HPD Software urges commercial finance sector to embrace data analytics
According to HPD Software, the time has come for the sector to embrace the concept of data analytics. A recent white paper launched by the business highlights that ‘those who fail to mobilise their big data strategy may potentially be left behind’.
HPD’s paper ‘Uncovering the benefits of data science in commercial finance’, highlights the need to centre data mining and analysis around a number of a core themes. These include: risk/reward, fraud reduction, customer retention, personalisation and business growth.
Kevin Day, CEO at HPD Software, said:
“There is no doubt the industry is playing catch up when it comes to making the most of its data. Historically it was kept for compliance purposes, but it wasn’t capitalised on. Risk analysis has always been there, but the technology has advanced and many commercial finance providers are missing out on opportunities to realise other business benefits from their data.
“The sector is maturing, and data science can support this trend by helping providers to understand their clients and use this insight to help them develop and grow. As the concept of data analytics has also grown, technologies have developed to support the entire data life cycle, providing real-time and predictive insights.”
The paper highlights some useful tips when embarking on a data analytics strategy. These include: starting small and with a proof of concept, setting parameters and defining objectives, quantifying the work and proving the return on investment and scenario modelling.
HPD also urges that when following the big data route, commercial finance providers should choose and focus on the strategy that is most appropriate to them and aligns with their business objectives, for example customer retention or maximising revenues.
Kevin Day said:
“Adoption levels will continue to be a challenge, but as more commercial finance providers start making the business case for ‘big data’ projects and investments, proof of concept exercises will go a long way to establishing consistencies. It’s time to make our data work harder in order to take a more customer-centric approach and reduce our exposure to risk.”
