Use of data can also help combat financial crime. For example, many financial services firms are using artificial intelligence (AI) tools to identify potentially fraudulent activity and act quickly to stop it – such as putting in place algorithms which will stop a credit card displaying unusual activity. This is particularly important given the rise of cybercrime and scam activity following the Covid-19 pandemic.
Another potential benefit for customers is greater accuracy and real-time information about the performance of their investments; and amid calls for more environmentally friendly and socially conscious investing, the combination of data from several sources could help show the true carbon footprint and climate risk of a company.
Challenges and risks
However, there are some significant challenges faced by the financial services sector as it tries to benefit from data-driven opportunities. Attention needs to be given to the regulatory framework within which financial services businesses need to comply in their use of data.
That framework is not limited to complying with the General Data Protection Regulation and other applicable data protection laws. Some regulatory requirements will take effect even in circumstances where data use is critical but does not relate to specific individuals.
The FCA’s Consumer Duty, ESG and operational resilience requirements may all be relevant to the data management governance processes and controls which financial services businesses put in place. Ensuring that the provenance of data is known and does not impinge on the commercial rights of other organizations also needs to be addressed.
These legal and regulatory concerns can become more pronounced where data collaboration opportunities arise. Where data sharing arrangements are in place, consideration should be given to the extent to which the financial services business has visibility over its collaboration partner’s data governance.
Potential data quality concerns including timeliness, consistency and completeness of datasets could present significant risks to the usefulness of data if effective due diligence has not been undertaken of a potential collaboration partner’s data management arrangements. Ensuring that findings in due diligence also translate into contractual commitments to ensure the quality of data provided will also enhance the opportunity to maximize the benefit of the collaborative arrangement.
Any financial services businesses moving forward with new data-driven strategies need to ensure that there is alignment within their business across key functions. This includes risk and compliance, legal and privacy, data governance and quality, information security and technology functions.
There is a good reason for all financial services businesses to have in place data-as-an-asset strategies in order to grow revenue and maximize the benefits that can be gained from data insights. Effective data management processes and controls which take note of the legal and regulatory landscape in which data can be used can provide a solid foundation for maximizing the value of data and innovating quickly with it.
Co-written with Hannah Ishihara of Pinsent Masons.