data migration risks

5 Major Data Migration Risks

Migrating data between systems presents significant risks for investment firms utilizing outsourced services and technology providers. This blog aims to outline the typical risks associated with capital markets data integrations and suggest mitigations to facilitate a successful transition phase.

During system transitions, normal Business as Usual (BAU) procedures are disrupted.

For instance:

  • Encrypted system-to-system connectivity like MQ, sFTP and API’s may shift to less secure methods like email transmission of TXT, CSV, or Excel files.
  • System-enforced maker-checker controls may be replaced by procedurally enforced controls built into daily procedures.
  • Significant manual data manipulation with minimal audit trails may become necessary.
  • A ‘hit & hope’ approach to file uploads to destination systems may be adopted.

These changes introduce significant stress and risk to the production environment, often considered a temporary state that must be endured.

Identified risks include:

  1. Account Information Security Breaches:
    Incorrect client information leakage or sharing incorrect fund data can lead to security breaches. According to the Securities and Exchange Commission, eight firms faced sanctions due to cybersecurity failures resulting in email account takeovers, exposing the personal information of thousands of customers and clients at each firm [1].
  2. Data Mapping Errors:
    Incorrect mapping of source data can result in loading incorrect information into target systems, leading to long-term errors despite post-upload quality assurance checks. Data mapping is crucial for establishing relationships between different data entities and reducing data redundancies for reliable data analysis [2].
  3. Increased Manual Intervention:
    Environments with substantial manual intervention tend to have higher error rates, demanding increased human resources. Financial institutions have faced challenges due to flawed manual processes, resulting in significant financial losses [3].
  4. Reputation Damage:
    Issues during the data migration phase can negatively impact subsequent phases, affecting customer service, reputation, and regulatory compliance. Poor data migration processes have led to disruptions, data loss, and reputational damage in the financial services industry [4][5].
  5. Regulatory Challenges:
    Meeting regulatory deadlines and requirements may pose additional stress and challenges to the team. Financial services institutions face growing regulatory burdens, including rules governing privacy, cybersecurity, data handling, and artificial intelligence, along with requirements for environmental, social, and governance reporting [6].

Neglecting these risks can cause substantial economic, operational, and reputational harm, jeopardizing the data migration and undermining client trust. Utilizing a dedicated software solution or managed service focusing on secure data transmission can mitigate these risks, ensuring a smooth transition into parallel or go-live phases.

In Conclusion

Platforms, like ProdktrSegue, offer features to streamline the data migration process, including data extraction, scrubbing, export, and quality control checks.

Contact us for a walkthrough of our solution or discuss managed service requirements. For further elaboration on other risks, you can read more here.



[1] Securities and Exchange Commission,

[2] TechRepublic – Guide to Data Mapping,

[3] AuditBoard – Third-Party Risk Management,

[4] Deloitte US – Financial Services Industry Challenges,

[5] KPMG – Ten Key Regulatory Challenges,

[6] FT Adviser – Regulatory Headwinds Facing Financial Services,