By Xav Harrigin

The dawn of the digital age, marked by the rapid proliferation of electronic devices and the omnipresent influence of the internet, has reshaped industries across the board. The banking sector, long regarded as a pillar of stability and tradition, finds itself amidst a transformative whirlwind. Micronotes emerges as a beacon in this change, introducing its cutting-edge recommender engine to navigate these uncharted waters.

Deciphering the Data Deluge and the Advent of Personalized Banking

In the intricate web of modern banking, institutions grapple daily with a deluge of data. Every deposit made, every transaction processed, and each loan application submitted paints a vivid picture of a customer’s financial journey. Micronotes’ recommender engine, harnessing the power of AI-driven technology, delves deep into these data narratives. It ensures that banks transition from mere reactive strategies to proactive, forward-thinking approaches. Parallel to this, the banking sector has witnessed a metamorphosis from generic service offerings to a more nuanced, financially personalized model. Taking cues from platforms like Netflix, which has mastered the art of personalization, Micronotes’ engine dives into a customer’s financial history, crafting tailored product suggestions. This evolution from broad-based to individual-centric banking is a cornerstone in enhancing customer loyalty and overall satisfaction.

Predictive Analysis and Engagement in the Digital Age

The capabilities of Micronotes’ recommender engine extend beyond simple product recommendations. It ventures into the realm of predictive analysis, identifying patterns and potential trends. Such insights allow it to anticipate financial challenges or even predict customer attrition, enabling banks to intervene with timely solutions, thereby strengthening their customer bonds.

In today’s digital-first world, the dynamics of customer engagement have undergone a significant overhaul. The once-dominant banner ads, which were the go-to strategy for online promotions, are now seeing waning effectiveness. Micronotes’ engine, emphasizing authentic engagement and boasting game-changing click-through rates, paves the way for banks to foster meaningful, in-depth conversations with their customers.

Unearthing Camouflaged Opportunities

Amidst the vast expanse of data lie hidden opportunities, waiting to be discovered. Micronotes’ recommender engine stands out for its adeptness in pinpointing these concealed gems. Through strategic interactions, it empowers banks to present bespoke solutions, ensuring optimal growth without burdening operational resources.

Versatility: The Hallmark of Modern Banking

The modern banking landscape demands adaptability and versatility, and Micronotes’ recommender engine epitomizes these traits. Whether it’s driving loan growth, championing deposit retention, or amplifying the reach of new digital products, its multifaceted applications highlight its critical role in the contemporary banking ecosystem.

Conclusion

Micronotes, through its pioneering recommender engine, is not just unveiling a groundbreaking product; it’s signaling the dawn of a new era in banking. In a world where data reigns supreme, this engine equips banks with the tools they need to adeptly navigate the complexities of the digital age, ensuring they deliver unmatched customer experiences.

By Xav Harrigin

The Independent Community Bankers of America (ICBA) ThinkTECH Accelerator Demo Day is a nationally acclaimed program that promotes early-stage solutions designed specifically for community banks. The program is known for its commitment to fostering innovation in the banking industry, connecting the most innovative fintech companies with community bankers and industry leaders. At a recent Demo Day, Parker Steed, VP of Sales at Micronotes, delivered a compelling pitch that showcased the company’s innovative, AI-enabled, cloud-based marketing automation solutions for financial institutions (https://www.youtube.com/watch?v=Y_Mt84zq0qI, starts at 39:32).

Steed began the pitch by reflecting on the evolution of banking from in-person branch visits to digital interactions. He shared a personal anecdote about how banking has changed over the years, highlighting the importance of Micronotes’ mission to help community banks maintain strong connections with their customers in an increasingly digital world. He then emphasized the importance of emulating the traditional branch conversations in online and mobile banking environments, a feat made possible by Micronotes.ai’s cutting-edge technology.

Micronotes.ai, based in Boston, serves about 140 community banks in the U.S. The company’s growth has been supported by a distribution relationship with Fiserv and investments from Experian Ventures, TTVCapital, and most recently, Bank Tech Ventures. Being part of the ThinkTECH Accelerator has further enabled Micronotes.ai to connect community banks with their customers using big data, advanced analytics, and engagement technologies.

Steed’s pitch focused on two key areas: deposits and loans. He explained how Micronotes.ai’s technology identifies opportunities for exceptional deposits and initiates conversations with customers to retain those deposits. The company’s AI-driven marketing automation also helps banks predict customer behaviors such as delinquency and attrition, enabling banks to proactively offer solutions like overdraft protection products and retention strategies.

