Credit unions often lag competitors, technologically. Technological needs must be balanced with service, growth, and profit; often, those needs compete with fintechs, compliance, IT security, and ever-changing regulations.
Fortunately, credit unions have access to data—sometimes, that includes data from other credit unions. Yet, having data and leveraging it are two completely different issues.
That’s where data analytics comes in. Data can provide insights, drive efficiency, solve specific problems, and power digital transformation. If your credit union is getting into data analytics—or switching providers—this post is for you.
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Data Analytics Trends and Insights
1. Why credit unions need data analytics providers.
From checking and savings account data to mortgages, auto loans, HELOCs, credit cards, and insurance… and email correspondence, branch visits, social media comments, call center disputes… member survey data, geographical location, demographics, credit scores…
At some point, it’s best to understand who your members are, what they want, and what they’re eligible for. You’ll learn who’s at risk of leaving, who wants a better credit card, and who’s eligible for a mortgage refinance.
Operations, marketing, HR, lending, and other departments can all use this information to create a better, more engaging, more relevant, and more rewarding member experience.
But to make positive changes, they need that information. And that information comes from data analytics.
Data analytics providers can help you aggregate, clean up/normalize, store, process, and use your data. They’ll show you what your credit union looks like now, what it will look like on its current trajectory, and even what you should do to change it. And, to make it easy, they’ll give you charts, graphs, and other visualizations and reports to make the data easy to understand and act on.
Decisions based on guesswork can get you pretty far—especially if the guesswork is done by a longtime industry professional with a keen eye to the future and the influence of technology. But decisions based on information will always be superior to guesswork.
Data analytics providers will allow your credit union to make informed decisions and transform your credit union, from the internal culture to your roadmap, to the member experience.
2. To warehouse, or not to warehouse?
We’ve separated vendors into two major categories: those that provide a data warehouse (thus offering scalability and a single source of truth), and those that don’t (providing spot solutions with your data).
We think of these as holistic and targeted solutions, respectively. Holistic solutions with a warehouse provide more flexibility for the future—you can build, buy, or borrow spot solutions as needed. Targeted solutions without a warehouse offer more focused guidance for specific strategic concerns. Hybrid approaches are possible!
If your goal is long-term growth, we generally recommend warehouse solutions. Getting the infrastructure, owning your data, and understanding the process is key to developing a data-driven culture. Plus, when you send away for analytics, it gets manipulated and merged, and you lose the source of your data.
One caveat is that we recommend against buying a data warehouse from a company that doesn’t specialize in data warehousing. Sure, it might work and be cheap, but it’ll lack in quality and won’t support your long-term success.
There are also non-warehouse solutions. For smaller credit unions, or those who simply need a few quick answers or solutions, and those who don’t want to develop a data-driven culture, non-warehouse solutions are still a good option. You can get actionable insights with minimal work and often with far less time invested up front.
You may also note that we didn’t include providers such as Amazon, Azure, Google, or Snowflake. Although these solutions are technically superior, they have a few major drawbacks:
- They aren’t designed for financial institutions;
- They don’t have integrations or connections with common third-party tools for credit unions; and
- Most credit unions don’t have the in-house expertise to implement, maintain, and maximize the investment in these solutions.
Lastly, it should be noted that some larger providers with massive product suites may be trickier to integrate with products from other vendors. For example, JHA and Fiserv integrate well with other JHA and Fiserv products.
However, integrations outside of their product suite can be far less straightforward. For this reason, we typically prefer vendors that specialize heavily or exclusively in data analytics and who are dedicated to credit unions.
3. What is “data activation”?
If you’re reading through this guide, you’ve likely encountered the buzz surrounding the transformative concept of data activation. But let’s delve beyond the buzz and explore why data activation has become the cornerstone of success for credit unions leveraging fintech solutions.
If data analytics is the process of turning data into insight, then data activation is the next step that turns the insight into a plan (results not guaranteed).
Data activation is the dynamic process that bridges the gap between insights and action. It’s the secret sauce that transforms your data into actionable strategies, workflows, and initiatives. From powering targeted marketing campaigns to next best product recommendations or ensuring complete referral follow up, data activation empowers credit unions to translate insights into tangible outcomes that help them serve members better and faster, all while increasing revenue.
It’s why you wanted data analytics in the first place.
Why is this shift towards data activation so crucial?
Because in today’s hyper-competitive landscape, time is of the essence. It’s not enough to simply gather data and generate reports. What truly matters is the ability to act swiftly and decisively based on those insights so you can serve members better. Without data activation, credit unions risk being inundated with charts and graphs that offer little more than a snapshot of past performance.
