Datawatch Reports Continued Growth In Credit Union Industry, Driven By Increased Demand for its Self-Service Data Preparation Platform

More than 700 credit unions using Monarch to overcome data access, reconciliation and analytics challenges, and turn static report data into actionable business intelligence


BEDFORD, Mass., May 17, 2017 (GLOBE NEWSWIRE) -- Datawatch Corporation (NASDAQ-CM: DWCH) today announced that it continues to see sustained demand for the Datawatch Monarch self-service data preparation and analytics platform among credit unions. The company experienced 124 percent revenue growth in the industry over the past year alone, and it now boasts more than 700 credit union customers with assets ranging from $23 million to $78 billion. Credit unions across North America are turning to Datawatch Monarch to expedite data access, preparation and analysis; streamline reconciliation; distribute reporting processes and datasets; and facilitate data-driven financial decisions.

“Many credit unions struggle with accessing, organizing, integrating and analyzing data trapped in flat reports, transaction systems and other business documents scattered throughout the organization,” said Michael Morrison, CEO of Datawatch. “Monarch has seen rapid adoption in the credit union industry because it solves this exact problem, enabling users to access all of the data they need regardless of source or format, and then transform the information into interactive reports for easy analysis and visualization. Looking ahead, Monarch’s new features related to data socialization and the sharing of curated data sets for enhanced collaboration will provide credit unions with deeper visibility into their business, resulting in more informed decisions, time and cost savings and improved member experience.”

With Monarch, data can be prepared for analysis in a fraction of the time that it takes using spreadsheets and other manually-intensive measures. Stagnant information in stock system text reports is transformed into actionable business intelligence that expedites analysis, yields more accurate and strategic financial decisions, and improves operational processes. And, through automated and repeatable modeling, credit unions can eliminate errors inherent with manual calculation and input, and create, distribute and publish thousands of reports internally without time delays or involving IT.

In addition to tasks such as daily teller reconciliation, debit and credit card reconciliation, ATM terminal activity analysis, loan servicing, and member service enhancement, some of the most common use cases for Monarch among Datawatch’s credit union customers include:

5300 Call Reports
For credit unions in the U.S. regulated by the National Credit Union Association, the primary regulatory report mandated for quarterly filing is the 5300 Call Report, which consists of accounting and statistical information detailing credit unions’ assets, liabilities, liquidity and risks. Monarch enables credit unions to streamline collection, reconciliation, preparation and submission processes, and reduce data preparation time from weeks to hours. Monarch also helps organizations reduce the risk of incurring exorbitant fines from late or inaccurate reports.

Harry Schreiber, senior systems analyst at Bellco Credit Union, explained: “We use Monarch to access and extract data from trial balances, parse it out and then apply it to different fields in the 5300 Call Report. It has eliminated the need for us to manually input data into spreadsheets, and this has resulted in significant time and cost savings for our organization.”

General Ledger Reconciliation
Reconciling the general ledger is essential for ensuring that all banking transactions match the balances shown in each account – and accurate reconciliation is vital for maintaining credibility and trust between credit unions and their customers. Datawatch’s self-service data preparation solution helps credit unions shorten day-to-day operational reporting tasks from weeks to hours, or hours to minutes; improve accuracy by replacing manual re-keying with automated data extraction from static reports; and reduce the risk and cost implications from late or inaccurate books.

Advancial Federal Credit Union uses Monarch to prep disparate data for upload into its general ledger software. “We receive reports in multiple formats, including PDFs, XMLs, CSVs and PRNs,” said Advancial Accounting Manager Dana Herrington. “Monarch allows us to integrate, manipulate and prepare all data, and easily blend it into a common report format suitable for our general ledger system. The ‘drag and drop’ functionality and intuitive nature of the Monarch software is tremendously helpful for us.”

Director of Core Systems, Judi Burton at Arbor Financial Credit Union relies extensively on Monarch to resolve data issues and share accurate information across departments. “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 and serve our customers better.”

