Digital banks and other FinTechs are emerging as more nimble competitors to established legacy banks. The digital banks that are on their way to becoming fully chartered have the opportunity to set up fully automated processes and systems without legacy systems getting in the way.
As essentially greenfield sites, digital banks have the chance to eschew manual processes for many business functions, and regulators are actively discouraging them from taking a manual approach to their regulatory reporting obligations. Instead, banks applying for a charter need to prove they have a robust risk and regulatory reporting plan with the ability to be in production quickly and scale with rapid growth. The ability to quickly implement an operational platform to start business is a key consideration for regulators.
Many newcomers are electing to adopt automated reporting systems to meet the demands of the regulators while at the same time bringing significant operational benefits. These include reduced time to market, a reduction in errors and lower operating costs.
Applying for a charter is a significant undertaking for emerging digital banks. Putting in place sound reporting processes and systems that connect to your core banking data to data driven applications will help you accelerate and maintain your business applications, including; regulatory reporting, risk management, finance reporting, performance managements and business analytics. This will help you avoid the pitfalls of data inaccuracies that characterize legacy technologies and resultant operational disruption, and regulatory penalties endured by traditional banks.
So, what is needed to build a robust, integrated finance and regulatory compliant data management system?
Four Areas to Consider
New entrants can build a solid foundation for the future while demonstrating to regulators their commitment to putting in place the elements necessary to improve the financial health of their customers through superior technology and total transparency.
1. Align Systems Deployment with an Optimal Staffing Model
As with any early-stage venture, pre-charter banks are frequently challenged by limited access to valuable resources, and staffing is no exception to this. As a newly formed digital bank or aspiring bank, your staffing resources may have limited IT and regulatory and financial reporting expertise. If the business plan is to restrict headcount as the firm builds traction, it will be important to consider the technology solutions and partners you bring on board to help you scale.
This is where new ventures can benefit from the freedom they enjoy from the restrictions of legacy systems. Those building banks from the ground up have the luxury of following best practices from the outset. This extends to designing and implementing technology solutions that relieve existing staff from having to make manual interventions to, for example, adjust business rules to manage changing regulatory requirements, maintaining quarterly updates and other issues arising from the reporting process.
There are additional human resources benefits from implementing an optimal, future-proof technology platform. First, with no legacy systems to worry about, firms don’t need to hire legions of consultants to keep aging platforms running and up-to-date with today’s requirements. And with no end in sight to the current trend of working from home - necessitated by the Covid-19 pandemic - modern platforms offer banks the ability to manage systems remotely and the flexibility to hire and deploy staff around the country or even globally.
2: Put in Place a Robust Data Management Framework
To meet the rigorous demands of today’s regulatory and financial reporting environment, financial institutions need to implement a robust framework to manage data collection, normalization, integration and distribution in support of their regulatory reporting obligations.
To meet your every-day data driven challenges, consider how your core banking data might work with other data driven applications. Since BCBS 239 published principals for effective risk data aggregation, the banking industry was encouraged to achieve greater data standardization, implement greater controls and institute higher data quality – all resulting in higher levels of regulatory reporting accuracy.
This points to the need for a robust and industry-proven regulatory reporting solution. Regulators are demanding that regulated entities put in place first-class records-validation functionality to meet their data quality requirements. These systems must be able to identify and filter out data anomalies at the beginning of the platform’s ETL (extract, transform, load) data ingestion process.
This ETL validation process should engage at the data records sourcing and origination stage. It should continuously qualify all table records being ingested for key BCBC 239 data quality indicators, with checks for accuracy, completeness, validity, integrity and comprehensiveness. Finally, it should give users the flexibility to adjust these data quality dimensions to fit the overall objectives of the organization’s data governance framework.
With regulators keen to understand the provenance of the data in the reports they are receiving, the data management platform must provide data lineage capabilities that allow the bank to identify any changes to data records. This includes changes from source banking systems and rules transformation workflows. The platform must also offer standard integration, with support for end users, internal IT controls and data auditability.
This kind of greenfield data management approach further differentiates the disruptor offering from traditional banks, for which the crushing data management costs resulting from the 2009 credit crisis are being compounded by new disruptions from the Covid-19 pandemic. Digital banks can build a strategic data management system that aligns regulatory and financial data for operational efficiencies, analytics, and better business decisions as they grow – something that wouldn’t have been envisaged pre-crisis. Regulatory reporting data requirements now include substantial risk data elements, and new entrants need a platform that is sufficiently comprehensive in terms of its ability to handle a broad range of data if they are to take full advantage of the opportunity of adding a new system from scratch.