Why fintechs, not advisors, are driving change in financial planning

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Financial planning development is speeding up, but the pace is not being set by the advisor industry.

“I believe we are right at the beginning of a supercycle,” says Cinch Financial CEO and founder Sean Collins.

The Boston-area based startup is at the bleeding edge of how I have come to think young consumers will expect to embrace financial planning — that is, without them even knowing what they are engaged in is financial planning.

Cinch tends to refer to what it is building as autonomous personal finance. Their free direct-to-consumer online service acts as an always-on holistic fiduciary software agent. It takes in a user’s financial life, inclusive of debts, savings, day-to-day cash flow, insurance, and large monthly bills.

Cinch then takes this data and applies behavioral science and predictive analytics to help their users make the smartest financial decisions in their day-to-day lives. This ranges from how much to save, to how to prioritize payment of their debts from month to month, whether student loans, credit cards or when it will be best to get a mortgage if that is among their goals.

Cinch primarily targets millennials who have debt and not a lot of assets.

“We start with someone’s everyday finances and then turn to big goals like buying a home and building retirement savings,” Collins adds. Unlike quite a few fintech founders, Collins is not a young visionary right out of college. His Twitter profile quips that he is a “financial services lifer now redeeming myself through Cinch.”

Wealthfront is doing something similar in terms of longer-term goal planning with ongoing developments of its Path product. Though it is not helping a user prioritize monthly budgeting and spending, it has evolved from an initially simple, straightforward planning process that began with account aggregation and morphed into a tool tackling some of life's biggest financial decisions, like buying a home.

The startups are employing data scientists and working with various forms of artificial intelligence, including machine learning, in a way I have yet to see when it comes to the financial planning software available to advisors.

“It is a gap,” says William Trout, who heads research firm Celent's global wealth management practice.

“There is a pretty big divide between financial planning technology and AI, this is kind of unchartered territory,” he adds. He made clear though, that while direct integrations between planning software and types of AI are yet uncommon in the advisor universe, the same is not true of CRM.

“Today, the rubber hits the road with the CRM platform,” says Trout. He cites Salesforce, which has gained among advisor clients, and the company’s Einstein AI.

“Enabling the CRM to connect wildly disparate information points by leveraging AI is going to be a work amplifier for advisors, enabling them to better scale their practices to work with more clients at greater depth,” says Trout.

eMoney Advisor CEO Ed O'Brien argues against the notion that AI and planning connections don’t exist in the incumbent advisory industry.

“Every one of them [the large incumbent firms] is working in those domains; one of the advantages with machine learning is that it gets better with more scale,” he says.

“Artificial intelligence is all about the algorithms and smart people anywhere can build a good algorithm but when it comes to machine learning it requires some scale to make the thing actually learn,” O’Brien adds.

While prototyping AI and machine learning will lead to future tools, applying it to task automation in the near term holds the key to improving advisors’ lives and growing their businesses.

“I think all of us are concluding the focus on integration for now is to automate and eliminate manual tasks,” says O’Brien. He agrees that planning-led relationships can evolve to a point where they can become entirely digital, entirely autonomous processes.

However, clients will inevitably want to talk to a human that possesses emotion, and can relate to emotion and factor it in to helping making decisions. “But it is hard to say; is it 5%, 10% of the time?” he asks rhetorically.

Others suggest that there is plenty left to do without enlisting the absolute most cutting-edge technology.

“There is a race among companies that are progressive and startups like ourselves,” says Steve Chen, founder and CEO of NewRetirement.

“What we are doing is not AI, rather very personalized, pretty intelligent and precise suggestions,” he says of his company’s direct-to-consumer free online retirement software. It was developed for those over 50 who are approaching retirement but find themselves unprepared, a crisis that confronted Chen's own educated, professional mother.

He said his users do not share the same mindset as millennials who are much more comfortable with account aggregation and sharing their account credentials.

“We do projections based on what they do tell us they have, and are capturing very granular data from them,” says Chen. Then the application applies what is in its knowledge database. He illustrated this by talking about industry Social Security expert Mary Beth Franklin, who he recently interviewed for a podcast.

“Think of the permutations around taxes or even Social Security alone, for example, for those married more than 10 years in certain circumstances,” he says. “It’s those types of things we have built or are building into the software.”

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Automated investing Artificial intelligence Machine learning Fintech Mobile technology Apps CRM systems