At Hymans Robertson we take great pride in providing award-winning independent services to employers, trustees, and financial institutions, offering expertise in pensions, investments, benefits and risk consulting.

We’ve made it our mission to help clients secure better financial futures for their businesses, people and customers. And we’re increasingly turning to data as a tool to unlock better insights, innovation and decision-making.

In this session, three lightning talks will illustrate some of the different ways we’re harnessing data and modelling to deliver better outcomes for our customers and clients and enable better decision-making by our consultants and business leaders.

Lightning talk 1: First steps on the journey to become more data-driven: what we’ve learnt along the way, Ali Humphry

During this 10-minute presentation, Ali will describe how the firm’s administration business is starting to embrace data analytics to improve the customer experience for pension scheme members and the key lessons she’s learnt along the way. She’ll explain how the launch of a new customer web portal is changing the service delivery model and how data is helping to smooth the journey, using examples to bring this to life.

Lightning talk 2: Using Data Science techniques to promote cross-selling opportunities and understand client needs, Charis Chanialidis

Charis will attempt to summarise two (very different) projects that his team worked on over the last year during this 15-minute presentation. These will include how to use market basket analysis to identify clients who are most likely to purchase specific products, as well as how sentiment analysis can be used to understand client desires and identify clients at risk.

Lightning talk 3: Transforming financial data into risk management Insights, Ben Clare

The future is inherently uncertain, especially from a financial perspective. Ben is going to talk about how Hymans Robertson’s proprietary economic scenario generator helps clients in their risk management. He will explain:

· what an economic scenario generator is;
· how large sets of financial data and qualitative data are fundamental to the modelling;
· the use of data science-based techniques in our work; and
· the importance of strong governance.

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