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From spreadsheets to suptech for financial sector market conduct supervision

Douglas Randall's picture

From Spreadsheets to Suptech for Financial Sector Market Conduct Supervision

Market conduct supervisors in the financial sector have a tough job. And it’s getting tougher.  

Their core work involves collecting data from disparate sources and undertaking complex analyses to identify and assess risks. They must also determine compliance with rules that are often principles-based. For example, what do complaints data, consumer agreements and marketing materials indicate about whether a financial service provider is treating its customers fairly?

But, increasingly, market conduct supervisors must also keep pace with financial sector innovations and supervisory mandates that are evolving to cover not only banks, but also financial cooperatives, microfinance institutions and new fintech companies - such as nonbank e-money issuers and person-to-person (P2P) lending platforms. And all of this in the face of significant resource constraints.

As a result, many market conduct supervisors are turning to technology, in a trend dubbed “Suptech” – that is, supervisory technology – to facilitate and enhance their work.

We and our colleagues just published a discussion note – From Spreadsheets to Suptech : Technology Solutions for Market Conduct Supervision --  in which we identify use cases for Suptech and provide case studies to illustrate how Suptech is being pursued by market conduct supervisory authorities in Brazil, Lithuania and the United States.

We see four main use cases for Suptech in the context of market conduct supervision:

  • Automated data collection: Suptech can improve the timeliness, scope, quality and granularity of collected data, and reduce reliance on manual processes. For example, a data-pull system can allow a supervisory authority to automatically access raw business data directly from a financial service provider’s management information system and aggregate it into a set of indicators and reports. Automated data collection can yield real-time granular data, create cost and temporal efficiencies, and free up staff resources from manual processes for tasks that require professional judgment.
  • Advanced data validation, analysis, and visualization: Suptech can be leveraged to clean and analyze unstructured data using natural language processing, for example for marketing materials or consumer agreements. Advanced analytical tools can be deployed to detect spikes and trends in key market conduct indicators —for example, to detect misconduct or a trend or rise in a certain type of potentially suspicious transactions.
  • Platform and database integration: Suptech can be deployed to merge disparate, often “noisy” data sets – such as monthly off-site supervision monitoring reports, financial ombudsman data, and credit bureau data - into a single platform or data set. These platforms and data sets can enable data validation, generate more efficient information flows and ensure that supervisors have access to the full range of data needed for effective market conduct supervision. 
     
  • Data management and storage: Suptech solutions, like cloud computing, can help to manage and store “big data,” enabling convenient on-demand network access to a shared pool of configurable computing resources (such as networks, servers, storage facilities, applications, and services).  The case studies illustrate how three very different supervisory authorities use Suptech.
The Consumer Financial Protection Bureau (CFPB) in the United States and the Bank of Lithuania use Suptech to collect, validate, and analyze complaints data, and then use that complaints data to improve identification of emerging consumer risks. For example, at CFPB, a spike in real-time complaints data may result in modifying the annual on-site examination schedule or deploying other supervisory tools to address the identified risk(s). In some cases, the CFPB has identified consumer risks based on real-time complaints data and reached out to the affected financial service provider, even before the provider was aware of the issue.

The Central Bank of Brazil (BCB) uses Suptech to facilitate remote supervision of AML/CFT regulation through a web-based communication platform. Since its launch, BCB has improved the quality, scope, consistency, and timeliness of data, more efficiently allocated staff resources, and improved the flow of information between supervisors and financial services providers. The platform allows BCB to supervise a large number of non-bank financial service providers in a cost-effective and risk-focused manner. More recently, the solution was integrated with other supervisory systems within BCB.

We also discuss several key considerations for supervisors in pursuing Suptech. First, supervisors and financial service providers must have adequate capacity to adopt technology solutions. Supervisors and policymakers will also need to continuously assess the appropriate balance between innovation, efficiency, and data protection and privacy.  It’s also important to emphasize that Suptech itself is not the goal. Supervisors should actively work with external vendors and internal IT staff to ensure that Suptech solutions are tailored to enable a robust supervisory approach.

Overall, we believe Suptech holds massive potential to improve the efficiency and efficacy of market conduct supervision, including to enable accurate and timely identification of risks to inform risk-based supervision of new fintech market entrants and digital financial services.

SupTech graph

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