Following a few years of disruption in the form of regulatory headwinds and challenging funding markets, the turbulence in fintech appears to be calming down somewhat. Even as it continues to innovate, the industry itself is maturing – and fintech companies are now more likely to be seen by banks as partners rather than competitors.
Still, risks remain that must be carefully navigated. Fintech companies need to put appropriate controls and safeguards in place. Striking the right balance between innovation and risk management will be key to thriving in the dynamic fintech landscape of 2025 and beyond.
The regulatory landscape for fintechs and bank-fintech partnerships is evolving, particularly where consumers are concerned. There is expectation of direct oversight of fintechs by the Consumer Financial Protection Bureau, and the Federal Trade Commission recently brought a claim against a fintech alleging deceptive consumer practices.
Although the new administration and Republican-majority Congress could change the environment, regulators have signaled heightened scrutiny and expectations through recent actions such as the interagency request for information (RFI) on bank-fintech arrangements.
The RFI underscores regulators’ view that bank-fintech relationships should be treated as business arrangements rather than partnerships, with each entity expected to operate independently with clear roles and responsibilities. Key areas of focus include the impact on banks of different sizes, bargaining power dynamics, and concentration risks such as liquidity, credit, and revenue reliance on fintech relationships.
Additionally, the Federal Deposit Insurance Corp. has proposed new deposit recordkeeping rules for custodial accounts with transactional features used in many bank-fintech models. The proposed rule would require banks to maintain direct, continual access to details on owners of these accounts.
While still digesting feedback, regulators have made clear that more rulemaking is coming to govern these arrangements more comprehensively. Also, with an expected increase in M&A activity, regulators will expect banks that invest in or acquire fintechs to have conducted appropriate, defensible due diligence and have integration and oversight plans in place.
Regulators’ salient message is that banks and fintechs must enhance governance, due diligence, and ongoing oversight as regulatory expectations increase. Additionally, customers and the court of public opinion will continue to play a role in why fintechs should take risk management and compliance seriously. Investing in the right controls, talent, and processes will be critical for sustainable participation in this rapidly evolving space.
As fintech companies expand their product offerings and services, obtaining a system and organization controls (SOC) report has become a market expectation to showcase their commitment to information security and governance. SOC reports issued by independent auditors provide assurance over the controls and processes implemented by a service organization, including fintech companies.
The two most common types of SOC reports are SOC 1 and SOC 2. A SOC 1 report focuses on the controls that are relevant to a user entity’s internal control over financial reporting. A SOC 1 Type 2 report evaluates the design and operating effectiveness of controls related to financial reporting processes outsourced to the service organization. The effectiveness of a SOC 1 report obtained by a fintech partner can allow a financial services organization to reduce the scope and effort required for its financial statement audits, aiding both management and external auditors.
SOC 2 reports take a broader perspective. Service organizations (in this case, fintech companies) must implement effective controls to protect their clients’ (financial services companies) data, focusing on one or more of the trust service criteria: security, availability, confidentiality, processing integrity, and privacy. The security criteria, which emphasizes protecting information and systems from unauthorized access, is mandatory for a SOC 2 report. The additional criteria are optional and can be included based on the service organization’s needs and the user entity’s expectations or requirements. A SOC 2 report is suitable when a service organization handles any sensitive data, extending beyond personally identifiable information, of a user entity and must demonstrate that it has effective controls in place to safeguard this information.
By obtaining SOC reports, fintech companies can demonstrate their commitment to maintaining a robust control environment and building trust with their clients. These reports provide transparency into service organizations’ processes and controls, enabling user entities, such as banks and other financial services organizations, to evaluate the risks associated with outsourcing critical functions to the fintech company. SOC 1 reports offer value to user entities by providing financial reporting assurance, enhancing audit efficiency, and supporting risk management. Meanwhile, SOC 2 reports deliver value through data protection assurance, effective third-party risk management, and compliance with security best practices. As a result, SOC reports have become an essential component of due diligence and vendor management processes in the fintech industry.
The AI opportunity landscape for fintechs is robust, but it also comes with its share of risks. Take the example of enhanced fraud detection and prevention. AI models can analyze large transaction datasets to detect fraudulent patterns in real time, such as unusual transaction amounts or locations. The successful implementation of AI can lead to reduced financial losses and improved customer trust through faster and more accurate fraud detection. However, success relies on the quality of the input data. AI models trained on low-quality or incomplete historical data might lead to inaccurate AI predictions in fraud detection, which is why data governance is such an important element of AI enablement.
As fintechs explore implementing AI to improve efficiency and capture insights, they will first need to confirm data readiness through effective data governance and quality measures. Successful AI implementation hinges on having trustworthy, high-quality data inputs.
Data governance establishes the vital framework for managing data as an enterprise asset, and it defines clear ownership, roles, and responsibilities for data stewardship. Fintechs should put robust processes in place for monitoring data quality, ensuring accessibility while controlling access to sensitive information, and maintaining data security and integrity. Regular communication and training can help reinforce data governance across the enterprise.
Assessing data maturity is key to understanding gaps and establishing a road map for data readiness that can enable AI. Data maturity reflects the capabilities regarding data management and governance processes, as well as the ability to derive value from data assets. Even fintechs at a relatively low maturity level can benefit from focusing on the foundational areas of data governance – people, processes, and technology.
Data quality management – which involves implementing controls and validation rules to promote data accuracy, consistency, completeness, and integrity – is fundamental to data governance. Disciplined data profiling and monitoring provide visibility into data quality levels. By proactively addressing data quality issues, fintechs can avoid the “garbage in, garbage out” pitfall that plagues AI and analytics initiatives.
Data classification categorizes data based on its sensitivity, value, and regulatory requirements, and it helps determine how data should be stored, processed, and shared for AI use. For example, personal or sensitive data might require encryption, limited access, anonymization, or exclusion altogether before being used with AI models. Popular AI use cases often involve data subject to privacy laws and regulations. Consider the scenario of providing real-time customer support via an AI agent. Customers might ask questions that lead to their sensitive information being exposed to an AI agent whether required or not. While the value of enhancing operational efficiency and driving customer satisfaction is significant, it’s important to exercise proper governance over data to mitigate these risks.
With a solid governance foundation and high data quality standards in place, fintechs can confidently explore AI use cases, knowing that their data assets are reliable and well managed. AI readiness requires this robust data backbone in order to succeed and to scale AI adoption while mitigating risks.
As the fintech industry matures, the future of bank-fintech partnerships will be shaped by evolving expectations, regulatory requirements or guidance, and the need for continual adaptation. Both banks and fintechs are raising the bar in response to regulatory pressures, customer expectations, operational resilience considerations, and the pursuit of profitability. Following are four key areas of focus for the foreseeable future.
The future of bank-fintech partnerships lies in striking the right balance between innovation and risk management. By embracing rigorous due diligence, prioritizing operational resilience, pursuing profitability, and cultivating top talent, these partnerships can unlock new opportunities while navigating the complexities of an ever-changing regulatory and technological environment.
From AI transformation to SOC reporting, we can support your fintech company as it turns new challenges into big opportunities. Reach out to learn more about how our specialists can help you.