Skip to main navigationSkip to main content
The University of Southampton
Southampton Business School
(023) 8059 8964

Dr Mee Chi (Meko) So BSc, MPhil, PhD, FHEA

Associate Professor in Business Analytics

Dr Mee Chi (Meko) So's photo

Dr Mee Chi So is an Associate Professor within Southampton Business School at the University of Southampton.

Dr Meko So is an Associate Professor with expertise in credit scoring and marketing analytics.

I obtained my first degree and a master’s degree major in Operational Research from the University of Hong Kong. In 2009, I completed my Ph.D. at the University of Southampton. In my Ph.D., I collaborated with two large banks in UK and Hong Kong to look at how to derive optimal credit limit strategies for credit card lenders.

In 2011, I took up the position as a Research Facilitator at the University of Southampton. Since 2013, I have taken up the Lecturer position. Apart from my academic education and experience, I was a CRM analyst in B&Q and a market research analyst in the international company IDC.


Throughout my career, I have developed expertise in predictive analytics, consumer credit risks and marketing analytics. I am particularly interested in using large-scale real-application datasets to deliver actionable insights for organisations. I have participated in a number of consultancy or MSc projects to collaborate with a wide range of organisations such as the UK Financial Conduct Authority, Global Radio, Lloyds Banking Group, United Health, etc.

In 2014, I was awarded a Knowledge Transfer Partnership (KTP) grant (£142,000) funded by Innovate UK for a two-year project to work with the company AppLearn to deliver an analytical software product measuring employees’ adoption and engagement. In 2015, I was awarded a research grant by EPSRC (£375,755, FEC) for a 30-month project 'Dynamic pricing in the ferry industry'. This project aims to develop a set of models to estimate the ticket prices which maximise revenue for ferry operators. Through working with P&O Ferries and Red Funnel, this project will use real data to inform the models.


I have taught both undergraduate and postgraduate level courses. I was a visiting lecturer at Department of Mathematics of Cardiff University teaching a postgraduate module Credit Risk Scoring.
I am one of the investigators of a bid awarded by Her Majesty’s Revenue and Custom (HMRC) to deliver Master’s level quantitative skills courses to the employees of HMRC.

Staff Member

CORMSIS, Centre for Operational Research, Management Sciences and Information Systems

Research interests

  1. using actual data (big data) to draw actionable insights for retailers to improve product pricing
  2. the use of social network data to improve the performance of customer-level predictive analytics models
  3. modelling the behaviour (e.g. churns, defaults, etc.) of transactors and revolvers of credit card holders
  4. modelling the debt collection process with Markov decision models

I am welcoming PhD applications to study the above topics, or other topics in the predictive analytics, marketing analytics and consumer credit risk areas. If you would like to pursue a PhD degree and are interested in applying mathematical and statistical techniques in application-oriented topics, please feel free to contact me.

Moreover, I work together regularly with my colleagues (including, Bart Baesens, Kasia Bijak, Cristian Bravo, and Christophe Mues). We welcome any students who are interested in studying a PhD degree with our joint supervision.

Research Projects

Dynamic Pricing in the Ferry Industry

Please email me for further details.

Sort via:TypeorYear



Working Papers

Modules teaching currently:
  • MANG6331 Text Mining and Social Network Analytics
  • MANG6230 Data-driven Marketing
Modules taught previously:
  • MANG2043 Analytics for Marketing
  • MANG3056 Data Mining for CRM
Dr Mee Chi (Meko) So
Southampton Business School, University of Southampton, Highfield, Southampton SO17 1BJ, UK

Room Number: 2/4016

Share this profile Share this on Facebook Share this on Twitter Share this on Weibo
Privacy Settings