Wed. Apr 17th, 2024

The phrase “digital transformation” is a common phrase to hear in the banking business. In banking, teams are always on the lookout for the next big thing, whether breakthroughs in controls in the 2000s, automation after 2008, or artificial intelligence and commercial analytics (such as Oracle Flexcube), in recent years.

Despite this, many chief financial officers (CFOs) argue that the rapid pace of Flexcube core banking advancement may give the impression that the needle is still motionless.

However, this is not a cause to give up on your own potential. Businesses must adopt new digital technology if they are to stay competitive and meet the requirements of their clients and consumers. The difficulty is to maintain focus on the most critical areas while also identifying and executing a strategy to address the most pressing issues that arise.

So, what are the most significant and high-value outcomes for the bank?

  • Real-time actuals reporting: Stakeholders are increasingly demanding that information and insights be supplied as rapidly as possible. This has been a significant emphasis of banking transformation over the previous decade. Many banking operations are experiencing an increase in the use of hyper-automation as a result of this trend (automatic judgment and process orchestration with the use of Oracle Flexcube universal banking). Traditional cycles will become more meaningless in a world where reality and projections are getting closer to instantaneous creation.
  • Self-service: Many business customers don’t need help with all forms of financial data, which is understandable. Automation of a wide variety of banking-related procedures is being implemented to free up bank departments to focus on more complex analytics, insights, and engagement with the rest of the organization. This involves everything from the preparation of financial reports to the investigation of budgetary issues. Finally, the goal is to replace data in spreadsheets with user-configurable dashboards that are straightforward and easy to use.
  • Improvements in forecasting, planning, and business intelligence skills: Rather than concentrating on automating routine financial accounting activities, technology suppliers are increasingly concentrating on assisting fast loan on app professionals who wish to add value to their organizations via innovation. Finance departments may benefit from analytical and artificial intelligence technology, which may help them make better and more timely choices by offering rapid forecasting, scenario analysis, and automated insight that results in better and quicker information for decision-makers.

Despite the fact that many organizations have identified and pursued these objectives, putting them into action is tough. A growing number of stakeholders are frustrated by the time and borrow money online associated with implementation, resulting in delays or deprioritization of the actual delivery of a product or service. According to our knowledge, the most common obstacles to change, as well as the methods by which banking services might overcome them, are as follows:

  • Allowing for the funding of discretionary expenses: It is challenging to acquire a budget if you do not adhere to all applicable legal and regulatory requirements. Financing for many contemporary technological advancements is sometimes cut because they are seen as “nice to haves.” If banks want to get corporate backing, they must demonstrate how new technologies can benefit the bottom line.
  • There is an issue with digital literacy: In many firms, data scientists and business analysts are taking the position of traditional accountants, which is a significant change in the profession. Numerous bank CEOs have expressed concern about a shortage of technology-based competencies in their present teams, as well as difficulties in recruiting qualified candidates from the market. Teams that have the potential to be upskilled inside the organization should be sought out and sponsored. Long-term recruits that can satisfy the company’s anticipated mid-term demand should also be sought out.
  • This is a risk-averse culture in which we live: Traditional banking requires meticulous attention to detail in all facets of the work. New technology is increasingly focusing on directed and indicative analysis in order to promote faster decision-making in the future. Lack of risk aversion and an excessive focus on correctness may make BAU deployments more challenging to complete successfully. It is necessary for banks to conduct a more thorough evaluation of what is “good enough” in order to ensure that perfection does not become the enemy of good.
  • Poor data infrastructure: It doesn’t matter whether a front-end solution is used; integrating the relevant data is often a time-consuming and complex task in and of itself. Because input data comes from throughout the company and is based on a variety of data models, this is particularly difficult for financial institutions. The truth is that there is no one method that works for everyone in this situation. However, even while automation may make the process of conveying and modifying data between systems easier, the need for strong human inputs, change control database updates, and you cannot ignore adequate data governance. Banks, in collaboration with CDO teams, must ensure that strong financial data governance is in place and get buy-in for remediating source data as well as moving toward standard data models wherever possible.

CFOs are confronted with a complex collection of difficulties, but this does not suggest that they should abandon their use of digital technologies, such as Oracle Flexcube 14.x.

Despite the apparently constant game of catch-up, substantial progress is being made. Establish a pipeline of employees ready to embrace digital, know when good enough is good enough, and repair data inaccuracies wherever possible. The banking teams that embrace change will triumph in the coming years.