Data Governance in Fintech: Business Outcomes and Best Practices
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Data governance in fintech companies ensures data security and regulatory compliance while enhancing decision-making and operational efficiency.
This article offers insights into data governance within the fintech sector, covering regulations, business outcomes, and best practices.
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Table of Contents
- What is data governance in fintech?
- How data governance supports business outcomes in the fintech industry
- Data governance best practices for fintech companies
- Summing up
- Related reads
What is data governance in fintech?
Fintech (financial technology) is the technology that helps you manage your money — chatbots, mobile banking, stock trading apps, RegTech, crowdfunding platforms, cryptocurrency, and blockchain.
Data governance in fintech is a scalable way to ensure that the data captured by these technologies is secure, consistent, accurate, and compliant with the relevant policies, regulations, and laws.
How data governance supports business outcomes in the fintech industry
Data governance can help fintech firms with:
- Regulatory compliance
- Data security, privacy, and integrity
- Operational efficiency
- Growth opportunities and profitability
- Customer experience and satisfaction
- Innovation and competitive advantage
Also, read → Data governance in banking
Let’s look at four essential outcomes — data security, data privacy, operational efficiency, and regulatory compliance to understand the impact of data governance in fintech.
1. Regulatory compliance
One of the most significant outcomes for fintech firms would be regulatory compliance. The fintech industry is heavily regulated, and businesses must navigate complex laws depending on the region of their operation.
The regulatory landscape for fintech firms: Who oversees what?
In the US, the FRB (Federal Reserve Board), the OCC (Office of the Comptroller of the Currency), and the CFPB (Consumer Financial Protection Bureau) are examples of regulators. These bodies oversee rules and policies that all financial services firms, including fintechs, must follow.
For example, the OCC is responsible for the BSA (Bank Secrecy Act). This act focuses on Anti-Money Laundering (AML) compliance for fintech companies. All financial institutions must “develop risk-based AML programs to deter, detect, and report suspected money laundering, terrorist financing, and other financial crimes.”
Now, if you’re a US fintech with EU-based clients, then you must also comply with the EU GDPR (General Data Protection Regulation).
According to Bloomberg Law, this would include businesses that “use an EU language or currency, (offer) the ability to place orders in an EU language and (make) references to EU users/customers.”
On the other hand, if you operate in the EU, you’re subject to the ESMA (European Securities and Markets Authority). It oversees fintech investment initiatives in the EU, with increased scrutiny on cryptocurrency trading platforms, mobile wallet providers, and virtual currency exchange management.
Regulatory compliance is essential for fintech companies to avoid paying hefty fines, maintain brand reputation, and ensure effective data management.
2. Data security, privacy, and integrity
Data breaches occur when hackers exploit vulnerabilities, such as software bugs (Heartbleed bug in OpenSSL or the POODLE vulnerability in SSL 3.0 or ineffective security protocols (the DES and early SSL/TLS protocols).
However, insulating from such issues is challenging for fintech companies.
For instance, Cybersecurity Consulting Partner at EY India Aniket Bhosle highlights how classifying, encrypting, or tokenizing data assets is a complex endeavor for fintech firms.
“Data protection … is complex for a fintech (to do) as different organizations that they cater to may have their own policies and control requirements.”
Effective data governance can help fintech firms personalize data encryption and masking policies depending on the data source, domain, project, and more. This would lead to better data security, privacy, and integrity.
For instance, if your goal is to ensure data privacy and confidentiality at scale, then you can set up an active data governance and management platform like Atlan. This lets you map your entire data estate based on domains, confidentiality, integrity, availability ratings, and GDPR compliance. Once mapped, you can manage data access and use at scale.
Here’s how Ian Bass, Head of Data & Analytics for Austin Capital Bank, describes using a platform like Atlan for data governance:
“As we thought about data governance more and more, it became clear I wanted a tool to handle that. You really need an interface built on top of Snowflake so that you can easily see who has access to what. And that’s where Atlan came into the picture.”
With Atlan, Austin Capital Bank could control access in an easily repeatable fashion, track lineage, organize all information and classifications, and get context.
3. Operational efficiency
Another example is operational efficiency.
Without an effective data governance mechanism, data consumers at a fintech like Octane (Octane Lending, Inc.) used an internal Slack channel to ask questions about data. Data engineers would be responsible for answering them — they range from requests for further context on metrics to inconsistencies in spreadsheets.
