Finding A Yardstick: Field Testing Outcome Measures for Community-based Financial Coaching and Capability Programs

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Finding A Yardstick: Field Testing Outcome Measures for Community-based Financial Coaching and Capability Programs Measurement Tools J. Michael Collins University of Wisconsin- Madison 2013 1

The Coaching Model Focus on improvement Focus on the future (not the past) Ongoing collaborative process Client sets his/her own goals 1. Set Goals -> Intentions/plans 2. Accountability & Self-control -> External monitor; counter procrastination 3. Focus attention -> Persistence Useful Financial Coaching Information - http://fyi.uwex.edu/financialcoaching/

Financial Coaching Framework Improve the financial security, mental and physical health, cognitive development, and general well-being of low-income children and families. Family members develop greater financial capability and are empowered to adapt to new economic contexts through increased self-efficacy, accountability, self-control, attention/reduced inattention, and goal-focused financial behaviors. High Impact Financial Coaching Programs Volunteer Models Public Systems Nonprofit Professionals Access to high quality coaching is expanded and integrated into programs. Skilled Coaches Reliable Metrics Community of Practice Professional Field

Diagnosis Purposes for the purpose of triaging services and matching clients to appropriate resources Baseline status in order to document the initial or pre-service condition of clients Outcome measurement in order to re-assess the status at baseline or prior periods to intermediate or post-service status of clients 4

Measurement Model Attitudes Experiences Behaviors Decisions Financial well being Self sufficiency Knowledge 5

Categories of Measures Savings (household level) Banking Debt (household level) (household level) Credit Psychology (individual level) (individual or household) Economic Sufficiency (household level) Human Services (household level)

Categories of Measures Savings: many variations; too difficult to measure ambiguous at least in short run Banking hard to measure and interpret Debt ambiguous at least in short run Credit requires access to reports still developing standards Psychology lack standards Economic Sufficiency longer term and broader in scope Human Services requires public agency cooperation

Survey Credit score Credit report items Pros Flexible, especially when collected at intake or as part of services Single metric; widely used in industry to allocate and price credit; well understood benchmarks Number of accounts, delinquencies and balance ratios available from credit report; more likely to move than score Cons Self-report bias; lack of cooperation, especially for follow-up; can be costly to collect, requiring incentives. Proprietary formula based on credit report for a fee. Some clients have 'thin' files and no score. Slow to change even as behaviors improve. Some clients lack reports; benchmarks not well agreed upon; privacy and consent barriers. Bank balances Directly manage assets; more accurate than self-report(?) Budgeting data Self-reported in concert with transaction records and relevant documents for verification Public records Legal filings generally posted within 1-2 months of judgment, foreclosure, or bankruptcy Public agency data Public benefits use, earned income reported under FICA, education, unemployment, and other issues are related to household financial status. Very noisy. Only a snapshot of one point in time; regulatory, privacy and client consent barriers. Complicated and time consuming; one point in time. Challenging to collect longitudinally. Relatively low probability events. Data quality and access is uneven across communities. Requires agreements with state agencies; consent and human subjects limits. Generally need large-scale projects.

Data Time Measures Use Bon Secours (Baltimore) fall 2012 to spring 2013 8Q survey; credit records (debt, delinquencies, judgments, credit scores) X-sectional reliability (combined); validity The Financial Clinic (New York City) fall 2012 to spring 2013 8Q survey; credit records (debt, delinquencies, judgments, credit scores) X-sectional reliability (combined); validity University of Wisconsin-Extension (UW-Extension) fall 2012 to spring 2013 8Q survey X-sectional reliability (combined); small panel to examine prepost outcomes LISC Chicago (always used alone) January 2011 to December 2012 Full intake (100+ measures), budgets, credit records (debt, delinquencies, judgments, credit scores); survey Qs (4 in common) X-sectional reliability and validity; panel to examine pre-post outcomes; analysis of credit scores

Question Concept Evaluation 1 Budgeting Modify. Language related to budget, spending plan and financial planning maybe too broad. Key construct is planning ahead. 2 Goal Perhaps retain, but drop written portion unless useful programmatically. Goals maybe a key activity of coaching but have little diagnostic value. 3 Confidence Keep. Appears more predictive of credit and savings behaviors than reporting a goal. 4 Auto Deposit/Save Keep. Language may need to be refined (currently restricted savings examples). 5 Emergency Fund Keep. Language is convoluted. Time period of 3 months maybe excessive. Not clear how spending for an emergency might be handled. 6 Spending Modify. Currently 3 possible responses. Key factor appears to be spending less than income. Change to yes-no. 7 Late fee Keep. Time period could be modified but fees are strongly predictive. 8 Credit rating Retain (as score proxy). Appears to have little relationship to other behaviors, but is correlated with current credit score (0.63)

Fig 1: Scale vs Credit Score (TFC/BS))

