The amount of data generation has multiplied many folds overdue to the dominance of the digital age. Thus, enterprises that wish to remain in business and remain relevant in today’s world and the future must understand and learn how to manage a large volume of data through a strong, scalable, and flexible platform. Apache Kafka is one of the means to achieve it.
Apache Kafka, an advanced streaming platform that manages to send messages from one end to another, is a perfect tool to handle big data. In this blog, we will look at a few real-life use cases of Apache Kafka in the banking sector.
Here below are some of the most common use cases:
Use Case #1: Kafka Messaging
For a more conventional message broker, Kafka works well as a substitute. Message brokers are used for various reasons like to safeguard unprocessed messages, decouple handling from data producers, etc. Kafka has better imitation, in-built partitioning, throughput, and error tolerance. In contrast to most messaging systems, it makes for a worthy solution for big-scale message handling applications.
Use Case #2: Kafka Metrics
Kafka is commonly used for operating monitoring data. Further, it takes account of combining statistics from distributed applications to generate integrated feeds of operative data.
Use Case #3: Kafka Log Aggregation
Kafka can be utilized across the company to capture logs from multiple services and make them available in a customary standard format to several consumers.
Use Case #4: Stream Processing
Few standard frameworks read data from a subject, process it, and write processed data to a new topic, where it is made available for users and applications, like Spark Streaming and Storm. In the framework of stream processing, Kafka’s robust stability is quite beneficial.
Apache Kafka Use Cases in Investment Banking:
Kafka is highly popular and used by fin-techs, banks, and conventional financial institutions to enhance their operations.
Use Case #1: Fraud Detection all the way!
The banking sector deals with a large number of scams, money laundering, and illegal payments. Apache Kafka can assist banks to effectively identify scams and, therefore, re-establish their integrity, confirming the best safety measures for their clients.
Use Case #2: Customer satisfaction is important too
Banks are constantly working towards an effective strategy to give their clients a wholesome experience. Kafka can be used to gather numerous forms of data and collect them to generate innovative strategies. For example, the platform can work to suit the necessities of each client, customizing their experience. It can also incorporate and handle messages in various languages without any hassle.
Use Case #3: Trade it until you make it!
Trading occurs every single minute of the day. Thus, the volume of data generated is huge and requires high data analysis. At the same time, the industry is at risk through various types of manipulation. Financial institutions that manage trades can benefit from stream analytics using Kafka as a monitoring tool that can sense even the slightest bit of fudging and immediately caution authorities to take appropriate action.
Here is an example of a financial establishment leveraging Kafka to accomplish a competent authority in the industry.
Use Case #5: Goldman Sachs
Goldman Sachs created a platform called ‘Core’ to manage its data. The platform has helped the financial institution to accomplish a high data loss prevention rate, reduce outage time and get easier disaster recovery.
We hope this blog has helped you in understanding the use cases of Apache Kafka in various areas, particularly the investment banking sector. You can depend on Apache Kafka to increase customer satisfaction, provide quality data analysis, and retain a competitive advantage. And if Kafka is a powerful engine, Knoldus Inc. is the supersonic jet that can make the most out of it. Let’s get started!!!
Also published on Medium.
