Delegates gathered at this year’s Financial Information Management (FIMA) conference in London, titled ‘Optimising your data strategy’. Some of the main topics at this year’s event included data ethics, cloud innovation and modernising regulatory reporting. The conference encouraged interesting debate surrounding data ethics, and delegates discussed what people can practically do in this area.
Discussing data ethics, one speaker said in a panel that people need to understand what the right thing to do is when it comes to dealing with data. The panellist said: “It is about weighing up particular choices and forming a structure that defines boundary lines for people over what is right and what is wrong.”
They continued: “It has to start with a discussion that forces people to think about their decisions and their accountability around data ethics. There should be a framework in place that enables people to think about what the right decision would be in a certain scenario.”
One panellist advised industry participants to use data that is proportionate to their business needs, saying that there is a set of framework rules that can be applied. Explaining this further they advised industry participants to ensure robust practices and to work within their skill set, adding that they should make sure their work is transparent and that they should be accountable for those decisions and use data responsibly.
Meanwhile, another speaker said: “Ultimately, we are all profit making and whilst you want to monetise, you also need to do so in a way that is ethical, which is always a hard balance to strike.”
The moderator noted: “If this was easy there would be no ethical dilemma—there is no one clear answer here, there is just a lot of opinions and we need to apply the framework to get some level of transparency”, he then asked the panel if they had to adjust their strategy to cope with data ethics.
In response, one panellist replied: “Yes, we have had to act and adjust. Ethics is something that is continuing to grow. Conversations around data ethics are starting to happen more rapidly and we will see more of it over the years.”
One panellist added: “Of course we have to adapt but because most large organisations have an ethical framework in place, the focus is more about data. In our case, we do have something available.”
He added: “What I find fascinating in the industry is the emergence of environmental, social and corporate governance (ESG). Firms have started to think about the environment so all of these things are starting to make an appearance in the industry.”
While the panel was in session, a live poll found that some 47 percent fully agreed to the statement that ‘General Data Protection (GDPR) determines what can be done with data, while data ethics address what should be done with data’. Some 44 percent agreed, 7 percent disagreed, and 2 percent fully disagreed.
In another session on the first day of the conference, Olivier Colinet, cloud leader, financial services, EY, said that cloud is a business transformer, not a technological shift. He explained that “cloud is a disruptor and it is about considering cloud as a business accelerator”.
Colinet added: “Clarity over compliance remains the key barrier to cloud adoption”, and he drew upon his presentation which questioned the possibilities of being able to demonstrate to the regulators a real-time view of controls in a format they recognise. He asked: “And what if you were able to be alerted to shadow IT the moment someone spins up a new system?”
Colinet also stated that cloud is about changing the mindset and he looked into what the ‘new normal’ might look like. He said: “All security safeguards are to be broken; instead detect new threats and respond rapidly—an open versus walled garden security model.”
He added: “Data creation, data exchanges and data inputs may at times escape corporate policies, shadow IT and set controls to get alerts in real-time.”
Meanwhile, discussing the opportunities around cloud, Colinet highlighted that the cloud offers unparalleled opportunities and he drew upon the data quality (DQ) regulations and data quality machine learning (DQML) tool. Clients want to know what the cloud looks like, therefore, EY has been investing in using visuals to translate the value of using the cloud, Colinet revealed.
He said: “The EY DQML tool is a mobile responsive application that enables clients to detect and address data quality issues such as duplicates, missing values, outliers and address verification using advanced machine learning algorithms and models.”
“Moving to the cloud isn’t simple—it is important to use the cloud as a journey and driving metrics behind these initiatives is crucial. Drive cloud adoptions, deliver on cloud vision, and lead cloud transformation.”
He also suggested that cloud is paramount in building the bridge between cloud and business. He commented: “It is about finding innovative and disruptive ways of doing things as well as the agility and the speed of doing things.”
“It is an exciting time, being able to see how the cloud can be transformational in your organisation. We believe that cloud is the new IT.”
He also cited that the mindset needs to change around the cloud, adding that we are operating in an open environment rather than a walled garden.
Colinet advised: “Cyber is operating in an open environment and the same environment applies to data. It is important for CTOs to set the right controls in place. Architecture is becoming a commodity so don’t stop yourself innovating and using the full power of the cloud.”
On day two of the conference, Sanjay Saxena, head of data governance at Northern Trust, said that the industry “must move the needle” beyond what it can offer in the data space. In a presentation, entitled Monetising Data, Saxena questioned what exactly exploring data meant and what it means on the industry’s journey as it moves forward.
Saxena stated that more must be done to manage the quality and quantity of data beyond regulatory targets.
He commented: “Speakers here this morning have already talked about the quality and management of data. We have to move beyond regulatory initiatives [for firms] to become an effective data company. We should be promoting values around culture and quality of data, which is what we are doing at Northern Trust.”
He stated that data must be given in a consumable form, aimed to enhance insights for the customer and, it must, he said, offer as many monetary benefits as possible.
He added that in particular, there should be a stronger partnership between data and product groups to build data-centric products.
To move forward, Saxena said firms should ensure that they do not cannibalise existing products and should make privacy concerns paramount to their business model. Saxena also stated data aggregation across many different firms is becoming a new disruptive business model.
Looking to the future, he predicted the shift toward data-centric business models will be slow and will require additional investments in architecture, data platforms and data governance.
In another panel on ‘Re-imagining Your Data as a Commercial Proposition’, one panellist said that chief data officers (CDOs) should be at the top of the tree of coordination for any firm in financial services.
They said: “Going forward, understanding data is mandatory in the regulation space, and if [firms] do not understand and utilise data [they] will not survive in the industry, and will see no progression.”
The speaker added: “You need to have a strong CEO and CDO who project confidence to the regulator and create capabilities that clients can easily access and utilise. You must understand where exactly your data is coming from and always question its accuracy.”
They stated that people within the financial industry did not fully understand the notion of data strategy as an asset even five to 10 years ago. The speaker also added that since the financial crash of 2009, the industry understands the notion of operational risk much better.
Since then, the speaker said, data has been treated as a mindset. The panellist concluded that it is imperative to “constantly know that your data is there for where and when you need it”.
