A Digital ‘Tipping Point’ for Financial Services Business Models

The shift to remote work will endure after last year's 'digital tipping point', and more staff will handle data. But 2020's big success story is automation

Things are finally beginning to settle: After a year of uncertainty, three quarters of the financial services data leaders we surveyed now have a clear idea of what their post-pandemic businesses will look like.

Our survey of 100 US-based data leaders from financial services companies with at least $500 million USD in revenues also hints at how the turmoil of 2020 has already transformed the sector’s future. Three quarters of respondents confirm that their enterprises have rapidly digitized products, services and processes in response to the pandemic.

The picture that emerges is that COVID-19 catalyzed and accelerated a large number of digital transformation projects across the US. This has led some in the sector to label 2020 a 'digital tipping point' for the sector.

“Companies are investing more into digital capabilities, and there’s more emphasis on automating and taking the inefficiencies out of back-office processes”

John Hershberger, Financial Services Practice Leader, Wavicle Data Solutions

“Much like Y2K was great for building the first big internet iteration of data and analytics, COVID-19 has helped companies to focus on how people can be more productive,” says John Hershberger, Financial Services Practice Leader at consulting and development company Wavicle Data Solutions.

Jose A Murillo, Chief Analytics Officer at Mexican banking giant Banorte, agrees: “Banks that invested prior to the pandemic in digitization, artificial intelligence and data science are seeing the return on investment earlier than they thought they would.”

Digitally Enabled Business Models Here to Stay

It should come as no surprise that digitization was one of 2020’s key financial services industry trends. More than 40% of our survey respondents have finished digitizing both client-facing and back-office processes, while most of the rest say these transformations are now underway.

Our findings also show that many who were resistant to remote working before the pandemic now see its benefits. Some 63% of data and analytics leaders saw productivity gains across their organizations after shifting to remote working models.

It remains to be seen how much this change will endure. But many executives believe their companies will maintain a far more flexible attitude to remote working.

“When COVID-19 first hit, many organizations were shocked. They were thinking ‘How are we going to operate in this environment?’” says El Diawlol, Director of Advanced Analytics at Goldman Sachs. “But they were very surprised to see that most of their operations stayed operational.”

He adds: “Now, the trend is about how we can build a hybrid model between working from home and the office.”

At the same time, greater investment in digital channels has transformed how customers interact with financial institutions. For banks like Banorte, channels such as mobile will play a far greater role moving forward.

“You have to wrap up all the resources that you're devoting as a company into mobile,” Murillo recommends. “We need to devote much more physical, technological and human brain power towards that channel.”

Data Democratization Capabilities Starting to Mature

Data democratization is a cornerstone of data strategies at financial services and insurance companies. Goldman Sachs developed self-service portals stakeholders can use to uncover their own insights two years ago. Citi, Morgan Stanley and others have similar projects.

However, our research shows that most data democratization programs have yet to move past the ‘early adopters’ stage. Just 14% of survey respondents say most of their colleagues can now access the data that’s relevant to their role using self-service tools.

“Giving everyone the right to vote is not the same as everyone voting,” quips Dan Costanza, MD and Chief Data Scientist for Banking, Capital Markets and Advisory at Citi. “And giving everyone the tools and ability to use and think with data is not the same as getting people actually do it.”

He adds: “That's why we so heavily focus on individual adopters over an ‘if you build it, they will come’ kind of approach.”

“We have tried to stay within the kind of technological frameworks people are more comfortable with, but to reroute them slightly to improve the data model of those things”

Dan Costanza, MD and Chief Data Scientist for Banking, Capital Markets and Advisory, Citi

Costanza says the best approach is to focus on the teams that are most passionate about data, first. Once data leaders have built up goodwill in these teams and cultivated success stories they can share across the business, they will be able to expand their democratization programs.

Over the past 12 months, he has been using this approach to get his colleagues talking about the benefits data-driven tools and build wider buy-in for their adoption. The 32-year-old’s promotion to Managing Director at the end of 2020 is a ringing endorsement of the strategy.

Automation Emerges as 2020’s Big Success Story

Automation was biggest industry success story of 2020. Two thirds of the companies we surveyed have started automating client-facing business processes, such as auto-filling insurance policy forms.

“For certain banks, when you request a loan you are given a form to fill in,” Diawlol notes. “I don't think that that should be the case, with all the available technology.”

This trend is even more pronounced internally, with 77% of respondents reporting that they’ve started automating back-office processes.

AI is playing a key role in this transformation, with 64% of respondents saying they use AI tools for tasks such as automated underwriting or risk management. Another 19% plan to start using them within two years. 

“With AI doing the first screenings, your capacity is going to be bigger and the outcome is going to be much better”

Ren Zhang, Chief Data Scientist and Head of the AI Center of Excellence, BMO Financial

Ren Zhang, Chief Data Scientist and Head of the AI Center of Excellence at investment bank BMO Financial, says this trend is sparking sweeping change in the industry. She argues that AI adoption will help existing staff to be more efficient.

“Will it affect the existing workforce? Absolutely,” she says. “I think what will emerge is different types of skillsets, with people getting to do more value-added work.”

Zhang uses the example of fraud investigation to illustrate this point. AI tools can screen large numbers of cases to help humans focus the investigation on the most suspicious ones.

Relatively few companies are automating their data integration or ingestion processes today, but 64% plan to start within two years. This, too, will give data professionals more time to work on driving business value.

Financial Services After the 'Digital Tipping Point'

The financial services sector has invested heavily in data and analytics since the 2008 crash. But the crisis of the past year has accelerated business-critical transformations across the industry.

These silver linings have helped the industry build strong digital foundations during what has been a difficult time for people and businesses alike. The challenge now is to make sure data-driven capabilities are adopted, and to scale the best initiatives to transform organizations for the better.

“You have to empower your executives to be able make the right decisions,” says Diawlol. “Now that we’ve done all this investment, how can we drive growth based on these investments?”

This is an extract from our Future of Financial Services Data 2021 research. To discover even more about the data-driven trends that will shape the financial services sector this year, click here now to access the full report.