Neocova Helps Community Banks Unlock Millions in Revenue Opportunities with MongoDB and AWS

Without the IT resources needed to generate insights from their data, many community banks miss out on revenue opportunities that would help them compete with larger institutions. Fintech startup Neocova helps these banks find potential revenue opportunities from existing customers by modernizing their approach to data and data accessibility. Built on MongoDB Atlas and powered by Amazon Web Services (AWS), Neocova’s solution transforms and enriches bank data, allowing banks to match customer intent with highly targeted cross-selling strategies. Thanks to the integration between AWS and MongoDB and the support of both teams, Neocova can deliver its solution in minutes, empowering banks to unlock millions in new revenue.

Woven into the fabric of their local economies, community banks provide critical banking services that help small businesses and area residents prosper. Representing about 95 percent of all banks in the United States, community banks typically hold less than $10 billion in assets. While their small size and local focus help them meet the needs of their communities, they often lack the information technology resources required to compete with major regional or national operators.

Neocova, a fintech startup based in Austin, Texas, saw an opportunity to help community banks by modernizing their approach to data and data accessibility. By unlocking insights buried in what Matt Almeida, vice president of engineering at Neocova, calls “messy data,” these banks can identify revenue opportunities that would otherwise be missed.

From the beginning, Neocova built its solution on MongoDB Atlas, a developer data platform from AWS Partner MongoDB. Atlas offers an integrated suite of cloud database and data services that accelerate and simplify how users build with data. Using MongoDB Atlas, Neocova can take a community bank’s data from Excel spreadsheets or legacy applications, transform it into a single unified language, store it, and create an application layer. This application layer can then be plugged into both the bank’s own CRM system and other third-party tools, making it easier to derive insights from all kinds of data.

“One of the reasons we chose MongoDB was the simplicity of integrating the platform with AWS infrastructure,” explained Almeida. “We needed a well-resuméd cloud architect to help us build out a bank-level professional service, and the maturity and cleanliness of the integration was impressive. What AWS and MongoDB Atlas offered together made it a very easy decision.”

Neocova also uses MongoDB Compass, MongoDB’s graphical user interface (GUI), to make it easy to switch between clusters, build aggregate queries, and interact with data. “That’s something you don’t get with other NoSQL solutions,” said Almeida. “Our developers can churn through data and query analysis significantly faster with this than with any other tool they’ve tried.”

Neocova deploys and manages its containerized services on Amazon Elastic Container Service (Amazon ECS) clusters using both AWS Fargate serverless compute and Amazon Elastic Cloud Compute (Amazon EC2) instances. The company connects this to each customer’s unique Atlas cluster with a VPC Link integration to ensure the connection is as private as possible. Neocova also uses Amazon Simple Storage Service (Amazon S3) that rotates into Glacier and Amazon Relational Database Service (Amazon RDS) to handle other data storage concerns. To monitor AWS resources and applications, Neocova relies on Amazon CloudWatch and AWS CloudTrail.

Because banks must meet SOC 2 compliance requirements for client data management, each customer has a separate, dedicated instance of Neocova’s solution. MongoDB’s security features support the data isolation and privacy protections bank customers expect. In addition, Neocova uses AWS Identity and Access Management (IAM) and AWS Key Management Service (AWS KMS) as the basis of its right-sized approach to security, which includes following the principle of least privileged access. The company also leverages Amazon GuardDuty to monitor operational data and Amazon Inspector to scan workflows for any vulnerabilities to support SOC 2 compliance efforts.

Almeida and Matt Beecher, CEO at Neocova, pointed to the assistance the team received from both MongoDB and AWS as critical to the success of their solution. “I can’t overstate the support MongoDB provided. They’ve been phenomenal in every aspect,” said Almeida.

Beecher added, “Our work with AWS has been an incredible partnership. They inspired a lot of design thinking into how we run our infrastructure that ensures we can manage costs without compromising effectiveness.” In particular, Beecher noted the value of the AWS Migration Acceleration Program (MAP) in helping the company reduce IT spend and improve usage efficiency.

The templated MongoDB-AWS solution slashes time to delivery from days to what Almeida called “a blink of the eye.” The speed of delivery means that Neocova’s data team can spend its time developing new value-added features rather than managing complex deployments. “We wanted to make sure everything was well templated so that it’s simple to link with the customer’s virtual private cloud (VPC) and quick to get started, and Atlas and AWS make that possible,” Almeida added.

In addition, the solution’s flexible architecture will allow Neocova to easily add artificial intelligence and machine learning (AI/ML) capabilities as the company grows. “We have some exciting irons in the fire here,” said Almeida. “For example, we’re looking at developing an attrition model that tells banks when a customer is at a high risk of closing their account or going to another institution. We’re also looking at a next-best-product model that suggests new ways to cross-sell to existing customers.”

Neocova’s solution has empowered its customers to find new revenue opportunities in old data. Beecher cited an example of a bank that discovered it was missing out on $5 million a year in revenue from lost merchant fees going to third-party providers.

Other customers have used newfound insights to offer corporate credit cards and other products that represent potential future revenue streams. Still others are winning back commercial debt held by account holders in other banks—in one case, commercial loans in excess of $250 million.

For one of its first customers, the Neocova team completed a proof of concept that found opportunities of more than $373 million in consumer refinancing, $24 million in corporate insurance, and nearly $160 million in credit card payments. “When you translate those numbers, you’re talking about the potential for $10 million a year in additional revenue for that bank,” said Beecher. “That’s a 20 percent lift, which for any bank is really significant.”

Going forward, the Neocova team is exploring how distributed data mesh architecture could be used to deliver what Beecher called “an archipelago of new products” that support different use cases. These products would “allow banks to choose their own adventure” when it comes to connecting with the solutions they find most valuable.

“We want to redesign our data architecture to be future-facing and able to scale,” concluded Almeida. “We know AWS and MongoDB can definitely help us get there.”