4. Don’t forget your data strategy
Many of the vendors listed here will help you with your data strategy. However, not all of them will be there to guide you from Point A to Point Z.
If you’re working with a more hands-off provider, a solution that doesn’t include other integrated products, or a vendor without a warehouse and/or strategy solution, then do this:
Bring on a data strategy consultant.
That goes double if you’ve decided to go the DIY route.
Many of the vendors above will include data strategy as an add-on service. Their add-on services will be pretty good because those consultants will be familiar with the platform you’ve chosen.
However, we’d also recommend looking for an independent consultant, such as Anne Legg of THRIVE Strategic Services (she literally wrote the book on credit union data analytics strategy). Anne Legg has helped hundreds of credit unions understand and build out mature data analytics programs. She’s also spoken at many of our events, and she is always a hit.
Evaluation Strategies
There are many ways to evaluate data analytics providers. Especially if you’re just starting your data analytics journey, your first step should be to figure out what you want to accomplish with analytics.
Simply using data-driven technology isn’t a goal in and of itself—rather, goals are things like improving interchange income, increasing auto loan portfolio size, and reducing attrition.
You’ll need to figure out what kind of projects you plan to augment with analytics. Knowing your goals will help you choose the tools best for achieving them.
In the past, we ranked data analytics vendors by 3 different variables:
- Data sophistication
- Normalization and composability
- Descriptive, predictive, and prescriptive abilities
- Connections and integrations
- Support
- Training, support, or management
- Access to existing models
- Credit union focus and understanding
- Ease of use
- Time to deploy and gain insight
- UX/UI and ease of use
- Visualization and reporting
We have a more extensive exploration of the above in another section (see our Definitions and Explanations section).
However, most data analytics providers you’ll find are quite adept at all of the above. We’d rather leave it to you and your data team to quantify the specifics of each vendor.
In light of that, we encourage you to think about the entirety of the provider’s data analytics solution. You might be buying just a piece of the puzzle, or you could find yourself with the puzzle, the table, and a partner to complete it.
Rather than diving into data sophistication, support, and ease of use, we want to provide some evaluation questions and considerations that may help you narrow down the field to find the best fit partner.
Evaluation Questions to Ask Data Analytics Providers
Not all data analytics providers offer the same services, nor do they deliver their solutions in the same way. As open-ended as data analytics can be (in that they are often platforms that allow credit unions to learn various things, limited only by creativity and need), there are nevertheless significant differences between providers.
Consequently, you may want to ask potential providers some of the following questions to see whether their responses fit your needs.
Information access
Once it’s in their warehouse/lake, many providers effectively own your data and will charge you for access to it. What is the provider’s access policy? What do they charge?
Support and training
Does the provider offer any support or training? Can they provide a fractional data team for you if you don’t have the right personnel at your credit union?
Real-time capabilities
How long does it take to do anything with your data? Do you have access to real-time data or are you always working with historical data?
What isn’t included?
Your data analytics platform is one piece of your total data strategy and ecosystem. Are you purchasing your data analytics platform a la carte, or are you looking for a more holistic solution? What other peripheral tools, products, services, or solutions will you need to include in your data analytics purchase? Is there support for indirect lending? A CRM? SEG or onboarding management? Compliance? Does it take you all the way to data activation, or does it stop just short?
Total cost of ownership
Does the price reflect service storage costs? Data access? FTEs to support its use? Additional products or services you’ll need to accomplish your data goals?
The Data Analytics Provider Scoring Guide
CU 2.0 scores fintechs and providers based on what we believe are the 4 pillars of the credit union ecosystem:
- Income statement: (1) Non-interest income and/or deposits, (2) interest income, (3) both
- Balance sheet: (1) Deposits, (2) loans, (3) both
- Member impact: By members affected: (1) 1–33%, (2) 33 – 66%, (3) 66–100% and/or memberization
- Employee impact: (1) Improves workflows, (2) automates some, (3) automates a lot
We score each pillar on a scale of 1–3, although you may see the occasional 0 or N/A when we think it’s appropriate. Additionally, in some guides (like this one), most of the providers will have very similar scores.
Our ratings don’t necessarily correlate to quality, nor do they suggest which solution is best for you. Fintechs with higher scores aren’t automatically better, or a better fit, for your credit union and members. Additionally, please note that these ratings are estimations based on our understanding of the product or service.
Trusted solutions are highlighted with an asterisk—these are providers that CU 2.0 has vetted or worked with personally.
