lowell sees his company to have the advantage of being much younger, using other technologies, and having different cost structures.
The difference between Enterprise and FinTech customers
On their site, Quovo highlights three different industry verticals the company works in: wealth, lending, and payments, as opposed to targeting specific categories.
According to Lowell, borders between startups and large institutions are increasingly blurring.
“Robo-advisors like Betterment and Wealthfront, what do you call that? Are they startups, or are they enterprises? They have hundreds of thousands of customers, they have billions of assets. They’re looking more and more like Enterprise customers.”
At the same time, Lowell mentions big insurance companies that have their FinTech squads and teams building financial tools. Quovo’s offering has become part of these tools. Thus, Lowell considers these enterprises as akin to FinTech startups.
“I’d say that the biggest difference, if I had to [cite] one, is vendor management and procurement that is obviously a stated function [of] an enterprise, while it generally is more ad hoc at a FinTech company.”
The need for maintainability
Quovo aggregates data about bank accounts, investments, credit cards, insurance, student loans, etc. Unlike most startups, which think mostly about new features, Quovo expends a great deal of effort on maintaining the built infrastructure and technology.
“We need to stay on top of changes that happen at thousands of end institutions. We are building infrastructure, both human infrastructure, operational infrastructure, and technical infrastructure, to maintain our connectivity. We have connections based [anywhere] we need [them], but maintaining those connections, and maintaining them really quickly, is very challenging.”
Lowell states that connections must be fixed quickly to ensure that their clients don’t face service disruptions on their own platforms. According to Lowell, Quovo runs outlier reports on millions of accounts every night to identify inaccuracies, delays, and other issues.
“There is no way you can have enough people watching thousands and thousands of connections, so we need to have automated monitoring systems to tell us where to allocate our development resources to fix those broken connections.”
The best QAs are the clients: once a client finds a problem and informs Quovo about it, Quovo’s team solves it quickly and notifies both those who have discovered the issue and everyone else who has yet to do so.
Being in the middle, Quovo has the ability to ask institutions to correct their data, but they also build their own processes to deal with broken data and correct it if possible. Otherwise, the system stops sending data to Quovo’s customers until the institution in question corrects its own problems.
“Happy”/“unhappy” paths to authentication
Quovo provides account aggregation to offer a holistic 360-degree view of end users. To verify account ownership and balances, the company offers account authentication services. Lowell says:
“The three main ways to think about how we gather data is a happy path, [a] less happy path, and [an] unhappy path.”
He describes instant account verification as “the happy path.” In this case, the user authenticates at an institution with his/her credentials and Quovo is then able to retrieve the information needed to initiate an ACH process.
Since some institutions don’t make full instant authentication information available, users may need to validate an account. In this case, Quovo offers “the less happy path”—it initiates and automatically verifies microdeposits using its aggregation technology to parse an account’s transaction history for the receipt of the test deposits.
“The unhappy path” is required when an account is not connected to Quovo (e.g., Quovo doesn’t cover an institution). In this case, the system initiates a traditional microdeposit but cannot verify it; the customer needs to check it two days later and verify the account.
“Obviously the unhappy path is very unhappy, because [around] 30 to 50% of microdeposits don’t ever get verified.”
Moving from the raw data into insights
Talking about the company’s upcoming plans, Lowell mentions their Cue product.
“There [are] a lot of useful insights wrapped up in the data, but most people—especially most advisors—don’t have time to look at raw data for their clients and then distill that information to tell a story. If we can help distill insights out of that data a little bit faster, we can add operational leverage into an advisor’s practice.”
The company aim to create a simple query-based Boolean system that checks certain parameters within an account and alerts advisors if they correspond to specific conditions.
“We have a couple hundred cues already built. They range from very simple ‘what is a client’s net worth?’ or ‘has a client’s net worth increased beyond a certain amount in a certain period of time?’ to more complicated, such as ‘has one of this client’s accounts outperformed other accounts on a rolling 90-day basis?’ which obviously requires retrieving data, normalizing it, calculating performance off of it, and then comparing the two performances.”
Quovo is also working on predictive cues that look for life events that can be determined from significant changes in spending or in the client’s cash flow. For this purpose, the system analyzes spending transactions and uses machine learning and AI in its algorithms. Lowell believes that the most complicated machine learning is used for the least interesting data points, such as identifying whether the account is taxable.
“The predictive stuff is pretty straightforward, it’s almost heuristic, because you can just simply tell when spending categories or transaction types have changed in such a dramatic way. You can set a pretty hard threshold for what dramatic is, and then that threshold probably adjusts over time.”
Working with customers and the team structure
Unlike many other companies, Quovo prefers to not customize their product to their customers. Instead, Lowell says that prefer to make their features configurable.
“The person who gets customized software ends up with something that’s out of date immediately, and the tech team here now has a forked repository, so there’s all kinds of problems with that. We avoid that at all costs.”
The company needs time to balance between a long-term roadmap, which considers industry trends, and a short-term roadmap, which is client-driven. They have to think about priorities from current customers, new customers, core verticals such as wealth, and ways in which to spread core data services over new lines of business. For these purposes, Quovo has four product managers, each of which is focused on one of the following areas:
- the core infrastructure layer;
- the front-end widget;
- the API;
This corresponds to the division of the development team:
- A dedicated front-end team works on tools and widgets, and is 90% front-end based;
- Two backend teams are focused either on data science and analytics or API infrastructure;
- A data retrieval team gathers data and handles institution connections;
- The Dev-Ops team is separate from each of the other teams, but services all of them together.
“As we get bigger, I’d love for us to reach a stage where we have people from each discipline on each team. But today, we’re more functionally focused than product focused.”
According to Lowell, the company includes more than 70 people, about 30 of whom are technical software engineers.
The platform is based in AWS and has multiple availability zones. The entire architecture is cloned to Canada, and Ireland. The company builds a continuous integration and continuous delivery (CI/CD) process that allows it to deploy across jurisdictions. The deployment layer is separate from other layers; it includes API servers that are independently load balanced.
“I don’t know if we fall under the firmest definition of truly microservice-based, but definitely a services-based structure.”
At Quovo, Datadog is used to monitor all processes. Since the company can’t send any data from their database outside, the team had to develop their own internal administrative tools.
For the CA process, they have benchmarks and tests that cover all code.
“Getting into a continuous deployment cycle for our syncing code is very important. And it’s more important than our application code, because a syncing code has to get updated […] immediately so that each individual syncing agent can be independently deployed if they meet the integration tests, and if they break that’s just one that breaks, not the whole system.”
To enable their clients test changes before they are pushed into production, Quovo has a number of stage environments that are independently maintained for clients.
Quovo already has a number of small and medium-sized FinTech companies and larger institutions as customers and data sources, and is now ready to win larger customers. The company has proved their ability to efficiently process manifold data, protect end users and be a valid contender for large deals.
We may expect to see Quovo finding new lines of business within wealth management and expanding their strategy into other FinTech areas, such as insurance, lending, mortgage, etc. It looks like the company’s vigorous team will be able to offer data services based on any retrieved financial data.