QUALITY:
Training, professional development, and certification for practitioners and programs.
COMMUNITY:
Local, state, and national stakeholder networks that support and develop practitioner efforts.
CONSISTENCY:
Service delivery models and the underlying data systems that support them.
To assist low-income households with making more informed financial decisions, this brief proposes the implementation of a data-assisted case management/financial coaching model using a set of financial ratios and indicators. Incorporating household financial data in guiding financial decisions will inevitably lead to the professionalization of the field and will generate a real demand for structured training of new cohorts of financial coaching experts. Over time, this will create a pathway to build upon the collective knowledge base of all practitioners and present an opportunity to standardize definitions, facilitate communication among experts, and track improvements in financial well-being using objective measures of data. It can also lead to a more effective segmentation of the market, a key element in improving the delivery of programs and services to low- and moderate-income (LMI) communities.
Data assisted financial coaching could be an effective strategy to help improve financial well-being of lower income households. However, it will require financial coaches to receive additional training and embrace a possible professionalization of the field.
Ed Khashadourian, PhD is the principal at Opportunity to Asset (OPTA), a California-based social enterprise that specializes in savings and financial coaching programs for low-income households. The company also develops low-cost data collection platforms for its nonprofit partners.
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To assist low-income households with making more informed financial decisions, this brief proposes the implementation of a data-assisted case management/financial coaching model using a set of financial ratios and indicators. Incorporating household financial data in guiding financial decisions will inevitably lead to the professionalization of the field and will generate a real demand for structured training of new cohorts of financial coaching experts. Over time, this will create a pathway to build upon the collective knowledge base of all practitioners and present an opportunity to standardize definitions, facilitate communication among experts, and track improvements in financial well-being using objective measures of data. It can also lead to a more effective segmentation of the market, a key element in improving the delivery of programs and services to low- and moderate-income (LMI) communities.
Financial indicators and ratios introduced here are part of a framework known as the Equilibrium Model of the Household (EMH). EMH treats households as evolving economic units. Financial indicators are used in EMH in order to assess performance and financial health of the household, both in the short, and long runs. This essay only discusses short-term indicators which mainly focus on the household cash flow status (see Table 1). It is argued that if indictors listed in Table 1 are used in a systematic way by financial coaches, they may help identify the state of financial well-being of households on a continuum that covers complete “financial distress” to an “upwardly mobile” state of well-being. Knowledge of the financial condition of the household is critical in helping financial coaches to determine the proper coaching strategy for their low-income clients. In what follows, a total of seven distinct states of financial well-being are defined based on the financial indicators in Table 1. These categories can be used as a basis for segmenting the financial coaching market.
Data assisted financial coaching could be an effective strategy to help improve financial well-being of lower income households. However, it will require financial coaches to receive additional training and embrace a possible professionalization of the field.
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Financial indicators and ratios introduced here are part of a framework known as the Equilibrium Model of the Household (EMH). EMH treats households as evolving economic units. Financial indicators are used in EMH in order to assess performance and financial health of the household, both in the short, and long runs. This essay only discusses short-term indicators which mainly focus on the household cash flow status (see Table 1). It is argued that if indictors listed in Table 1 are used in a systematic way by financial coaches, they may help identify the state of financial well-being of households on a continuum that covers complete “financial distress” to an “upwardly mobile” state of well-being. Knowledge of the financial condition of the household is critical in helping financial coaches to determine the proper coaching strategy for their low-income clients. In what follows, a total of seven distinct states of financial well-being are defined based on the financial indicators in Table 1. These categories can be used as a basis for segmenting the financial coaching market.
44 Wall Street, Suite 605 New York, NY 10005 646.362.1645 phone 646.590.8743 fax
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44 Wall Street, Suite 605, New York, NY 10005
646.362.1645 phone 646.590.8743 fax