Competing for the millennial financial services market with category outsiders

How banks can leverage AI to deliver 1:1 interactions at scale

The kids are alright. Unless, of course, you’re in financial services marketing.

In 2016, The Economist reported that 61 percent of banking executives believe their biggest competition will come from outside of the industry.

So, what do these industry outsiders look like? Well, they look a lot like Mark Zuckerberg, Jeff Bezos and Jack Ma.

One in three banking and insurance customers globally would consider switching their accounts to Google, Amazon, or Facebook if the Silicon Valley-based companies offered financial services, according to a new 2017 survey.

Google, for example, launched Android Pay and Google Wallet, which allow consumers to send, receive, and request money. In addition, Google Finance also offers some online portfolio tools that could eventually expand to displace traditional brokerages.

In a non-retail play for consumer marketshare, Amazon partnered with Wells Fargo in 2016 to offer discounted student loans to Amazon Prime customers. They’ve also been active in direct loans through Amazon Loans and payments via Amazon Payments. In addition, Amazon Web Services (AWS) played a large role in migrating heavily regulated banks data to cloud infrastructure, which could accelerate further partnerships. Recently, Amazon announced its new Prime card, a Visa card with no annual or foreign transaction fees, standard interest and a whopping 5% cash back on Amazon purchases. It will undoubtedly come with other Amazon Prime benefits further strengthening Amazon’s relationship with its customers.

Note, even the whole notion of what is retail and was is non retail is blurring with the acquisition of Whole Foods by Amazon for $13.7B and their ability to leverage Whole Foods 460+ retail locations. Banks, as a specific sector if financial services, who have always viewed local branches and ATMs as a competitive advantage over these digital upstarts, had better wake up and smell the coffee.

However, if you’re wondering what true expansion by a tech giant into financial services actually looks like, one only has to look to China for a case study in tech financial services disruption. In 2015, Alibaba launched their all-digital bank, MYbank, which has grown to more than 450 million annual active users. The Wall Street Journal reported that 58 percent of online payments in China use Alipay, the bank’s payment service.

Meanwhile, two other major Chinese tech companies, Tencent and Baidu, both launched banks of their own over the past two years. Tencent, the company behind the ubiquitous WeChat social media app in China, launched WeBank. Baidu, the online search giant, partnered with a traditional bank to offer both online and offline services.

Alibaba’s capital lending arm is an optimal example of what the future of retail banking could look like. There’s no staff involved. Data algorithms calculate loan amounts and the application and approval process happen online—in minutes.

So what can today’s financial services companies do to avoid extinction via technology sector disruptors?

Beat them at their own game

Facebook, Google, and Amazon don’t have the market cornered on advanced algorithms and 1:1 consumer interactions at scale. Today’s financial services CMO’s have already adopted technology at a breakneck pace across the entire marketing and data ecosystem.

With all of this data and marketing infrastructure in place, financial services marketers stand to gain heavy ROI lift through implementing an artificial intelligence marketing (AIM) platform that continuously optimize every customer interaction across every channel based on the wealth behavioral and profile data already available.

Avoid churn—early.

Traditional churn models are like smoke detectors—they’re good at letting you know when yo­u building is already on fire.

The challenge for financial service marketers lies in making sure this information is surfaced and acted upon in a timely manner to anticipate and prevent customer disengagement. If you’re trying to prevent churn with customers after they’ve already reached customer service or the unsubscribe page, you’re far less likely to save them than if you’ve intervened earlier in their journey.

It’s also not enough to simply engage in the days leading up churn with a generic turn-around offer. Instead, it’s critical to answer the following questions to guide dynamic retention messaging and experiences:

  • Why is the customer at risk of leaving?
  • Do you have a remedy for it?
  • How likely is the customer to come back?
  • How much will they spend if they come back?
  • How likely are they to stay and for how long?

Don’t get stuck in rules-based marketing or next-best-action systems

The challenge with traditional marketing automation solutions is that they are only as scalable or as intelligent as the marketers running them. While such solutions have shown the ability to automate marketing execution for specific “if/then” scenarios, these solutions fall woefully short when trying to apply them broadly across a large B2C enterprise for three key reasons:

1. In order to get the desired targeting granularity, marketers have to write and maintain dozens of “if/then” rules across hundreds or even thousands of campaigns

2. All of the targeting rules have to be set in advance of ever having run the campaign, so initial success relies solely on the experience and “best guess” capabilities of the marketer configuring the campaign

3. Running A/B/N tests to optimize campaign efficacy remains a very manual, labor-intensive process, often requiring a data scientist to get involved and spend weeks doing uplift or propensity modeling, only to come up with a recommendation for improvement that, while helpful, only positively impacts a small portion of a marketer’s total audience.

As a result of these challenges, marketers spend their time programming campaign rules, managing holdout groups and analyzing test results instead of being strategic or creative. While it is important for today’s marketers to be “data-driven,” the pendulum has swung too far: automated and programmatic campaigns have become so focused on improving short-term opens and clicks that they miss out on optimizing the longer-term ARPU (average revenue per user) and retention KPIs (key performance indicators) that directly impact top line revenue for today’s financial services enterprises.

Remember: You’re the adult here.

Your kids ARE alright because you know financial services. You have the domain expertise to manage the interests of customers, financial markets, government regulation, and all the complexities of the financial service industry. What you need to do is take that knowledge and be bold and leverage the assets you have in ways you never thought possible.

Much like parenting, that requires you constantly nurture and each your kids new things so they grow so they can evolve from crawling to walking to running, financial services, now more than ever, need to do the same. Yes the kids are alright, but only for financial services institutions are bold enough to take the next step into AI marketing.

To learn more about how banks are leveraging artificial intelligence to optimize the entire customer experience, download the 2018 AI Marketing Guide: Addressing Banking's Digital Debt.

About Glenn Pingul

Glenn Pingul is VP of Scientific Marketing Strategies for Amplero, an Artificial Intelligence Marketing (AIM) platform that helps enterprises better connect with their customers. Prior to joining Amplero, he was a co-founder of the online video advertising ad tech company, Mixpo, where he was VP of marketing.

He has an extensive background developing digital marketing, analytics, and loyalty and retention strategies while serving in executive level positions at T-Mobile USA,, AirTouch Wireless (Verizon Wireless), and The American Express Company.

About Amplero

Headquartered in Seattle, Amplero is an Artificial Intelligence Marketing (AIM) company that enables business-to-consumer (B2C) marketers at global brands to optimize customer lifetime value at a scale that is not humanly possible.

Unlike traditional rules-based marketing automation systems, Amplero's Artificial Intelligence Marketing Platform leverages machine learning and multi-armed bandit experimentation to dynamically test thousands of permutations to adaptively optimize every customer interaction and maximize customer lifetime value and loyalty.

With Amplero, marketers in competitive, customer-obsessed industries like telecom, banking, gaming and consumer tech are currently seeing measurable lift across key performance indicators—including 1-3% incremental growth in customer topline revenue and 3-5x lift in retention rates.

For more information, contact us today or follow us on Twitter.