After a few weeks here at Registry Trust, I thought I would use this opportunity to introduce myself as the new Data Analyst and explain how I came to this role.
My name is Millie Corless, and I am recent Masters Graduate of Geographic Data Science, having completed my Bachelors in Geography at the University of Liverpool. I decided to complete my MSc dissertation alongside an industry sponsor, and with particular interest in spatio-temporal inequalities and financial vulnerability, I was introduced to Registry Trust.
Registry Trust maintains the register of Judgments, Orders and Fines for England & Wales, Scotland, Northern Ireland, Republic of Ireland, Isle of Man and Jersey. Its aim is to share ‘public data for the public good’ to inform responsible lending and borrowing in the UK. This data has become vital to the credit information industry and, with a global pandemic causing unprecedented economic shocks, analysing and understanding this data is more important than ever for household finances.
My dissertation served as an introduction to the huge potential for varied analysis of Registry Trust’s data. Understandably, some may find data related to financial vulnerability somewhat gloomy, however I do not. Instead, I see this virtually untouched dataset as an opportunity to guide improvements in our society; with my dissertation project as my starting point!
First, a little context. The 2008 and 2016 Global Financial Crisis exacerbated the two-fold issue of declining incomes and increasing living costs. This amplified financial strain generates an increasing likelihood of borrowing money, or an inability to afford repayments.
My dissertation project assessed geographic and temporal patterns in consumer (individual level) County Court Judgment (CCJ) rate (as an indicator of financial vulnerability), and considered the extent to which general health influences personal financial vulnerability across England and Wales. The project then considered the influence of additional socio-economic variables, such as Tenure and Employment Status, on financial vulnerability. The outcomes highlighted spatio-temporal locales where specific socio-economic variables influence financial vulnerability more, thus where the implementation of health improving policy will tackle the instability.
The methods of the project included basic descriptive statistics of CCJ rate, followed by percent change analysis, and OLS/GWR modelling. The full methodology can be found in the attached literature.
My key findings were as follows:
*Across England and Wales, using the time frame of 2001-2019, CCJ rate increased most after 2012 (coinciding with UK highest unemployment rate since 1993). This could be attributed to financially stabilising policy introduced by the government after the 2008 Crisis, which were gradually withdrawn, thus producing a delay in financial decline. Particular increase occurred in CCJ’s of £251-£500 in London, the North West and the South East.
*When including General Health and CCJ rate alone in the models, across all time frames (2011, 2015 and 2019), the strongest relationship between financial vulnerability and bad health occurs in Manchester, Birmingham, and London. The temporal and geographical consistency of this factor means policy makers may wish to target these areas with health-improving policy, to subsequently improve financial stability also.
*All GWR analysis showed the north: south divide in health-related financial vulnerability to be decreasing from 2011, to 2015 through to 2019, attributed to an increase in internal migration for students, professionals and retirement.
*When including the additional socio-economic variables, OLS and GWR analysis for 2011, 2015 and 2019 indicate that other variables have a greater influence on financial vulnerability than bad health (shown through a negative bad health coefficient), i.e. employment type, whose relationship with financial vulnerability remain positive.
*Regarding the North of England, the relationship between bad health and financial instability decreases. Policy makers should therefore shift their focus to an alternative medium with a larger influence two tackle financial vulnerability/indebtedness, i.e. employment.
I am looking forward to using the insight gained from my dissertation to take the ongoing analysis of Registry Trust data to the next level to inform public discussion on the economy as the ever-changing situation evolves.
Outside of work, I am a member of the local Athletics Club and enjoy socialising (albeit currently social distanced) with friends. I am also an avid reader of non-fiction (often internationally based, as since COVID has restricted my travel plans I must whack on the heating and envisage myself abroad instead!) Currently working from home up North, I am thoroughly excited to join the office and begin my life in The Big Smoke!
*The images shown are taken as extracts from the full dissertation document, and highlight the strength of the relationship (positive or negative), between CCJ rate (financial vulnerability/indebtedness) and the variable detailed above the legend. Please follow the link below to the document for additional key findings and explanations.