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Explore the vast potential for banking in the IoT era with insights from Bas Geerdink, IT Manager at ING. Learn about IoT use cases for banks, ING's data-driven strategy, and the technology driving their data lake.
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Fast Data in the IoT Bas Geerdink
About Me • IT Manager / Chapter Lead • Academic background in Artificial Intelligence andInformatics • Working in IT since 2004, previously as developerand architect • At ING sinceJune 2013 • Twitter: @bgeerdink • LinkedIn: https://nl.linkedin.com/in/geerdink
The IoT offers a lot of opportunities for the banking industry Source: The Bank of Things – Accenture, 2014
The use cases forbanks in the IoT canbedivided in twocategories • The bank as facilitatorof IoT services, byprovidingmicrotransactionsand open APIs • Real-time, automatic pay per use of gas/water/energy consumption • On-demandbuying of groceriesandother items in the ‘smart home’ • Direct, automatic payments of gas/electricity in gas stations in the ‘connectedcar’ • The bank as provider of IoT services byusingitsowndevices as the source of data • Personal assistence, e.g. real-time financeadvise • Alertingandother means of signaling in the ‘smart home’ • Location-based services, e.g. buyingadvisefor a house based on Google Glass data • Individual marketing andadviseby making use of beacons in shops and branches
There are three types of data streams at ING BIG DATA FAST DATA
All data streams follow the samepatternand pass throughpipesand filters Source: A Reference Architecture forBig Data Solutions – Bas Geerdink, 2013
ING’s Data Lake is based on IBM’s Data Reservoir reference architecture
ING’s Data Lake is based on IBM’s Data Reservoir reference architecture Core Systems Analytics Tooling GovernanceCatalog Real-time Streaming Reports Archive Exploratory Data Batch & Incremental Feeds Enterprise Datawarehouse
ING’s Data Lake is based on IBM’s Data Reservoir reference architecture Core Systems Analytics Tooling GovernanceCatalog Real-time Streaming Reports Archive Exploratory Data Batch & Incremental Feeds Enterprise Datawarehouse
The technologydepends on the data size, speed andusageNote: components are examples, technology is under constant evaluationand subject to change Core Systems Analytics Tooling GovernanceCatalog Real-time Streaming Reports Archive Exploratory Data Batch & Incremental Feeds Enterprise Datawarehouse
Summary andConclusions • The IoT offers a lot of opportunitiesfor the banking industry • Banks can act as facilitator or provider for IoT-driven services • Someexampleuse cases are: automatic payments, microtransactions, buyingsuggestions, financial advise • Sensory data includeslocation data, household equipment, data fromcars, ING’sinfrastructure • ING has a data-drivenstrategy, aimed at providing the best customer services • It makes sense to invest in aninfrastructureforany kind of data processing, including IoT streaming data: the data lake
Thankyou bas.geerdink@ing.nl @bgeerdink