The Micronotes.ai solution goes beyond traditional banner ads in online and mobile banking. It offers 26X the click-through rate (CTR) of banners, more engagement, and most importantly, it starts conversations that enable banks to learn from and about their customers. This approach helps to keep the “community” in community banking.

Steed also highlighted how Micronotes.ai can help uncover “camouflaged small businesses” through the retail banking side of a bank. By identifying these businesses, banks can cross-sell products like small business credit cards or loans without increasing headcount.

The pitch concluded with a demonstration of how Micronotes.ai uses Experian credit data to identify creditworthy customers and find meaningful savings if they were to consolidate their loans with the bank. This personalized approach not only enhances customer experience but also helps banks retain and grow their customer base.

In a world where customers are constantly bombarded by ads from competitors and large fintechs, Micronotes.ai offers a solution that keeps community banks competitive and connected with their customers. It’s not just about retaining and growing deposits or booking better loans; it’s about starting meaningful conversations, developing relationships, and building trust.

Micronotes.ai is revolutionizing the way community banks engage with their customers. By leveraging big data, AI and machine learning, the company is helping banks to better understand their customers, predict their needs, and offer personalized financial solutions. The result is a win-win situation: customers feel understood and valued, while banks increase their revenue and deepen their customer relationships.

If you’re a community bank looking to take your data and make it actionable, Micronotes.ai is ready to help. As Parker Steed concluded in his pitch, “If you need to retain and grow deposits or book better loans, give us a call, we’d be happy to help.”

In the previous deposits-focused article, we discussed how to detect and immediately act on anomaly deposits to keep those deposits from exiting the financial institution’s balance sheet.  In this article, we’ll discuss asking existing customers/members for deposits held elsewhere, programmatically, because that’s always the first order of business.

The most obvious sources of deposits held elsewhere by existing customers/members are the direct deposits being made by your customers/members to other institutions.  The financial institutions we serve have typically established a direct deposit relationship with fewer than 25% of their total customer/member base, leaving a lot of room for growth.   The lack of a direct deposit relationship with so many customers/members reduces the deposit base and increases attrition.  For example, past attrition studies we have published demonstrate that holding all other variables constant, a customer with direct deposit has 0.42 times the odds of leaving the financial institution versus a customer/member without direct deposit*.   For example, if the odds of attrition of a customer without direct deposit averages 10%, the odds of attrition of a customer with direct deposit average 4.2%.  This metric won’t surprise anyone in retail banking, the direct deposit relationship is king**!

So, a simple way to improve both deposits and retention is to programmatically ask your customers/members without direct deposit to establish direct deposit with you like this (this particular example is for loan customers):

Figure 1

The “other” button enables the user to describe exactly what it would take, sometimes surprisingly!

Figure 2

Summarily, use technology to ask your customers what it would take to move their direct deposit relationship, then get the direct deposit relationship to increase deposits and cut attrition risk.  You’ll probably be the only financial institution that ever asked.

In our next installment, we’ll talk about how to:

• Attract customers who can make large deposits.

*Study of 779 customers lost over 2 months out of a total of 67,424 customers total), 283 of which were deemed “profitable.” by the bank.

** “Holding all other variables constant, each additional e-service (e.g. bill-pay, debit card, e-statements) a customer takes multiplies the odds of churn by 0.73.”

By Devon Kinkead

As Ron Shevlin of Cornerstone Advisors likes to say, checking accounts have become “paycheck motels” – that is, temporary places for people’s money to stay before it moves on to bigger and better places.

Given the all-out war for deposits right now by competing financial institutions, we see this temporary cash housing problem as a serious but preventable threat to the financial well-being of our client financial institutions and their respective customers and members.

Nothing New to Micronotes

We’ve been helping financial institutions increase deposits for years using our proprietary microinterview engagement technology targeted by machine learning.

Quoting Tom Novak, VP and Chief Digital Officer of Visions Federal Credit Union in a 2021 Q2 case study, “…Micronotes is a conversational AI tool, digital marketing tool, where we use machine learning on the backend to more effectively target and curate offers and messages to our digital banking members. One of the best outcomes we experienced a couple years ago, before COVID hit, was when we were in a little bit of a liquidity crunch. We needed to tell our members that we had great deposit rates, and that they could bring those deposits to us and we’d reward them with nationally leading interest rates – or dividend rates, as we call them on the credit union side.  We developed that through Q2’s SDK (software development kit), which is part of the Innovation Studio. It let us curate those messages and integrate them into the digital experience. In a few short months, we brought in over $8 million in deposits, retaining those deposits on our books.”

