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Is Your AI Model Actionable?

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Alkami Appoints Deep Varma as Chief Technology Officer

It feels like everywhere you look these days, you see companies of all types leveraging advances in machine learning, natural language processing, and other forms of artificial intelligence. Through this increasingly trending technology, they provide relevant and instant recommendations to consumers.

From Amazon to Netflix to the majority of online shopping merchants, firms are using AI modeling to enhance the customer experience. Consumers appreciate the use of data to personalize their entertainment experiences and online shopping journeys. It’s no different with their banking products and services.

The idea of financial institutions using their account holders’s product adoption and utilization data, along with other financial spend patterns and lifestyle insights, to identify cross sell opportunities is fundamentally no different from any of the other services consumers use on a daily basis.

Consumers now accept that their data will be collected, analyzed and used to enhance the quality of their service. In fact, they expect it.

Data is the Most Powerful Tool in a Marketer’s Toolbox

With access to data insights that are meaningful, actionable, and that uniquely describe account holders’ financial patterns and lifestyles – personalized, relevant engagements and experiences can be delivered.

Large banks with significant resources are beginning to use the same type of sophisticated data analytics services that Netflix and Amazon are using. In banking, AI models can be built leveraging product adoption, utilization and transaction data to fuel account holder retention, risk mitigation and needs-based cross-selling programs.

A blog recently published by a colleague titled, The Many Hats of a Bank Marketer: 5 Tips to Stay Focused, stated that marketers should utilize both technology and data to target consumers. It points out that “research has found that brands that have adopted artificial intelligence (AI) for marketing strategy have seen a 37% reduction in costs along with a 39% increase in revenue.” Effective targeting creates less waste.

Community financial institutions that have traditionally lagged in using data analytics, can no longer leave it to the big players. Now is the time to get started.2 Shouldn’t every marketer have AI in their toolbox?

Future-Proof Your FI

Technologies driven by data have incredible power to transform our lives and impact the decisions we make every day. Financial institutions that embrace the use of data to predict future behaviors and personalize account holder experiences will result in more intelligent, more customer-centric and more timely engagement and communication. This will build a level of trust, and ultimately a more profitable institution.

The right AI predictive models dig deep into the Financial Institution’s (FI’s) full universe of account holder data and analyze singular moments of their account holders’ lives, the transactions they process, their utilization of products, and their financial patterns. These insights can then be leveraged to predict future behaviors and to identify patterns that make marketing messages more relevant. The uniqueness of the transaction data – such as identifying customers making micro-deposits to a robo-advisor, or an increase in car insurance payments – combined with product data is the predictive modeling approach FI’s need now.

Mobilize Your AI

Ideally, an AI predictive modeling solution should always be deployed alongside a full suite of account holder insights, providing context to predictive model results and informing engagement opportunities that drive consumer change behavior.

Predictive model results are limited in their scope of effectiveness if additional insights are not also available to make the results actionable. For instance:

➜ How can you deepen your relationship and win back the business of your account holders who are likely to churn if you don’t know their current patterns of behaviors with your products or their activity with competing institutions?

➜ Identifying account holders who are likely to open a HELOC but not understanding their lifestyles so you can deliver relevant engagements describing how these funds can help them achieve their dreams, may cost you marketing dollars because your message will disappear into the white noise of the advertising all around them.

➜ When reaching out to your accounts that are likely to open a Money Market, it’s important to understand not only their deposit balances with you but also their transfers to held-away investment accounts and holistic borrowing activity with you and competing institutions. Communicating that your goal is their overall financial well-being is a foundation to building trust in your account relationships.

AI + Humanity

In the last two years, those consumers who trust their FI to look after their long-term financial well-being has dropped 14 points to 43 percent 3. But all is not lost.

By infusing humanity and personalization into account holder outreach, married with predictive modeling results, financial institutions have an opportunity to forge strong account holder connections, build trust, and, ultimately, drive growth. A key to improving this trust, will be injecting humanity through a “digital brand personality” and embedding personalized experiences in digital account holder journeys at the moments that matter.

With a full universe of insights and AI modeling, financial institutions can deliver optimal experiences to the right account holders through the right channels, driving growth and improving client satisfaction. Leading to increased likeliness of account holders’ financial well being, expanded share-of-wallet, and most importantly – increased institutional profits.


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