I. Introduction
The National Federation of Community Development Credit Unions helps low- and moderate-income individuals achieve financial independence by assisting credit unions that serve under-banked communities. The Federation’s members provide financial services to over 4 million customers and hold $32.5 billion in assets. The Federation’s members are classified as “community development credit unions” (CDCUs) – a particular type of financial institution which aims to assist economically vulnerable individuals in establishing financial security for themselves, their families and their neighborhoods. With an emphasis on mission, stewardship and personal interactions, these organizations have served as important lifelines in the
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II. Methodology
Through informational interviews with seven industry experts and a thorough literature review, the team explored the concept of “big data” and generated key insights which will guide the Federation’s approach as the organization develops its members’ data analytics capacities. Additionally, the team identified a clear business case for implementing data analytics at CDCUs using strategies appropriate for the level of resources within each individual organization. The team also developed a set of survey questions for the client to use when gauging the level of interest and capacity within any individual CDCU.
III. Understanding Big Data and Predictive Analytics
The increasingly popular terms “big data” and “predictive analytics” have become so widely discussed that, in many ways, they lack a cogent meaning – even within the financial industry. The Capstone team used the literature review as an opportunity to scan the field for defining characteristics, resulting in a suggested guide for how the Federation should articulate these concepts. Generally speaking, big data is about the growing availability of data, as well as the tools needed to analyze the information. Predictive analytics refers to the analysis of big data which can help uncover patterns, correlations and trends that were otherwise unknown to the organization. Predictive analytics is also known as
Navy Federal Credit Union is the world’s largest credit union that serves the military and their families. Navy Federal Credit Union is non-profit organization that offer competitive packages to their employees and customers. Navy Federal has a peer 2 peer recognition programs that encourages employees to tell their co-workers how great they are by giving them a virtual “first bump (Fortune, 2016). Navy federal dedicate their services to members, and families that serve in the military. They offer a variety of variety of packages and incentives to satisfy their employees. They promote innovation by providing onsite health benefits, family care programs, compensation programs, and community involvement.
The organization selected for analysis and evaluation is American Lake Credit Union. This organization is composed of two main branches, both located in Tacoma, Washington. In contrast to banks, Credit Unions are smaller organizations and are directed by members who are selected via a vote to serve in an all-volunteer board of directors for the organization (Scott, and Johnston, p.2, 2011). Specifically, this credit union was founded in 1948 and has grown since then. (C. Fitzer, personal communication April 7, 2014). For instance, although the organization is small in size through a partnership with a credit union network, it is able to provide general financial services at diverse locations
Foster Provost and Tom Fawcett. Big Data, Data Science and its Relationship to Big Data and Data-Driven Decision making,” http://online.liebertpub.com/doi/full/10.1089/big.2013.1508
Big data and its definition has changed over the years. In a 2011 research project by MGI and Mckinsey’s Business’ defined big data as
The credit Union focuses on providing a message of being able to provide reduced rates below that of a
Today, data is a growing asset that various businesses are having difficulty converting into a powerful strategic tool. Companies need help turning this data into valuable insight, which can diminish risk and enhance returns on investments. Companies are struggling to make sense and obtain value from their big data. Superior and reliable
“Predictive analytics uses technology to predict the future and influence it.” [27] It is predominantly being used to improve business processes, which is a great opportunity for entrepreneurs to achieve positive business outcomes [26]. The goal of this white paper is to discuss the impact of predictive analytics in today’s world and the various concerns that come along with it. The paper addresses key research questions like what are the legal and ethical concerns that rise from predictive analytics? And where can we use predictive analytics to get positive results? We have tried to analyze the current market situation in order to answer these questions, focusing on the key areas where predictive analytics has had positive and negative impact. After intense scrutiny of the facts and details encountered by us, we have come up with some recommendations and solutions to address the issues caused by the use of predictive analytics and how their effects can be balanced by organizations.
