Working with financial data requires a high degree of rigor due to the numerous regulations and the risks involved in security breaches. In this episode Andrey Korchack, CTO of fintech startup Monite, discusses the complexities of designing and implementing a data platform in that sector.
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- Your host is Tobias Macey and today I'm interviewing Andrey Korchak about how to manage data in a fintech environment
- How did you get involved in the area of data management?
- Can you start by summarizing the data challenges that are particular to the fintech ecosystem?
- What are the primary sources and types of data that fintech organizations are working with?
- What are the business-level capabilities that are dependent on this data?
- How do the regulatory and business requirements influence the technology landscape in fintech organizations?
- What does a typical build vs. buy decision process look like?
- Fraud prediction in e.g. banks is one of the most well-established applications of machine learning in industry. What are some of the other ways that ML plays a part in fintech?
- How does that influence the architectural design/capabilities for data platforms in those organizations?
- Data governance is a notoriously challenging problem. What are some of the strategies that fintech companies are able to apply to this problem given their regulatory burdens?
- What are the most interesting, innovative, or unexpected approaches to data management that you have seen in the fintech sector?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on data in fintech?
- What do you have planned for the future of your data capabilities at Monite?
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
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