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Financial services relies heavily on unstructured data
And protecting it has become more critical than ever before

Superna helps the financial services industry

protect its most valuable assets

Emerging technologies and collaborative workflows add complexity to protecting unstructured data:
Unstructured data in Financial Services

Financial services firms leverage advanced analytics, artificial intelligence (AI), and machine learning (ML) techniques to extract insights and value from unstructured data. By analyzing both structured and unstructured data, they can enhance risk management, improve customer service, identify potential fraud, and gain competitive market advantage.

Examples of unstructured data used in financial services include text, including email, social media posts, customer reviews, research reports, and legal documents. Audio data might include customer service calls, meetings, conference, and speech-to-text technologies. Video includes recorded webinars, training sessions, surveillance footage, and video conferencing data. Photographs and scanned document images are used for identity verification, document processing, and fraud detection. And unstructured market data might include unformatted financial reports, news articles, and analyst notes.
Unstructured data typically lacks organizational. Without clear labels, metadata, or defined data fields, it can be difficult to classify and even more challenging to identify sensitive data requiring protection.
Comprising a multitude of formats, including Word documents, PDFs, PowerPoint files, images, audio files, and multiple video formats, creating a consistent and effective security strategy can be a challenge.
With unstructured data being generated by a multitude of sources – including social media, emails, documents, images, and videos – the sheer volume and rate of growth requires the ability to easily manage across different storage types and regions, adding to the challenge of identifying and protecting sensitive information, along with maintaining regulatory compliance.
Lack of Organization
Data Volume
Inconsistent Formats
Unstructured data is frequently shared among different stakeholders – including medical professionals, insurers, patients, even artificial intelligence – creating yet more unstructured data – making it difficult to restrict access to sensitive information and prevent data leakage.
Unstructured data is often stored across several locations – from shared drives and mobile devices to cloud storage across multiple regions – making it difficult to keep track of and adequately secure.
Frequent Collaboration
No Centralized Storage
When it comes to protecting unstructured data – data that doesn't fit nicely into a traditional database structure, such as emails, documents, audio recordings, and video files – the financial services industry faces some unique challenges:

  • Cybersecurity threats: The financial services industry is a prime target for cyber attacks, and unstructured data can be especially vulnerable to these attacks. Hackers will typically exploit vulnerabilities in email and file-sharing systems to gain access to sensitive data.
  • Data volume and complexity: The financial services industry generates vast amounts of unstructured data, including emails, documents, and other types of files. This presents a challenge around storing and securing the data, as well as ensuring that it is easily accessible to authorized users for collaboration.
  • Regulatory compliance: The financial services industry is subject to various regulations, such as GDPR, PCI DSS, and FINRA, which require businesses to protect sensitive data and prevent unauthorized access to it. However, unstructured data can be challenging to manage and secure, which makes compliance with these regulations that more difficult.
  • Data silos: Unstructured data is often spread across multiple systems and departments, creating challenges in terms of accessibility and data sharing or collaboration. This makes it difficult to identify and respond to cybersecurity threats and ensure compliance with industry and regional regulations.
  • Insider threats: Insider threats – like employee theft or negligence – pose a significant risk to the security of unstructured data. Employees may accidentally or intentionally share sensitive data with unauthorized parties, or fail to follow established security protocols leaving it exposed to hackers, ransomware, or exfiltration
Protecting unstructured data requires a multi-faceted approach that involves implementing effective security technologies, compliance with regulatory requirements, ensuring data accessibility for sharing and collaboration, and implementing robust policies and procedures to control access to sensitive data and to mitigate insider threats.

Superna understands financial services



Protecting unstructured data requires a comprehensive strategy that includes data classification, encryption, access control, employee training, and regular security audits.


For more than a decade, Superna has been at the forefront of protecting and managing unstructured data around the globe. From workflow automation to data classification and management, to data tiering and archiving, our tools, technology, and domain expertise help ensure that your unstructured data is protected, secure, and available whenever and wherever you need it.

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