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Four factors businesses need to consider when it comes to automation and decisioning

As we enter a new decade, many financial providers plan to harness the power of automation and invest in advanced analytics such as Machine Learning and Artificial Intelligence to help transform their processes.

With this transformation, many are currently investing in major projects to bring together disparate data sources together into one coherent framework. And although a central, accessible data source is essential, organisations need to consider several factors if they want to take full advantage of the myriad of ways data can improve decisioning, efficiency, and customer journeys.

Here are four aspects businesses need to consider:

Relevancy of data

Previously, the temptation has been for organisations to gather as much data as possible. However, the more that is being handled, the greater risk there is of data-quality issues. More than 99% of data held by organisations today is never actually used and regular audits can cause significant strain – a better approach would be to identify potentially valuable data sources in the first instance.

New data sources

As part of the process of centralising decision making, businesses will want to consider new data sources that have been shown to add value to the automation process. These include social data, geo-demographic data, bureau data and economic data and which can then be fed-in to automated systems to deliver the desirable outcomes.

System issues

Most organisations’ ambitions can be limited or curtailed entirely by their legacy systems. Traditionally designed to fulfil a very specific function, additional systems are added on a piecemeal basis, leaving a confusing maze of architecture which require bespoke workarounds to address new problems.

As organisations move towards a more data-centric framework, it makes sense to adopt systems that can cover the whole credit or marketing cycles, with system designed to be flexible and cater for a mixture of automatic and manual processes.

Exploring new models

Transforming data into information and insight is essential to understanding customers and approaching them with the appropriate communication. This process typically involves understanding what data adds value and then building an appropriate model.

With the right automated systems in place, new models and data sources there is an exciting opportunity to personalise journeys and engage better with your customers across channels. Furthermore, businesses can ensure that any decision is accurate, and efficient.

The future

The use of software to automatically make choices in business is already here, with society reaping the benefits of automation for years. Alongside analytics new, and better management of, data plays an integral role.

New data sources fed into automated systems, can offer more accuracy and more inclusive decisions – bolstering both the organisation and their customers’ experience of it.



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