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Intellias Guest Blog: Surprise, Your Money Is Already Being Managed by Artificial Intelligence

Humans aren’t always great at making financial decisions — enter autonomous finance

Spending a few dollars here on a good sale and a few more there on a fine meal is easy to justify. But then you end up with just enough money for avocado toast but not enough to ever set foot on the homeownership ladder.

That is, unless you’re using one of the popular personal finance management (PFM) apps that proactively nudge you to get better with your finances.

Over the past few years, the PFM software market has been growing at breakneck speed. By 2023, it’s expected to reach $1,213 million globally, up from a modest $837 million in 2017.

But higher revenue is likely not the only thing that will distinguish the PFM sector of 2023 from that of 2019.

The more interesting market trend right now is the rapid evolution of PFM solutions into A.I.-driven personal financial coaches (PFCs).

What’s autonomous finance?

“Autonomous finance — algorithm-driven financial services that make decisions or take action on a customer’s behalf.” — Forrester Insights, August 2019

The big promise of autonomous finance is removing the human factor from financial decision-making and replacing it with A.I. wits. Or more precisely, providing users with access to a 24/7 personal finance coach that will assist with day-to-day money matters and long-term financial planning.

But will people trust A.I. to manage their money? According to research by Credit Karma, yes. The general public is more comfortable with the idea of autonomous finances than with self-driving cars.

And if you dig a bit deeper, that makes sense. Because most millennial consumers find finances too complex to grasp. Here’s more data to prove the point:

(In fact, we’ve published an entire whitepaper about new customer demographics and their banking preferences. Grab your copy here.)

Autonomous finance: key niches & use cases

Several types of FinTech players have already made their cautious foray into autonomous finances:

Wealth management: Wealthfront and Betterment started the robo-investing revolution and were among the first to chip away clients from traditional banks. Both products leverage advanced algorithms, powered by big data analytics, to offer optimal portfolio allocations for their customers and suggest the best course of action.

They perfectly match Deloitte’s definition of robo-advising 3.0.

More recently, however, new types of wealth management apps have been coming to the fore — fully autonomous investment assistants.

Robo-advising 4.0 uses self-learning A.I. algorithms to devise the optimal asset allocations based on an individual customer’s needs and real-time market conditions. Such apps can deliver advice and monitor/adjust customer portfolios in real time, based on the slightest changes.

Here are several early examples:

  • Kosho is a robo-advising app powered by deep learning. Launched last year in South Korea, Kosho expanded to nine more markets this year. It boasts an 83.1% accuracy rate for market regime detection.
  • Algoritz is an A.I. algorithm that you can connect to any of your brokerage accounts to automate trading in equities and cryptocurrencies.
  • Walnut Investments is working on self-learning trading systems for hedge funds.

Personal savings and budgeting: Apps like Mint and YNAB rapidly took over the PFM space thanks to their straightforward value propositions and effective UX design — something a lot of banking applications lacked.

Today, however, the first-gen PFM apps are starting to lose their positions due to the increased complexity of personal finances.

A lot of users now hold a portfolio of multiple financial instruments from both traditional banks, FinTechs, and nonfinancial service providers. According to an EY report, on a global scale, 18% of FinTech adopters use five or more different providers. In some mature FinTech markets, the percentage that uses five or more providers is even higher:

  • China — 36%
  • UK — 23%
  • Japan — 22%

To scale effectively, PFMs now need to connect more dots and not just detangle the complex landscape of users’ financial obligations and spending patterns but transform that mess into streamlined, actionable suggestions.

Several players have already come to the fore with advanced A.I.-driven money management products:

  • Plum is a chatbot-based financial coaching app with functionality spanning savings, bill optimization, and investments. It leverages A.I. to analyze users’ regular spending and suggests manageable financial goals as well as ways for accomplishing them.
  • Cleo is a similar A.I.-driven financial advisor, serving over 1.5 million users in the U.K., the U.S., and Canada. It helps users consolidate all their financial data and offers multiple tools (including gamified features) to optimize spending and maximize savings/investment opportunities.
  • Digit assists with spending and credit card management and automates savings. Since 2016, their U.S. user base has grown by 300%.

Lending: Streamlined lending is yet to make its way to the West, but Chinese FinTech giants are already showing how lending 4.0 can work in tandem with digital banking. In China, local super apps such as Ant Financial are leveraging big data analytics and machine learning to make personal micro-loans easier.