Data Analytics Vendor Guide (with Warehouse)
| Income | Balance | Member | Employee | Description | |
| Alogent | 3 | 3 | 3 | 2 | Alogent’s AWARE platform provides powerful visualization and reporting to the mix with its focus on business intelligence. |
| Arkatechure Arkalytics* | 3 | 3 | 3 | 2 | Arkalytics is a data analytics platform with a warehouse, data lake, and fully managed services to transform your credit union’s strategy into actionable results. |
| Cinchy* Learn more | 3 | 3 | 3 | 2 | Cinchy isn’t a data warehouse provider—rather, it’s a data activation platform that frees credit union data from silos and enables new, real-time capabilities with data. |
| CU*Answers Asterisk Intelligence | 3 | 3 | 3 | 2 | CU*Answers is a CUSO that provides a host of critical products alongside its Asterisk Intelligence data analytics solution. |
| Datava* Learn more | 3 | 3 | 3 | 3 | Datava is a fully managed end-to-end data activation platform that handles the entire data journey from collection to activation. They focus on delivering insights to front-line staff, often deploying as a CRM, onboarding management tool, referral management, etc. |
| Fiserv iVue | 3 | 3 | 3 | 1 | iVue is Fiserv’s sophisticated data analytics warehouse solution that provides broad data capabilities in conjunction with their other products. |
| Gemineye (formerly The Knowlton Group) | 3 | 3 | 3 | 2 | The Gemineye Lakehouse revolutionizes the relationship credit unions have with data. Their combined data warehouse + lake gives CUs control of their data and their journey. |
| IBM Data Warehouse | 3 | 3 | 3 | 1 | IBM provides world-leading data management solutions with AI capabilities for enterprise-level clients. |
| Jack Henry & Associates | 3 | 3 | 3 | 2 | Technically, Jack Henry & Associates now uses IBM’s data warehouse in conjunction with its own strategy and support team. |
| Lodestar Technologies | 3 | 3 | 3 | 2 | Lodestar Technologies offers a very competitive solution with fantastic visualization and reporting. |
| TIBCO Software | 3 | 3 | 3 | 2 | TIBCO Software is a business intelligence software provider with data analytics solutions for credit unions. |
| Trellance | 3 | 3 | 3 | 2 | Trellance increased their capabilities and support through its acquisition of CU Rise and OnApproach, including their M360 App Store. |
| DIY (do it yourself) | * | * | * | * | The DIY route is the most difficult and expensive solution, but with enough resources, it can also be the best and most well-suited to your specific needs. |
Data Analytics Vendor Guide (No Warehouse)
| Income | Balance | Member | Employee | Description | |
| Altair | 3 | 3 | 3 | 2 | Altair provides data management and analytics solutions to many industries, including credit unions under $100m in assets. |
| Callahan & Associates | 0 | 3 | 0 | 0 | Callahan & Associates includes broader industry data from both banks and credit unions to augment its insights. |
| Crux Analytics* Learn more | 2 | 3 | 1 | 1 | Crux is an analytics platform that allows lenders to quickly, safely and efficiently serve a vetted pipeline of hyper-local small businesses. |
| Deep Future Analytics | 0 | 3 | 0 | 2 | Deep Future Analytics specializes in CECL and loan modeling. |
| nCino | 3 | 3 | 1 | 1 | nCino includes portoflio analytics and advanced business intelligence alongside its larger product suite. |
| Finalytics.AI | 3 | 3 | 3 | 1 | Finalytics.AI offers AI-powered data insights with their platform built specifically for community banks and credit unions. |
| Fiserv Prism | 3 | 3 | 3 | 1 | Fiserv’s Prism is a web-based auxiliary data solution that works well with its other data products. |
| Raddon | 3 | 3 | 3 | 1 | Raddon’s data analytics offering offers a comprehensive suite of services, but in limited quantity as parter of a broader product mix. |
| Temenos | 3 | 3 | 3 | 1 | Temenos includes advanced analytics and AI in its digital banking platform. |
| TerraStrat* Learn more | 3 | 3 | 3 | 2 | TerraStrat provides unparalleled data science as an extension of the credit union’s data and strategy teams. |
| DIY (do it yourself) | * | * | * | The DIY route is the most difficult and expensive solution, but with enough resources, it can also be the best and most well-suited to your specific needs. |
Data Analytics Definitions and Explanations
There are many ways to evaluate data analytics providers. Especially if you’re just starting your data analytics journey, your first step should be to figure out what you want to accomplish with analytics. Simply using data-driven technology isn’t a goal in and of itself—rather, goals are things like improving interchange income, increasing auto loan portfolio size, and reducing attrition.
You’ll need to figure out what kind of projects you plan to augment with analytics. Knowing your goals will help you choose the tools best for achieving them.