Big Data embraces structured, semi-structured and unstructured information. It can be demographic or psychographic information about the customers, their opinions, product reviews etc gathered from variety of sources such as tweets, blogs, other social media content, technical devices like sensors and stream of data from mobile devices. Businesses have started using Big Data to get right information to identify right markets and right customers at the right time in order to make right strategic decisions. The Big Data market is estimated to grow to $32.1 bn by 2015 and $54.1 bn by 2017. According to the report “Be Careful or Big Data Could Bury Your Bank”, the world creates 2.5 quintillion bytes of data daily and last 2 years have contributed to almost 90% of the data which exists today. It empowers institutions to learn more, create more and do more using the data available with them.
Business thrive when they have the most accurate, up-to-date, and relevant information at their disposal. This information can be used for a plethora of pertinent markers in small and large businesses, relating to accounting, investments, consumer activity, and much more. Big data is a term used to describe the extremely large amounts of data that floods a business every day. For decades, big data has been a growing field, facing controversy on many levels, but as of late, it has been a major innovator in the challenge of making businesses more sustainable. Big data is often scrutinized for its over-generalization and inability to display meaningful results at times. When applied correctly, data analysis can bring earth-altering information to the table.
According to a report from The International Business Machines Corporation, known as IBM, 90% of the data in the world has been generated in the last two years. Frank J. Ohlhorst (2013) explains how the concept of collecting data for use in business is not new, but the scale of data that has been collected recently is so large that it has been termed Big Data (p. 1). Company executives who choose to ignore Big Data are denying their companies an advantage over their competitors. Big Data analysis is fundamental for all fields of work; it provides an insight to large amounts of data that will answer questions and make discoveries to improve efficiency in all areas of the world.
In the U.S., there is nearly 2,000 community development corporations (CDCs) have built housing, involved in economic development projects, and provided the various social services for the past three decades (NCCED, 1995). Currently, most of attention CDCs have received is from government and private funders as a promising way to promote urban neighborhoods. These CDCs are consisted of nonprofit, community-controlled real estate development organizations that dedicate to the revitalization of poor neighborhoods. They undertake physical revitalization such as economic development, social services, and organizing and advocacy activities. Since public services for poor communities are fragmented across multiple agencies and levels of government, CDCs often are the only institution with a comprehensive and coordinated program agenda.
In the increasingly competitive global business environment, each organization needs to take advantage of every tool, opportunity, and advantage it can to achieve the best products and services, to gain and maintain market share, and keep stakeholders happy from investors and workers to supply chain and customers. The advance of data analysis has opened up new vistas to support decision making. Decision support systems (Sauter, 2010) have emerged that process various forms of data to build outcome models. These have been adopted in every segment of society, in the private and public sector, from political campaigns and the military to corporations and nonprofits alike. As a whole, the new set of tools involving the strategic use of data is called business intelligence. Within that general framework, the term analytics refers to the statistical, quantitative use of data to produce explanatory and predictive models for fact-based decision making. (Sauter, 2010).
Firstly, the main problem is deciding which data should be selected. The data, explaining customers’ desires and needs, is important to be collected while most of the enterprises are confusing about what data they should concentrate on. A recent Gartner report (2014) stresses that 64% of firms raced to plan or launch a Big Data project, though they did not have enough professional knowledge yet. To understand what customers need through Big Data possibly turns into the core of companies’ target. The large data volumes and different varieties of data lead to data complexity.
Data is the backbone of business today and has always played a critical role in business. Today in the era of “Big Data” and Digital Business, data has become the primary driver of decision making, growth and innovation. The big data today is radically different from the data of yesterday. The Big Data age has brought with it a tremendous increase in the amount of data and types of data available to businesses. New data is produced every day, generated by social networking sites, mobile phones, location, third party, business transactions, etc. We are in an era which is characterized by the 5 V’s of Big Data: Volume, Velocity, Variety, Veracity and Value. The Big Data opportunities are enormous, as are its challenges. In this context it is especially important to understand the Opportunities and Problems that business faces to extract value from Big Data Analytics.
“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” – Geoffrey Moore, author and consultant.