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Qlik: Why Explainability Is the Answer to Predictive Analytics Adoption in Financial Services

The digital acceleration brought about by the pandemic has been very useful in the fintech space, however, the one thing stunting long term success is the technology’s adoption. This adoption isn’t happening for one main reason: a lack of trust in the tech’s decision. 

Adam Mayer is the Global Products Marketing Manager at Qlik and has over 20 years B2B customer facing experience within the IT and Automotive sectors, working with internal and out-sourced manufacturing and marketing units in Europe, USA and Asia. He has a technical background in computing, underpinned by an incisive engineering perspective that supports effective product and marketing management strategies.

Using his expertise, Mayer discusses how Explainability is the answer to predictive analytics adoption in financial services and breaks down why the sector should not fear the decisions that are made:

Adam Mayer, Global Products Marketing Manager at Qlik
Adam Mayer, Global Products Marketing Manager at Qlik

There are many reasons why the financial services industry needs to get better at using its data. Compliance and regulatory requirements are inescapable. Less governed but no less important are customer service, product and service development. All rely on good use of data.

No more so than in recent times. When faced with a crisis such as the pandemic, decision-making needs to get faster, products more adaptable to changing consumer behaviour, and customer service even more responsive. It’s no wonder then that two-thirds (66 per cent) of IT leaders in UK financial services firms believe the pandemic has accelerated the use of predictive analytics to improve data capabilities.

Despite this acceleration, there is one big problem holding the financial services industry back from truly embracing predictive analytics – trust in the decision and how it was made. One third (30 per cent) of IT leaders fear not being able to explain predictive analytics decisions. This would be a problem in any industry, let alone one of the highest regulated that already spends $270billion per year on compliance and regulation.

Removing the fear around predictive analytics needs to be a priority for financial services if they are to unlock the potential of their data. It is an important part of the armoury of data technologies that will help companies move from a passive approach of consuming data to using it to derive Active Intelligence.

The solution? A focus on Explainability.

Explainable Business Intelligence

What is it? It does what it says on the tin. It provides the explanation behind where the insights that inform decision-making have come from and the data that it is based on. The data lineage revealing the source of the data, the governance that ensures data can be trusted, and the business logic applied to that data.

This information, together, creates a picture of the journey that data went through to transform from simply numbers to information that enables change. At its heart, Explainable Business Intelligence (BI) is about driving trust in data and the actions that it triggers. To give people across financial organisations confidence that the decisions they are making based on real-time intelligence and forecasts are the right ones, which in turn makes them far more likely to act in the “a-ha moment”.

Explainability is also important for fostering trust with customers as more advanced uses of their data are deployed. Indeed, one third (33 per cent) of IT leaders fear their customers won’t trust the decision made by predictive analytics solutions.

Ensuring that the implementation of advanced and predictive analytics capabilities don’t affect customers’ faith in their financial providers is especially crucial at the moment given the current low levels of trust, with just 14 per cent seeking help from their bank when experiencing a financially impactful life event in the past five years. As Richard Speigal, BI Centre of Excellence Leader at Nationwide Building Society put it, “we never want to make a customer feel like decisions were being made about them that couldn’t be explained. If you can’t explain how the models are built and can’t explain how they’re working, then there’s always going to be a question of trust”.

Empowering all employees – human or machine

Trust will only grow in importance as we see the human-machine partnership evolve. The value this partnership provides is inescapable, but that doesn’t prevent concerns around bias or lack of human oversight. Explainable BI helps drive trust in this partnership by removing doubts in the integrity of the insights it produces. Because, as Paul Carey, Data Management at HSBC said, “data quality is easier to achieve when the entire organisation knows its role in maintaining data integrity. Companies where everyone contributes to business intelligence are better able to steer towards success”.

‘Everyone’ in today’s modern financial services organisations, means humans and machines. The powerful forecasting of predictive analytics into the business intelligence platforms that already inform enterprise-wide decision-making is the perfect example of the partnership in action.

Data literacy – the ability to read, work with, analyse and communicate with data – will play an important in putting explainability at the heart of the organisation’s use of data for decision-making. Three-quarters of IT leaders believe it helps employees realise the limitations of and confidently question the output of predictive analytics (76 per cent respectively).

A similar number of IT leaders also believe data literacy will play an important role in explaining to customers and other stakeholders how decisions using predictive analytics are made (77 per cent), as well as in helping employees ensure their use of data complies with regulatory frameworks (74 per cent). So, if financial organisations are going to successfully seize the opportunities of predictive analytics, they need to ensure that employees have the skills to get the most out of it.

Grab hold of the Explainability lifeline

Replacing fear with trust is not something that will happen overnight. But it’s absolutely something financial organisations need to put work behind if they are to reap the benefits that predictive analytics and, in turn, Active Intelligence offer. Now is not the time to be tentative about the adoption of new analytics technologies. And Explainable BI offers a lifeline to those that may be drowning in indecision, concern or a lack of trust. Grab hold of it, and I guarantee you won’t look back.

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