Data Extraction from Core Banking System Reports
Datawatch credit union customers are turning to Monarch to automate and expedite the extraction, parsing, cleansing and joining of disparate reports from various core banking systems, including Fiserv, FIS, D+H, CSI, COCC, Jack Henry/Symitar, etc. Using the self-service data preparation and analytics platform, they can access large volumes of transactional data from all sources; mine from multiple reports and identify ‘data gaps’ and inconsistencies; reconcile accurate daily settlements faster and easier; and maximize the value of reports delivered by hosting providers.

Data analysts at State Employees Credit Union receive many reports from third-party vendors, and, before Monarch, it was extremely difficult for them to access the data in these documents. According to Data Analyst Kristen Snyder: “We have an extensive list of reports that we receive from outside vendors, and they are not always in the right format for analysis. Monarch helps us clean and prepare the data, so different departments in our organization can balance and reconcile it in a timely fashion. Monarch also helped us reduce data preparation time from days to minutes, and it automates monotonous daily tasks, so we can focus on what we’re really responsible for: data analysis.”

Core System Migration
Upgrading or changing critical business applications is a major challenge in any industry. When credit unions migrate from one core banking system to another, organizations must mitigate the risks of both downtime and compliance. To facilitate a seamless transition and accelerate the transfer of critical financial records, core banking system providers, systems integrators and credit unions leverage Monarch to extract critical data from files, reports and documents. Monarch enables teams to avoid manual data entry and time-consuming data reconciliation by automatically pulling semi-structured data formats and transforming it into structured datasets, saving time and ensuring information accuracy.

ATM Balancing/Settlements
Monarch also saves credit unions time, money and resources by automating the parsing and comparison of ATM posting reports with data from third-party ATM network providers. Not only can data analysts access large volumes of transaction data from all sources, but they can mine from multiple reports to identify ‘data holes’ as well as complete accurate daily settlements faster and easier.

For more information about how Datawatch Monarch is being utilized in the credit union industry, visit: http://www.datawatch.com/solutions-credit-unions/.

About Datawatch Corporation
Datawatch Corporation (NASDAQ-CM: DWCH) enables ordinary users to achieve extraordinary results with their data. Only Datawatch can unlock data from the widest variety of sources and prepare it for use in visualization and analytics tools, or for other business processes. When real-time visibility into rapidly changing data is critical, Datawatch also enables users to analyze streaming data, even in the most demanding environments, such as capital markets. Organizations of all sizes in more than 100 countries worldwide use Datawatch products, including 93 of the Fortune 100. The company is headquartered in Bedford, Massachusetts, with offices in New York, London, Frankfurt, Stockholm, Singapore and Manila. To learn more about Datawatch or download a free version of its enterprise software, please visit: www.datawatch.com.

Safe Harbor Statement under the Private Securities Litigation Reform Act of 1995
Any statements contained in this press release that do not describe historical facts may constitute forward-looking statements as that term is defined in the Private Securities Litigation Reform Act of 1995. Any such statements contained herein, including but not limited to those relating to product performance and viability, are based on current expectations, but are subject to a number of risks and uncertainties that may cause actual results to differ materially from expectations. The factors that could cause actual future results to differ materially from current expectations include the following: rapid technological change; Datawatch’s dependence on the introduction of new products and product enhancements and possible delays in those introductions; acceptance of new products by the market, competition in the software industry generally, and in the markets for next generation analytics in particular; and Datawatch’s dependence on its principal products, proprietary software technology and software licensed from third parties. Further information on factors that could cause actual results to differ from those anticipated is detailed in various publicly-available documents, which include, but are not limited to, filings made by Datawatch from time to time with the Securities and Exchange Commission, including but not limited to, those appearing in the Company’s Annual Report on Form 10-K for the year ended September 30, 2015. Any forward-looking statements should be considered in light of those factors.

© 2017 Datawatch Corporation. Datawatch and the Datawatch logo are trademarks or registered trademarks of Datawatch Corporation in the United States and/or other countries. All other names are trademarks or registered trademarks of their respective companies.

Source: Datawatch


            

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