Datawatch introduced Monarch some 30 years ago to solve data problems causing frustration at the time, releasing mainframe print spool data for use in other analytic tasks. Over time, formats evolved but challenges remained. With the arrival of self-service analytics tools, the need for a complementary data preparation solution became recognized.

Ken Tacelli, COO for Datawatch, explained, "There have been multiple iterations of the Monarch product line." About two years ago, the company introduced a new Monarch version, which included the components of the classic Monarch but was simpler to use. "Credit unions look at us because we're easy to deploy."

Datawatch Monarch runs on a Windows desktop, and as soon as a user drops a file or web page onto its canvas, it automatically extracts data into analytics-ready rows and columns. Monarch connects to all major relational and big data, as well as more than 30 other sources. Frequently it obtains important information locked away in existing reports or hard-to-reach resources, eliminating the need to re-key the data.

Earlier this year, Datawatch introduced Monarch Swarm, a web-based, self-service data preparation platform. "I want to build a data marketplace that allows everyone in the organization to come and get the data that we have curated and blessed, but at the same time [allows them to] easily use it and distribute it across their organization," Tacelli maintained.

Monarch, according to Datawatch, prepares data for analysis in a fraction of the time it would take when using spreadsheets and other manually-intensive measures. Through automated and repeatable modeling, credit unions can eliminate errors inherent with manual calculation and input, allowing them to create, distribute and publish thousands of reports internally.

Datawatch can also solve a credit union's data access problem, according to Dylan Tancill, who is in outside/enterprise sales for banking and credit unions for Datawatch. He explained, "Their data often is locked down. Most of the time you're not going to have access to the back-end database of the core because it has records of every financial transaction by the members. A lot of what Monarch does is take hard-to-acquire or messy data and turn it into an analytic asset."

The $743 million, Fairhaven, Mass.-based First Citizens' Federal Credit Union, for example, uses Monarch to crack cold storage reports.

"Anyone you ask in the banking industry will tell you one of their biggest issues with reporting is the format of cold storage reports – their format is not user-friendly, they're not exportable and they're in multiple rows," Maureen Sylvia, vice president of business intelligence for First Citizens', said. She explained auditors want information from cold storage that contains actual, official numbers that credit unions must reconcile, and noted Datawatch's solution simplifies the process of transferring data from cold storage to daily balancing.

"You can eyeball them or go through time-consuming exporting, but something like Monarch will assist us with that," she said. "We feel like we're too far advanced to revert back to eyeballing numbers every day to try and balance."

Jeff Sylva, process excellence consultant for Coastal Outsourced Solutions – a wholly-owned subsidiary of First Citizens', for which the CUSO also provides services – explained the Monarch solution can extract data for all its reconciliation processes. "Many of them boil down to the accounting process. One of the biggest issues with matching operational data with financial data is that operationally it is often in cold reports." He emphasized when the data is there and it is hard to extract, the process becomes very time-consuming.

Jeff Sylva noted just implementing the basic functions of Monarch cut the process from hours to 36 minutes. Then after learning of the solution's full capabilities, the organization was able to cut the process to seven minutes per day.

The $720 million, Montpelier, V.T.-based Vermont State Employees Credit Union historically used Datawatch Monarch for only pin and signature exceptions until about a year ago, when it also discovered more proficiencies. "We knew it was capable and powerful of doing so many other potential things that we were inspired and started creating more models or workspaces for our organization," Vice President of Accounting Kasey Furness said.

Furness pointed out the system is very sophisticated and allows for automation, process streamlining, efficiency and greater accuracy, so the credit union team doesn't have to spend countless hours copying and preparing for reconciliation.

Katherine Cummings, senior accountant and senior system accounting analyst for VSECU, explained, "We started with one model and now we're up to 50-plus workspaces."

One model centers around a program called VHeat, offered exclusively to members. VSECU negotiates discounts for fuel oil, propane, kerosene and wood pellets, then passes these discounts to members; more than 2,500 members are enrolled in the program. The credit union estimates the VHeat program saved enrolled members a total of $683,000 compared to the street price of the products.

A data prep solution such as Datawatch's Monarch allows credit unions to quickly reconcile thousands of teller transactions daily.

Prior to using Datawatch, it took VSECU three minutes per VHeat registration form to complete the form, upload it and send it to its core processor (Fiserv's DNA). Cummings developed coding to allow Monarch to extract the member name and number, clearing account number, dealer information and fuel type from a PDF. The new enrollment process now takes 30 seconds or less.

With as many as 200 to 300 enrollments daily, the credit union ended up saving 125 hours of staff time for the whole season.

VSECU also uses Monarch for other processes involving core accounting, general ledger, teller reconciliation, ACH and third-party data. Cummings described how the credit union sets up work stations for different categories. "We have some set up to identify exceptions when we're balancing, to extract data just to make it more presentable, and to create some manual entry posting files that go into our GL systems."

Another organization, the $513 million, Kalamazoo, Mich.-based Arbor Financial Credit Union, uses Monarch to sift through large amounts of information and discover what's pertinent to resolve data issues and share accurate information across departments. Director of Core Systems Judi Burton said, "We are able to quickly reconcile thousands of teller transactions daily and create accurate reports to share with the management team and other internal departments. Monarch has greatly improved our efficiency and allowed us to grow."

Some of the most common use cases for Monarch among Datawatch's credit union customers include:

5300 call reports. The primary regulatory report mandated for quarterly filing consists of accounting and statistical information detailing assets, liabilities, liquidity and risks. Monarch enables credit unions to streamline collection, reconciliation, preparation and submission processes, and reduce data preparation time.

General ledger reconciliation. The self-service data preparation solution helps credit unions pull automated data extraction from static reports; and reduces the risk and cost implications from late or inaccurate books. Credit unions can use Monarch to prep disparate data for upload into its GL software including PDFs, XMLs, CSVs and PRNs.

Data extraction. Using the self-service data preparation and analytics platform, credit unions can access large volumes of transactional data from many sources, mine from multiple reports, identify data gaps and inconsistencies, reconcile accurate daily settlements and maximize the value of reports delivered by hosting providers.

Core system migration. To facilitate a transition and accelerate the transfer of critical financial records, core banking system providers, systems integrators and credit unions leverage self-service data prep to extract critical data from files, reports and documents.

ATM balancing/settlements. Monarch can automate the parsing and comparison of ATM posting reports with data from third-party ATM network providers by accessing large volumes of transaction data from all sources, mine from multiple reports to identify "data holes" and complete accurate daily settlements.

A new area of interest for Datawatch customers centers around fraud prevention and specifically auto loan fraud, which, according to Tacelli, will cost credit unions $4 to $6 billion this year. As an example, credit unions can use Monarch to red-flag multiple new member accounts established and funded with the same outside account. "Customers know they have a problem here. But in some cases, they don't know there is a solution."