Recommended Financial Capability Scale (0-8 point scale) 1. Over the last 3 months, have you followed a personal budget, spending plan, or financial plan? (Yes=1, No =0) 2. How confident are you in your ability to achieve a financial goal you set for yourself today? * Not at all confident (0) * Somewhat confident (1) * Very confident (2) 3. Have you set aside funds that would cover your expenses for 3 months if you or someone in your family lost a job, got sick or had another other emergency? (Yes=1, No=0) 4. Do you currently have an automatic deposit or electronic transfer set up to put money away for a future use such as saving for retirement or education? (Yes=1, No =0) 5. Over the past 3 months, would you say your household s spending on living expenses was less than its total income? (Yes=1, No or DK=0) # 6. In the last 3 months, have you paid a late fee on a loan or bill? (Yes=1, No =0) How would you rate your current credit record? * Very bad * Bad * About average * Good * Very good (* Don t know) 13

Fig 5 Self Assessed Credit Quality and Credit Score (TFC/BS)

Rate your credit: Self Report Excellent 3% Good 14% Don t Know 6% Very Poor 13% 800 750 Credit Score vs. Self Assessments Fair 30% Poor 34% 700 650 Don't Know Credit vs. Rated Credit 600 800 700 550 600 500 500 400 300 450 200 100 0 Mean Credit Score Min Credit Score Max Credit Score 400 Very Poor Poor Fair Good Excellent Mean Credit Score Min Credit Score Max Credit Score Don t Know Knows score

45% Self Report of Frequency of Paying On Time 43% 41% 39% 37% 35% 33% 31% 29% 27% 25% Never Rarely Sometimes Often Almost Always Mean Percentage of Accounts Past Due 120 Mean Fees by Number of Late Fees Reported in Last 3 months 100 80 60 Mean Fees 40 20 0 0 1 2+

1. Credit score Credit Report Items 2. # 30 day delinquencies 3. # items in collections 4. # items judgments (public records section) 5. A. $ revolving credit limit (mainly credit cards, not HELOCs) 6. B. $ revolving credit outstanding (mainly credit cards, not HELOCs) 7. Ratio: B/A 17

Fig 7. Probability of Credit Score by Number of Active Cards

Demographics 1. Client age 2. Presence of spouse/partner 3. Number of dependents 4. Employment status (full, part, unemployed, disability) 5. Gender 6. Education (HS, some college, 4+ degree) 19

LISC Data mean sd count Written Goal 0.516 0.500 1370 Goal Length 23.06 37.51 1370 Have Budget 0.193 0.395 1336 Late/NSF 0.466 0.499 1343 Have Check Acct 0.577 0.494 1337 In Collections 0.404 0.491 1323 Emerg Save 0.211 0.408 1330 Age 41.35 12.23 1370 Income 9941.8 14032.7 1310 Ed Level (1-3, 1=hs) 1.168 0.775 1349 Male 0.445 0.497 1370 Fin Svs Intake 0.442 0.497 1370 30 day Dels CR 1.137 3.799 1035 CR Score 580.5 80.44 1035 Sav Bal (if >0) 1984.7 9813.1 431 Net Worth (0=0) 3125.8 64106.8 1352

TFC*, BS*, UWEX Data mean Do You Have a Budget, Spending, or Financial Plan? 0.512 Have You Used An Automatic Deposit to Put Money Away 0.401 Have You Set Aside Emergency Funds? 0.283 Have You Paid a Late Fee on a Loan or Bill? 0.345 Spend less than income 0.351 Spend more than income 0.406 Do You Have At Least One Financial Goal? 0.815 Length of written goal: 24.65 How Confident in Achieving Goal? 3.342 CR Score * 584.5 Debt Amt * 43281.2 Log Debt * 8.499 30 Day Del * 6.352

Fig 6: Scale Pre-Post Measures (UWEX)

Table 15. Coaching Outcomes: LISC data (1) (2) (3) CR Score t2 Sav Bal t2 Dels t2 Financial Counsel 3.704 89.124 * -0.047 (3.320) (43.250) (0.167) Constant -2.946-18.772 1.189 (13.181) (46.898) (0.739) R-squared 0.931 0.991 0.644 N 242 176 156

Take Aways No measure is perfect Some measures are better than none Changes in measures can be hard to interpret Self reports do have value Objective data also have limitations Details matter Context, wording, layout, format, mode, timing Field needs leadership to move to consistency 24

Questions: Measures 1. Are these outcomes of interest? To whom? 2. Other ways to measure goals? 3. What is cost of credit report data? Benefit? 4. What is the appropriate time frame for pre-post measurement Process 1. Is the data collection process a burden? For whom? 2. How to handle data entry? 3. How well can you follow over time? 4. What percentage of clients will likely cooperate?

Questions: Next Steps 1. What support is needed? 2. Will the field accept a narrower and more standard set of outcomes? 3. How interested are organizations in sharing their data? 4. What are barriers to more research? 5. How can human subjects protections be best protected? 6. What other administrative data could be obtained?