Transcript Using Data to Manage and Market your Loan Program

Using Data to Manage and
Market Your Program
Marcia Finlayson & Joy Hammel
University of Illinois at Chicago
AFP & ATF Technical Assistance Program
Federal Accountability Initiative


“If you don’t measure results, you can’t
tell success from failure” (C. Mindel)
“If you CAN demonstrate results, you
CAN win public support” (C.Mindel)
Session Objectives



To discuss how to effectively use AFP
outcome data in your state program &
systems change initiatives
To share examples of state use
To review the process for requesting
custom data runs and reports for your
state
The System: Data Collection

Initial Application (n=4210)


Follow-up: Approved at 6 months post (n=816)


Applicant & AT user demographics, AT Request, Prior
funding experiences, Loan info, decision & terms
If received & using AT, Impact on life
Satisfaction with services, Overall impressions of
program and its utility
Follow-up: Denied or did not accept at 1 mo.
Post (n=338)

Reasons for denial/not accept, Follow-up outcomes,
Satisfaction
Ways to Obtain & Use Data
1. Online Public Reports


By state or nationally
By time period
2. Annual & State
Reports
3. Custom Reports

From states upon
request
AFP Use Demographics

Overall demographics (n=4210 as of 11/4/04)





52.8% male
76.5% White & 17.1% are African-American
91% are primarily English speakers
70% are not working
Median monthly income = $2000/month


25% are below $1069/month
Fairly evenly distributed urban, suburban, rural (1/3)
Custom Reports: Data Mining



Refers to “mining” or exploring the data
available in much more depth
Possible by having UIC download the
data from the system into special
software that allows advanced statistical
analyses
Allows the development of custom
reports and the ability to answer
specific questions
Data Mining: Example
Question: How are older adults using AFP
and are there differences in AFP use &
outcomes by age?
Findings

Age distribution: Range: 6 months to 95
years


0.5-39: 33% (n=1386)
40+: 60% (n=2512)





40-49: 16.5% (n=693)
50-59: 17.4% (n=733)
60-69: 12.3% (n=516)
70+: 13.5% (n=570)
Not reported/unknown: 7% (n=312)
AFP Use by Age

Descriptive information:

Age



2003: Average age: 46.5 years (sd=19.8)
2004: Average age: 45.4 years (sd=22.5)
Find Out about the Program


2003: Referrals primarily through a disability agency
(25.2%) or vendor/dealer (19.7%)
2004: Referrals primarily through a disability agency
(23.5%) or vendor/dealer (27.8%)
**As of November 27, 2003, N=2639
**As of November 4, 2004, N=4210
Finding the AF Program
45
40
35
30
Vendor
Professional
Mail
Disability Agency
25
20
15
10
5
0
40-49
50-59
60-69
Age of applicants
70+
p<0.0001
Nature of Requests Among
Applicants Aged 40+

Overall, most common single request is
for adapted transportation (n=1413),
followed by hearing aides (n=881), then
mobility equipment (n=303)

Most common dual request is for mobility
equipment plus adapted transportation
(n=238), followed by computer equipment
plus computer access (n=100)
% of Requests for Specific AT,
by Age Group
100%
90%
% of requests
80%
70%
60%
adapted transportation
hearing aides
mobility equipment
50%
40%
30%
20%
10%
p<0.0001
0%
40-49
50-59
60-69
Age groups
70+
Outcomes of Applications
Among 40+ group

Overall, 65.6% of all applications have
been approved & 26.8% denied

Other outcomes of loan - 7.6%


E.g., withdrawn, approved/not accepted;
pending
Average age of:



Approved applicants = 60.5 (sd=13.0)
Denied applicants = 56.5 (sd=12.1)
Other applicants = 56.7 (sd = 10.8)
Loan Decisions by Age Group
100%
90%
% of decisions
80%
70%
60%
other
denied
approved
50%
40%
30%
20%
10%
0%
40-49
50-59
60-69
Age groups
70+
p<0.0001
Loan Amounts by Age Group
$7,000.00
Median Loan Amt
$6,000.00
$5,000.00
$4,000.00
$3,000.00
$2,000.00
$1,000.00
$0.00
40-49
50-59
60-69
Age Group
70+
Follow-Up on Approved Loans

474 people 40+ participated in at least
part of an approved follow-up interview


Missing data for individual questions
depending on applicability to loan request
– up to 30% for some questions
Results must be considered exploratory
Follow-up on Approved Loans

Status of AT equipment receipt (N=337
age 40+)




90.5% had received their AT and were
using it
3.6% had not yet received
Remainder (5.9%) had received but not
using (e.g., broken, don’t know how,
doesn’t meet needs, etc)= abandoned
No differences by age
Satisfaction with Program for
Approved Loans (N=336)
100%
90%
% of respondents
80%
70%
60%
satisfied
not satisfied
50%
40%
30%
20%
10%
0%
40-49
50-59
60-69
Age Groups
70+
Follow-up on Approved Loans

Participants reported improvements in:

QOL related to AT/EM impact –





88.7% report improvement (N=310); 9.8% stayed the
same, 1.1% got worse
60-69 least likely to report improvements (p=0.03)
Ability to participate in social & recreational
activities - 77.1% got better (N=284)
Ability to complete home/community management
activities - 70.3% got better (N=279)
Ability to control life and life decisions
- 63.4% gained control/increased (N=262)
Follow-up Outcomes

67.8% (N=329) report ability to fund AT they
would have been unable to obtain through
other sources



70+ least likely to report this outcome (p=0.02)
85.2% who were approved loans and did a
follow-up interview would recommend the
program to others (*)
86.3% who were denied loans and did a
follow-up interview would recommend the
program to others (*)

(*) – high rates of missing data (up to 30%)
Outreach to Older Adults
State Specific Examples of
Data Use
Additional ways to use AFP Data
Using data to negotiate with
lending institutions




Comparison of state interest rates to renegotiate
rates in each state
Proportion of African Americans using program to
negotiate relationship with lending institution that
serves this population
Average loan amount for each repayment schedule
(e.g., under 1 year, 5 yr., 10 yr. payback periods)
Relationship between income and loan size to
negotiate with bank
Using data to leverage/expand
resources for AFP


Proportion of low income individuals for tax
exempt program eligibility
Characteristics of AFP applications for people
under 18 yrs.of age to pursue grant to
supplement funding
Using data to target outreach
efforts

ID gaps in source of referrals and who’s applying


Examining how different groups access the program


E.g., coming in from professional referrals versus other
sources
E.g., looking at referral source in light of applicant
characteristics such as minority status, income status, etc.
Trends in these issues over time

E.g, showing how minority outreach & application rates have
increased over time/impact of targeted outreach campaigns
How to request your own
custom analyses
Requests

Either:

Send us an e-mail:



[email protected] or [email protected]
Complete the request form and mail or fax
it in
Turn-over time depends on the nature
of request and its complexity

Typically 5 working days
Questions & Comments