Leveraging inter-banking data for analytics applications will unlock untapped potential.
Such data is tough to exploit in raw form and requires a dedicated pipeline and platform.

Switflow is a data transformation pipeline that provides full transparency on inter-banking financial transactions (e.g. SWIFT messages), namely by parsing, enriching, structuring, and grouping those transactions into a data model tailored for downstream analytics applications.

Swiftflow contributions:

• Holistic parsing : information extraction from raw text of any message type¹, within all its blocks, sections, fields and subfields, without any loss of context, into a single data model.
• Simple API: the only input required is the raw message, which makes it ideal for explorative applications where no business knowledge is available
• Structured output : by flattening and exploding all nested and repetitive fields (common in MT5XX) into a big tree (JSON) or a big table (on demand), hence offering a data model ready for consumption by downstream BI² or ML³
• Enriched information (on demand): time zoning (according to BIC⁴ locations), geo location, entity recognition

Find all the details you need (use cases, data, functions, architecture, tutorials, ordering) in the knowledge base.

Swiftflow supports both MT and ISO20022 standards.

While the current migration to ISO20022⁵ is changing the payment messaging landscape globally, other transactions “are currently not in scope” according to SWIFT⁶, and the banking industry will still heavily rely on the SWIFT MT 15022⁷ standard for its inter-banking communication.

The MT standard will still be used in the years to come for :

• Corporate payments and cash management
• Securities post-trade
• Clearing and settlement
• Corporate actions
• FX
• Treasury and trade finance

Data analytics application that support MT or ISO200022 will enable:

• Operations to increase efficiency of business processes while adapting to regulation like CSDR⁸
• Compliance to adapt to stringent regulation frameworks in areas such as AML⁹ or CTF¹⁰
• Front office to gain entity knowledge (KYC¹¹), incl. monitoring wealth distribution

1. With exception of MTx99 that can be included if required
2. Business Intelligence
3. Machine Learning
4. Bank Identifier Code
5. https://www.iso20022.org/
6. https://www.swift.com/standards/iso-20022-programme
7. https://www.iso20022.org/welcome-iso-15022
8. Central Securities Depositories Regulation
9. Anti Money Laundering
10. Counter Terrorist Financing
11. Know Your Customer