CIVEA 2019: Debt and Financial Resilience
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The document discusses Policy in Practice's work on analyzing and managing local and central government debt through the Reimagine Debt pilot program. The program aims to consolidate household-level debt data to offer holistic debt guidance. Initial pilots in Newcastle and Barking manually pooled debt data on 39 families. The program is now looking to scale up this approach by using analytics on pooled household datasets to identify vulnerable families, engage them proactively, and track outcomes over time. The outcomes of the Barking pilot found that average arrears fell by £1,100 across 21 households tracked over 18 months, reducing total rent and council tax arrears by £17,600 and £5,500 respectively.
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CIVEA 2019: Debt and Financial Resilience
- 1. Deven Ghelani Policy in Practice CIVEA 2019 Debt and Financial Resilience
- 2. We make the welfare system simple to understand, so that people can make the decisions that are right for them We help people toward independence by making government policy simple to understand
- 3. A team of professionals with extensive knowledge of the welfare system who are passionate about making social policy work We help over 80 local authorities use their household level data to identify vulnerable households, target support and track their interventions Our benefit calculator engages over 10,000 people each day. We identify the actions people can take to increase their income, lower their costs and build resilience
- 4. 444 Why are people in debt?
- 5. Wider welfare reforms and austerity
- 6. People are worse off
- 9. Cost avoidance through reimagine debt interventions: • Court costs of enforcement and better collection • Eviction (referred to panel) and care costs for children (direct care costs and impacts of moving schools) • Improved wellbeing and better mental health outcomes (17% of cohort), e.g. lower GP / Medication costs (no longer losing sleep, less anxiety, depression, leaving the house) • Advisors had impacts on other outcomes too, clients could be suicidal, facing domestic violence, have language barriers to overcome, or parental conflict (parents with non-dependant children) The impacts of indebtedness
- 10. • 1.6 million people on Universal Credit today • A further 1.6m people moving onto Universal Credit this year • 2 million people moving on through ‘managed migration’ from 2020 Key recommendation: DWP and councils can identify these pressure points, and act proactively to prevent hardship and ease the transition to Universal Credit Universal Credit is rolling out fast
- 11. Reimagine Debt Policy in Practice has been asked by the Cabinet Office to analyse the management and collection of local and central government debt Building on the successful ‘Reimagine Debt’ pilot, looks at the role of data to generate a consolidated household level view of debt. Consolidated debt data, in the context of a household’s wider finances, can create a culture of holistic, proactive and effective service delivery across local & central government In Phase 1 Newcastle and Barking and Dagenham councils manually pooled debt data on 39 families to offer them debt guidance Phase 2 looks at how this approach can be scaled up
- 12. We pool your datasets on low income families, and link them over time to create a single view Our policy engine shows the impact of all policies, now and in the future, on each family The insights enable you to proactively identify who needs what support, engage people and track impact Household data + advanced analytics
- 13. 16,934 low income households in Neath Port Talbot
- 14. 2,596 are in council tax arrears
- 15. 1,255 owe more than one month’s council tax
- 16. 205 of them are impacted by welfare reform
- 17. 59 of whom face an ongoing cash shortfall
- 18. … and 7 will be worse off under Universal Credit
- 19. Focus on 1 household
- 20. Engage through tailored calculation
- 21. Lessons learned in LBBD Policy / legislative awareness: Look into the 3 cases where DHPs were refused. If households affected by welfare reforms had been made aware of DHPs earlier, then arrears may have been avoided. Ensure take-up of benefits: many of the improved cases started claiming Housing Benefit and / or Council Tax Support for the first time. What counts as an improvement?: There are cases where arrears have worsened, but their lives may have improved in other aspects (ie they have started work, agreed a payment plan). We need to track these households over a longer time period. Many of the improved households had changed utility provider: Is this a large opportunity, and does it have implications for the involvement of third parties eg. utilities? Consider differences in outcomes between Advisors: 90% of Advisor 3's clients saw their level of debt improve - compared to 63% of Advisor 2's and 43% of Advisor 1's. Are different Advisors taking different approaches, and can improved approaches be scaled?
- 22. We tracked the debt severity, living standards, financial resilience and other outcomes for 21 households across Barking and Dagenham across 18 months • 3 households moved out of arrears completely • Average arrears fell by £1,100 • Across the 21 households, the total rent arrears balance fell by £17,600 and the total council tax arrears balance fell by £5,500 The outcomes of reimagine debt
- 23. Follow: @policy_practice @Deven_Ghelani Subscribe: www.policyinpractice.co.uk/blog www.policyinpractice.co.uk/newsletter More information
- 24. www.policyinpractice.co.uk Thank you Deven Ghelani deven@policyinpractice.co.uk 07863 560677 James Rawlins james.rawlins@policyinpractice.co.uk Steven Coppard steven.coppard@cabinetoffice.gov.uk
Editor's Notes
- Three main areas: - Software Analytics Policy I worked on Universal Credit, Policy into Practice – Make sure policy can be understood by people and organisation on the frontline. Ensure policy is informed by practical experience on the frontline.
- Analytics – Software – Policy
- Wider reforms are all lumped into Universal Credit
- BRADFORD Governments may know how one policy affects many people. We can show how all policies combined affect one person. We work with household level data from over 40 different local authorities to Welfare reforms we model, and how accurate we are.