Finance teams are bottlenecking banks’ digital transformations
- Thanks to digital, banks' finance teams are no longer just the scorekeepers that report the company numbers, they're just as responsible for processing data and mining business insights
- RPA and big data technologies are becoming the new Excel skills for finance employees
Blame the finance department.
Banks are working hard to beef up their technology and innovation teams, embrace agile development and move to acting like digital companies, but bank finance departments still do a lot of manual work and will start to hold their companies back from becoming digital entities. Finance teams are the control functions and scorekeepers of an organization, but if they can’t process data at the same speed as the rest of the organization they could slow down the speed of company mergers or product rollouts when competing transactions are already taking place.
“In the last month or so I’ve talked to four or five CFOs who said, ‘we’ve invested a lot in improving finance but we’re recognizing, given the pace of change, that finance really isn’t in a position to be agile,’” Keith Novek, a principal at EY and the lead in its financial services financial management practice.
If finance can’t move as quickly as some of its colleagues would like, it’s because of the vast amount of data pouring into financial firms, which now doubles every couple years. That’s a big change to contend with for a CFO tasked with collecting and analyzing data, meeting financial and regulatory reporting, improving operational efficiency both from firm and finance itself — as well as providing controls and extracting business insights from that increasing mound of data. So while the objectives of the CFO role haven’t changed much, the pace to react has changed significantly.
“The biggest hurdle that CFOs in finance functions need to overcome is data,” said Kurtis Babczenko, a banking and capital markets advisory leader at PwC. “The challenge these days is we’ve moved far beyond just the finance function reporting debits and credits and producing financial statements to the amount of granular data required for them to produce regulatory and capital and liquidity reports. Getting their arms around that granular data is the biggest challenge.”
It’s been a discussion among banks for the last year, but Novek said their sense of urgency has started to build in the last three months. They’re looking more now at how to enable agility in their operating model; other areas of the bank are doing it already, but “kind of dragging finance along,” he added.
In the last week, financial firms have begun talking with EY about efforts to centralize innovation within the finance departments so they can evolve incrementally and continue to improve, rather than waiting for “a big bang change,” said Novek, who could not provide further details on the firms and initiatives involved.
“Innovation” in the finance department usually means process automation; implementing technologies that can help them read large quantities of data in less than half the time and cost of traditional methods. Finance has a key role in making sure the data is accurate, sourced from one place, that it’s controlled and not manipulated. There are a number of things driving organizations to make sure their data is correct, including pressure from regulators to prove the data is correct in all its different movements across the organization.
Traditionally, digesting data and doing the required regulatory reporting could take 18 months with a team of 30 people and cost about $10 million, plus a $500,000 license cost for database software, for a mid-sized bank. Recently, EY helped a bank do the same thing with a different, more automated approach that took seven months, seven people and about $3 million.
Finance’s slow digital shift is also demanding greater technological expertise from its incoming employees.
“Technology skills in finance as a capability are no longer an option,” said Todd Rebella, EY’s digital finance lead for the financial services practice. “In the same way we would not expect five years ago for a finance employee to be Excel illiterate, we look at robotics and data techniques as what will be the equivalent of today’s Excel skills for a finance person.”
Industry observers agree the evolving role of finance and overcoming its data challenges will be a growing theme next year, but the work required to see real progress will go beyond 2018.
“The industry has been very focused on data for several years now,” Babczenko said. “They’ll continue to have data as a top of mind issue as its the foundation for everything they need to do going forward.”