Financial services firms: How transparent company data can power risk management activities

Financial services firms are among the hundreds of organisations that use transparent company data at scale. Legacy banks, FinTechs, payment service providers and challenger banks all need a foundational understanding of which companies exist in the world to carry out their risk management activities effectively. 

But firms are increasingly looking to gain a competitive advantage by using company data to power their data management programmes, to aid the application of data analytics to drive insights and to improve their customer experience.

In this blog, we explore why financial services firms of all kinds can benefit from leveraging transparent company data.

Compliance & risk management

Compliance and risk management are core requirements for any financial services firm, and these activities are done best when they use high-quality traceable data sources. 

Regulatory pressure around financial crimes and third party risk management is especially increasing.

Critical compliance processes that leverage company data include:

  • Ongoing monitoring
    Regulators expect firms not just to rate the risk of a client before onboarding, but to review their risk rating on an ongoing basis, sometimes termed ‘perpetual KYC’. This requires data that illustrates how and when a client’s risk profile has changed by capturing, for example, a change of status in the company or the addition of a new director. 
  • Supply chain and third-party risk management
    Like any major corporation, financial services firms often have long and complex global supply chains which carry risks that need to be identified and managed. Transparent company data is critical for giving companies the intelligence they need to mitigate these risks and create actionable insights. We discussed this further in a recent blog.
  • Financial crime investigations
    Financial institutions are mandated to investigate suspicious activity and file Suspicious Activity Reports (SARs) with regulators. But in order to do this effectively and efficiently they first need workable and complete datasets.

    Companies can often find previously-invisible red flags in datasets such as sanctions lists, politically exposed persons (PEP) lists and customer transactions if they merge this data with an authoritative dataset of legal entities and apply data analytics tools. Knowledge graph technology is an example of this, with innovative firms using it to pull together previously disparate datasets to identify red flags.

Data management

We are increasingly seeing creative use of our data by companies to gain a competitive advantage over their rivals. Challenger banks and FinTechs have stolen a march on traditional banks by developing their data infrastructure from the ground up, and traditional banks are responding by overhauling their often-siloed legacy data systems. 

In this context, transparent company data can aid a firm’s data management efforts:

  • Master data management
    Financial institutions usually manage multiple systems with information about their customers, which often leads to issues such as duplicate entries for the same client. Some firms are trying to solve this problem by creating a master dataset – acting as a golden source of ‘who’s who?’ for their counterparties. Our data can add value here by being the quality reference point for the universe of companies that other datasets are then layered on top of.
  • Innovation: Training AI & machine learning models
    Many firms have set up innovation hubs and centres of excellence where they apply AI and machine learning technologies to drive insights, improvements and cost savings for different parts of the business – from customer experience to marketing to risk. These centres need high-quality datasets to train their engines on, whereas using inaccurate, out-of-date, or solely customer-provided data invariably leads to poor decisions. The insights from technologies such as machine learning after all are only as good as the data powering and training them.
  • Analytics
    Financial institutions increasingly use data analytics to create insights that wouldn’t otherwise be possible. Analytics tools can only do this if the data you have is easy to combine with other datasets – such as through the use of open identifiers for companies. 
  • Entity resolution
    Firms must juggle various datasets with multiple references to customers (whether people or companies) that may or may not be the same entity. We have seen legal entities identified by their address in one dataset, their business name (sometimes spelled in different ways) in another, and the name of their street in another. Our reference dataset of legal entities helps firms to clean up their data by reconciling different references to a legal entity into an authoritative record.

The list above is just some of the functional areas where transparent company data can add value to financial services firms.

Get a competitive by exploring how transparent company data can aid your firm.

Find out more about our data >

You may also be interested in…

  • Manage supply chain risk with transparent company data 
    Read our blog on how our data helps companies to get the intelligence they need to mitigate rising risks in their supply chain.
  • Why legal entities are the building blocks of the modern world
    Read our blog on why high-quality and provenanced legal entity data is needed today more than ever before. 

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s