Credit Karma seems to be taking a page from Ant Financial’s book. Kenneth Lin, the company’s CEO, is a strong proponent of autonomous finances. In his talk at Moneyconf 2018, he said:

“Now 1% [of U.S. consumers] have access to great finances. With autonomous finance, we can actually give 99% the same fantastic mentorship, advisory, and products. Almost half of millennials are ready to make this transition [to autonomous finances].”

And that seems to be Credit Karma’s mission for the next several years.

How major FinTech and financial players are moving into autonomous finance

For the past several years, Wealthfront has been growing its data analytics muscle and heavily investing in its proprietary A.I.-driven financial engine, Path, which is in charge of analyzing all their clients’ data and transforming it into actionable insights.

Andy Rachleff, the president and CEO of Wealthfront, also believes that the future of finances will be autonomous:

“Our vision is to deliver a service where you direct deposit your paycheck with us. We automatically pay your bills. We automatically top off your emergency fund, and then route money to whatever account is the most ideal for your particular goals, whether they’re at Wealthfront or elsewhere.”

NOMI Insights and Budget, a new add-on to the mobile banking app from the Royal Bank of Canada, demonstrates how traditional banks are making into the fray of personal finance coaching.

NOMI uses A.I. and predictive analytics to gauge a customer’s spending history (across multiple accounts), work out an optimal budget, and assist with savings. The app proactively suggests new savings opportunities and notifies users of suspicious activity.

“The advancements that we’ve made in A.I. technology enable our customers to receive financial insights, savings and personalized budgets with ease, and we’re quickly seeing the value that these solutions provide to so many people.” — Peter Tilton, senior vice president, digital at RBC

In the U.S., Wells Fargo recently added predictive banking functionality to its mobile app. Apart from improved personal spending insights, users now receive over 50 different prompts based on their past, current, and future account activity that help them better manage their finances.

“We’ve been exploring how A.I. can help our customers improve their financial health at the moment. This tool gives our customers insight into how they’re managing their finances, and it’s presented in a way that is personalized and easy to understand.” — Steve Ellis, head of the innovation group at Wells Fargo

Other players in the financial sector are gearing up as well and gradually making inroads into A.I.-driven finance management. That makes perfect sense, as the personal finance management niche has long been ignored both by traditional and digital banks.

Why PFC will become part of the digital banking experience

The FinTech sector has gone through several evolutions. Initially, a lot of market entrants chose the unbundling route to position themselves as a simpler, more effective, and UX-friendly alternative to clunky traditional banking products.

However, as customer bases mature, digital players are now scaling their offerings to meet the needs of a wider range of customers. They must avoid the most common mistake among incumbent banks — making product development decisions based on internal assumptions, rather than actual customer demands.

Here’s the deal: Most customers do not want more financial products per se — they want better guidance and stronger alignment between their day-to-day needs and the financial products at their disposal.

Introducing A.I.-powered financial planning functionality can help banks and app makers accomplish two things at once:

  • Delight customers with a handy and helpful feature
  • Collect a huge stream of new insights that can guide future product development

By knowing exactly where most of your users stand financially, they can:

  • Develop more targeted personalized offers
  • Devise next-best-action strategies
  • Add new in-demand integrations to their banking marketplace
  • Collect additional information for data-driven products such as automated lending, loan refinancing, and automated investing

In fact, unique PFC functionality can be primary value offering, as several digital banks have already done:

  • Bankin’ (France) puts a strong emphasis on its personal financial management and algorithmic coaching functionality.
  • Moven (U.S.) recently patented its advanced PFC tech and now offers it as a white-label solution.
  • Chime (U.S.) offers automated savings features and recently introduced a no-fee overdraft alternative for users who need some extra cash between paychecks.

Financial planning and wealth management has long been the turf of incumbent banks. Mostly because access to financial planning services was reserved for high-net-worth individuals.

New technologies (A.I., ML, and big data analytics) are commoditizing access to financial advice. Today, a personal financial coach is no longer a trained person armed with a calculator and loads of spreadsheets; it’s an algorithm capable of accessing an array of data sources and making real-time suggestions to millions of customers simultaneously.

Author: Anna Oleksyuk, FinTech Enthusiast at, looking beyond the hype in the adoption of the new technologies.

Read the original article here.

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