Near-real-time processing handles incoming data with short delays rather than waiting for a scheduled batch.
Near-real-time processing handles selected incoming financial data with short delays when a decision, such as an instant approval, cannot wait for a scheduled batch. section 5.1.1
Common patterns include:
Stream BNPL or card-approval data through Kafka and append it to daily logs for analytics. section 5.1.1
Merge selected data, such as bureau checks, for instant approvals, then finalize a daily batch for analytics. section 5.1.1
How Financial AI in Practice covers it
How deep it goes
Contrasts nightly or weekly batches with partial real-time merges, but does not detail stream-processing implementation.
Examples
Uses BNPL or card approvals streamed through Kafka and bureau checks merged for instant lending decisions.
What you can do after
Evaluate when to use partial near-real-time merges rather than relying only on daily or weekly pipelines.
How it connects
Connects data ingestion with batch processing, Kafka, bureau checks, and data marts.
Kafka for ArchitectsReal-time event processing is the handling of events with sufficiently low latency to support immediate or near-immediate reactions.
Kafka Streams in Action, Second EditionReal-time processing is the processing of data with sufficiently low delay to support decisions while events are occurring.
batchingcontrasts with · Batching is the grouping of multiple data items, requests, or operations so they can be processed together as a unit.
Apache Kafkaused by · Apache Kafka is a distributed event-streaming platform for publishing, storing, processing, and consuming streams of records.
microservice architectureuses · Microservice architecture is a software architectural style that organizes an application as independently deployable services with focused responsibilities that communicate through defined interfaces.
customer data platformimplemented by · A customer data platform is a platform that unifies customer data from multiple sources into persistent customer profiles for activation and analysis.
streamingused by · Streaming is the incremental handling of a sequence of data items, including their processing, transfer, or consumption as they become available.
Azure Functionsused by · Azure Functions is Microsoft's managed serverless compute platform for running event-driven or scheduled application code without managing the underlying servers.
This explainer was generated by Manning's knowledge graph from the text of Financial AI in Practice. The section links point to the parts of the book it draws on.