Our strategy for increasing deposits for our clients is:

1. Hold on to the deposits you have!
2. Ask for deposits held elsewhere, programmatically.
3. Attract customers who can make large deposits.

Watching Deposits Check-Out

How often has a customer or member parked a large sum of money in her checking or savings account while deciding what to do with it next? Did the banking institution reach out to discuss investment or new mortgage options for that big deposit? Probably not.

So what happened next? She probably moved the money elsewhere and 3 months later saw a billboard advertising great CD rates from her banking provider; too little, too late, and way too slow.

A better strategy is to detect deviations from an average account balance, deploy Micronotes and start a mobile or online banking conversation with your customer/member about investment opportunities and/or new mortgage/loan options; with a personal approach.

For example, look at these 10 real checking account balances that are 1-2 months apart (table 1):

Table 1

These 10 accounts all show anomalies given the balances at time 3, which are all North of ten times the average balance over the previous two periods.   Given the net interest margin advantage of having large deposits sitting in low-yield accounts, the risk of losing the deposit is now the key question.

The risk of losing an anomaly deposit can be computed by looking at anomaly deposits that exited the balance sheet within 30 days of the deposit and is a value from 0-1, 1 being 100% probability that the deposit will exit the financial institution balance sheet in the next 30 days.

However, this computation is unnecessary because the anomaly deposit represents a low-cost automated opportunity to learn about the large depositor’s life and needs. For example, a personalized microinterview with the mobile banking customer can be automatically triggered to uncover important information as shown below in Figure 1.

Figure 1

From this one question, we use branch and skip logic to pinpoint the depositor’s situation and needs and direct her to the right banker for options to retain the deposit.

The application of this simple method of detecting anomaly deposits, triggering a discovery conversation in mobile/online banking to understand context and intention, and connecting that customer to the right banker in your organization is a simple but powerful way to reduce the probability that your financial institution becomes a large deposit motel where deposits check-out at noon.

In the next installment, we’ll go through how to:

• Ask for deposits held elsewhere programmatically
• Attract customers who can make large deposits.

It’s time for retail banks and credit unions to apply “teaser rate” thinking to refinance more customer/member loans held elsewhere in a manner fully consistent with Fair Lending Laws. Offering attractive refinancing rates to acquire more loans customers/members hold elsewhere rewards loyalty by lowering their borrowing costs.  For the financial institution, acquiring more loan assets customers/members hold elsewhere increases assets, reduces attrition risk, and generates goodwill… a powerful trio.

Increasing Refinancing Pool Size

All else being equal, the lower the rate, the more likely a given pool of creditworthy customers will qualify for savings from refinancing debt held elsewhere.  Here’s an example from a recent campaign and the impact of rate on a single prescreen auto loan refinancing campaign.

[table id=1 /]

Prescreen loan offer volume can increase by up to 40% by lowering refinancing rates by 75 bps.  While profit per loan will diminish, the net new loans will always add revenue and reduce customer churn.

Retention

All else being equal, the odds of bank customer attrition are multiplied by about 0.42 with a direct deposit relationship and 0.73 with each additional product or service added.  For example, suppose the odds of attrition are 1% per month for the overall customer base. In that case, the odds of attrition for direct deposit customers is 0.42 x 1% or 0.42% and correspondingly 0.73% for customers with one additional service compared to the average customer, who may have 2 products.  And these attrition risk multipliers are cumulative. “If a customer adds both direct deposit and an additional loan, holding all other variables constant, her risk of attrition is now 1% x 0.42 x 0.73 = 0.31%, or one-third the attrition risk of the average customer.” says Devon Kinkead, CEO, and Founder of Micronotes. “Aggressive refinancing rates increase the odds of underwriting more loans and reduce the risk of churn for creditworthy customers. That’s smart business when the competition is intensifying efforts to get your creditworthy customers’ loan business.”

Goodwill

Micronotes’ AI-driven engagement and cross-sell solutions combine machine learning with the closing power of sales interviews to turn the digital banking channels into revenue generators. Imagine the goodwill created by systematically finding and lowering your customers’ borrowing costs. For example, a happy and energized customer who just saved $70/mo refinancing a loan with your bank can automatically be encouraged to write a review on social media, driving more new customer acquisition.

Summarily, aggressive refinancing rates should be part of any prescreen campaign to find and refinance mispriced loans held elsewhere. As total prescreen loan offer volume increases, more loans are written generating more revenue, more assets, reducing churn, and creating goodwill. It’s time to sharpen the pencil and get aggressive for everyone’s benefit.