The data equivalent of “nirvana” might be having affordable access to all the business intelligence you need to predict the optimal experience for an individual member, streamline operations, or solve business problems.
That’s the promise of data analytics, which uses mathematical algorithms to translate information into information and predict future behavior. Credit unions partner with vendors to shorten data development time and leverage solutions that are right for them.
A switch in perspective
Credit unions begin to move into ‘data nirvana’ when they stop looking at data through the rearview mirror that shows where it has already been, says Shazia Manus, director of strategy and business development for AdvantEdge Analysis, a supplier of the CUNA strategic services alliance. Data analysis focuses on looking through the windshield to see what to expect.
Manus says credit unions that engage in this process are transforming their business model by gaining the ability to contextualize and analyze data and information. This allows them to deliver personalized offers to members using a range of digital channels.
It also helps them identify member groups that hold the potential for deeper relationships. One example is finding out that millennials want a simplified route to a mortgage when buying their first home.
“We need to be more far-sighted when delivering experiences through the digital channel,” says Manus. “The only way to do this is to understand the consumer’s journey and their state of mind. Data analysis provides this information.
“We need to be more far-sighted when delivering experiences through the digital channel. “
A CUSO approach
Approaching, a credit union service organization (CUSO), has helped credit unions become data-driven since 2009 and provides a “collaborative analytics ecosystem” to credit unions with assets ranging from $ 40 million at over $ 4 billion, says Austin J. Wentzlaff, vice president, business development.
“A lot of the credit unions are trying to solve the same problems,” he says. CUSO’s approach minimizes the need to “reinvent the wheel” over and over in each case. This means that credit unions shouldn’t have to create the same integrations, reports, and models as their peers.
“The credit union community that works together has exponentially more resources than a single organization,” says Wentzlaff. “The OnApproach ecosystem aims to facilitate simplified collaboration around analytics to make credit unions, as a whole, more competitive in today’s financial services industry. “
Costs vary depending on the size. A credit union with assets of $ 500 million to $ 1 billion can start using data analytics through OnApproach for an initial base fee of $ 130,000 plus an annual fee of $ 40,000. These fees cover predefined reports and dashboards, as well as the installation of predefined forecasting tools and predictive models.
“This is a major breakthrough over traditional methods of data warehousing, which would require credit unions to spend $ 1-3 million over several years in hopes of building an isolated system that would then have to be maintained by the credit union, ”Wentzlaff said. .
Providing an industry-standard scalable platform allows OnApproach to reduce the time to implement a credit union to three months, says Wentzlaff. At the same time, credit unions need to understand what they want to do with data and change the culture for employees to use it.
“If you don’t have the culture that accepts data-driven decision making and accepts that data is part of everything we do, the technology will be harder to embrace,” says Wentzlaff.
Credit unions that overcome this barrier by gaining buy-in from across the organization are strengthening their data-driven culture with data analytics that are becoming ubiquitous throughout the organization, he says.
Overcome “disparate systems”
Ideal savings fund in Woodbury, Minn., began investing in data analytics to overcome the barriers of disparate systems that would otherwise keep information about its 50,000 members in separate silos.
“We wanted a solution where we could combine all of these disparate systems into one data warehouse for reporting and data analysis,” says Dennis R. Bauer, executive vice president / CFO of 730 Credit Union. millions of dollars.
A data warehouse would have been “prohibitively expensive” both in terms of tools and talent if the credit union had tackled the project on its own, says Bauer. Once the data was accessible, Bauer had an “oh wow” moment when he started using OnApproach’s analytics software to analyze member behavior.
Ideal began investing in third-party solutions that leverage its data warehouse to collect information and generate reports that help turn information into action. Examples include:
- Giving members the opportunity to reduce their loan payments with CU RateReset, a CUNA strategic service alliance provider. Bauer says most members are eligible for the online service, which allows them to use a seamless connection from the credit union’s website to choose a loan and enter into a simple refinance deal that extends the term of the loan in order to to reduce their payment. Data analysis identifies eligible members for personalized loan offers, meaning no credit checks are required.
- Allowing branches to track referrals via Raddon’s “Lead Builder” solution. Staff can use OnApproach’s M360 solution to monitor their incentives based on current benchmarks.
- Using BankBI’s cloud-based solution enables the credit union to review financial information, brand and product production from any device, anytime, anywhere at a summary level or explore specific branches and / or products.
- Using a solution from 2020 Analytics, a CUNA strategic service alliance provider, to comply with the Change in Current Expected Credit Loss (CECL) accounting rule governing the calculation of loan losses.
- Development loan or deposit marketing campaigns based on member transaction information.
Bauer says credit union staff are involved in the use of data analysis, with two team members assigned to data analysis full-time.
Her advice for credit unions just starting a data warehouse project to maximize data analytics? “Take all the data you can, even if you don’t know what to do with it yet. “
3 steps to using data analysis
- Organize your data through a data warehouse that collects information from multiple systems, including vendors.
- Translate data into meaningful reports using data analysis software.
- Execute by turning data insights into action. This could mean solving a business problem, removing friction from operations, or making personalized marketing offers to members.
Source: AdvantEdge Analysis