We’ve ranked data analytics vendors by 3 different variables:
- Data sophistication
- Normalization and composability
- Descriptive, predictive, and prescriptive abilities
- Connections and integrations
- Support
- Training, support, or management
- Access to existing models
- Credit union focus and understanding
- Ease of use
- Time to deploy and gain insight
- UX/UI and ease of use
- Visualization and reporting
This section goes into detail about the metrics by which we ranked the data analytics criteria above. Our scale measures from 1–3, with 1 meaning “not great,” 2 meaning “average or good,” and 3 meaning “great or market leading.” Scores of 0 are possible, but they likely mean the provider doesn’t provide a critical component of the criteria.
1. Data governance and sophistication
Normalization of data is critical. Essentially, this is the quality and integrity of data. Is it well organized? Is it accurate? Is it accessible? And, is it… extensive?
If you’re going to make data-driven decisions, then you want good data. Think of normalization as the performance of your data.
Composability is also key. In short, this is how easy your data is to work with. If you think of your data as a sandbox of possibilities, you can create more solutions with composable, wet sand than you could with messy, dry sand.
Descriptive, predictive, and prescriptive analytics fit different needs. Descriptive analytics are table stakes—any provider should be able to give you insight about what’s happening with your members and at your credit union. Predictive analytics will help you with issues like CECL. And prescriptive analytics are that cherry on top that tells you what actions to take based on what the data reveals. The ability to handle all three types of analytics is fantastic, but not standard.
Connections and integrations ensure you can use data from multiple sources. If you want to use member survey data, CRM data, and other non-core sources of data, you’ll want a provider that can work with as much of your tech stack as possible.
2. Support
Training, support, and management can be the difference between a vendor you love and a vendor you hate. Does the vendor train you on how to use their solution? Do they provide that training to all staff who need it? Is the training long enough, and is it hands-on or through cumbersome videos and instruction manuals? Are they invested in your success, or do they leave you to your own devices after you cut the check?
Additionally, attentive, ongoing support is a plus. And finally, is the vendor is willing or able to manage your data platform, in whole or in part? It’s rare, but we love the flexibility that provides for credit unions under the $10b mark.
Access to existing models is absolutely necessary. You’ll be better served by a provider that can get you up and running quickly with the solutions you need. Loan origination models, predictive analytics for CECL, marketing segmentations and solutions, KPIs for loan officers…
If every vendor you speak with has existing solutions, make sure they have relevant experience addressing your short- and long-term goals.
Finally, a focus on and understanding of credit unions is key. Many data analytics providers serve a broad range of industries or financial institutions. But credit unions have different cultures, goals, and needs than others—your vendor should be familiar with them.
We prefer vendors that prioritize credit unions, and we particularly appreciate CUSOs over major fintechs that shoehorn data analytics into much larger product suites.
3. Ease of use
Time to deploy and gain actionable insight is a big consideration. Financial technology is evolving rapidly, and machine learning and other AI are accelerating that. The longer it takes to implement a data analytics solution, the further behind your credit union gets.
However, while we give points for speed, it’s not the most critical component here. Solutions without warehouses, training, and thorough onboarding processes will be slower… and won’t be as comprehensive or scalable.
UI/UX and general ease of use are important. Although ongoing training, support, and management can make bad UI/UX or complicated platforms bearable, you’ll get a lot more out of something that looks good and feels intuitive. You’ll also be able to train new employees faster and more effectively.
At the end of the day, it’s better to want to use the platform rather than have to.
Visualization and reporting should not be underrated.
Most people are not data scientists. Instead, they rely on intuitive user interfaces, dashboards, and visuals to understand data. Is the data readable? Is it accessible? Does the readout make sense to the people using it?
Data analytics vendors that report data in intuitive, intelligible, comprehensive ways will make it easier on your team. You’ll spend less time wondering what the numbers mean, and more time deciding what the numbers are saying. And “time” is key here—if you’re running dozens of reports per month, you’ll want that process to be simple and effective as possible (automation and good design can work wonders)!
Conclusion
There are several vendors to compare, here. And we’ve certainly included enough metrics by which to measure their platforms and services.
The first step is to narrow down the list to a few who look promising to your credit union. Then, we recommend finding vendors who hit your criteria and doing further research. It’s important to choose a data analytics vendor who fits your credit union’s needs and project goals. After you’ve narrowed your list, it’s time to do some demos and move forward.
If you want to discuss any of the providers with a 3rd party, CU 2.0 would be happy to share what we know. Book a 30-minute consultation with us at no cost here:
Each quarter, we’ll review and discuss fintechs you’re looking at. We’ll also introduce other fintechs that may be of interest!