Octane worked on standardizing their data, ensuring all assets had adequate context, and were easy to search and access. This reduced the support requests by 40% in three months, leading to time savings of 200 hours per month.
4. Growth opportunities and profitability
At the risk of sounding like a broken record, let’s state the obvious: good data can help you find growth opportunities.
Without data governance, finding the right data and then sharing it with the right people is a challenge. Leroy Kahn, Data Management Lead at Zip, a digital financial services company, echoes the sentiment.
Zip was modernizing its data stack to drive profitable growth. The company tied this business goal to a data-related outcome — improve data consumption by 20%.
“Our Data & Analytics teams and data users were finding it difficult to quickly, reliably, and easily share, find, understand, and use data to really unlock the value of our data platform and our data products.” Leroy Kahn, Data Management Lead at Zip
Zip managed to achieve its goal, driving cost savings and better business decision-making, by adopting Atlan’s active data governance platform.
Data governance best practices for fintech companies
Data governance in fintech can support business outcomes by enhancing data access, security, efficiency, trust, and compliance.
Here are three data governance best practices that fintech companies should follow:
- Staying informed and adaptable
- Conducting regular internal audits
- Establishing a compliance culture
Let’s explore each best practice further.
Staying informed and adaptable
“Given the increasing regulatory attention and the need to have controls in place to both know and treat customers well, a compliant company may well be more attractive to the public.” A Deloitte report on finance and regulatory compliance
Knowing what to comply with requires staying informed by keeping a close watch on global, regional, and local regulatory trends.
Fintech companies can do so by engaging directly with regulatory bodies, collaborating with traditional financial institutions, and using technology to automate and scale compliance.
Conducting regular internal audits
Fintech companies should conduct regular audits to ensure compliance with regulations and identify areas for improvement. These audits can include:
- Early and ongoing compliance testing
- Monitoring, evaluating, and improving AML policies
- Identifying ways to scale compliance programs
Collaborative audits with banks can help fintech companies navigate the changing regulatory landscape effectively.
Advice I give frequently to fintech companies: Do the relevant audits early (SOC II, PCI, etc). Banks + partners will require it, and starting when you are small is easier + sets a culture of compliance / security.— Zachary Perret (@zachperret) October 25, 2019
Establishing a culture of data governance and compliance
Data governance isn’t a one-time effort. It’s a continuous, organization-wide process that requires continuous learning and engagement for its success.
Continuous employee training on data governance importance and ROI, regulatory guidelines, data culture, etc. is essential. Ensuring the senior management’s active commitment is also important, as it sets a positive example and fosters a culture of compliance.
Great #fintech and #CapitalMarkets Panel - biggest cultural challenges post financial crisis are neither lack of senior management buy-in nor lacking support at the most junior levels but normally there is a gap and resistance to change in the middle #ifgs2019 #UkFW19 pic.twitter.com/BvFcOWaUui— Susanne Chishti (@SusanneChishti) April 29, 2019
Also, read → How to improve data governance
Data governance for the fintech industry is not just about compliance but also about achieving operational efficiency, data security, and ultimately, growth.
By embracing data governance best practices and adapting to the ever-evolving regulatory landscape, fintech companies can mitigate risks and unlock new opportunities to drive business growth.
Data governance in fintech: Related reads
- What is Data Governance? Its Importance, Principles & How to Get Started?
- KeyObjectives of Data Governance: How Should You Think About Them?
- Data Governance FrameworkExamples, Templates, Standards, Best Practices & How to Create One?
- Data Governance and Compliance: Act of Checks & Balances
- How to implement data governance? Steps, Prerequisites, Essential Factors & Business Case
- How to Improve Data Governance? Steps, Tips & Template
- 7 Steps to Simplify Data Governance for Your Entire Organization
- Automated Data Governance: How Does It Help You Manage Access, Security & More at Scale?
- Enterprise Data Governance Basics, Strategy, Key Challenges, Benefits & Best Practices
- Data Governance in Manufacturing: Steps, Challenges, and Practical Examples
- Data Governance in Retail: Best Practices, Challenges, and Viable Solutions
- Data Governance in Insurance: Why is it Important and How it Drives Positive Business Outcomes
- Data Governance in Healthcare: Benefits, Framework, and Tooling
- Achieving HIPAA Compliance with Data Governance
- Data Governance in Banking: Benefits, Implementation, Challenges, and Best Practices
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