How Predictive Analytics & Big Data are Disrupting Financial Services
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1 #1 Agile Predictive Analytics Platform for Today s Modern Analysts How Predictive Analytics & Big Data are Disrupting Financial Services Vamsi Chemitiganti General Manager Financial Services
2 State of Global Banking 2016 RapidMiner, Inc. All rights reserved
3 Financial Services and Big Data Focused around business and technology vectors Technology vectors Cloud computing (OpenStack) DevOps and PaaS Mobility Big Data and analytics BPM and microservices Software-defined datacenters Digital Bank Bank 3.0s Business vectors Regulation and risk management Compliance and regulation Trading systems Omni-channel wealth management Payments systems Bank RapidMiner, Inc. All rights reserved
4 Areas of Impact 2016 RapidMiner, Inc. All rights reserved
5 Key areas within the financial services industry 2016 RapidMiner, Inc. All rights reserved
6 Lifecycle of Big Data adoption HDP helps FSIs drive efficiency gain RapidMiner, Inc. All rights reserved
7 Predictive Analytics on Hadoop Write data prep and predictive analytics code for Hadoop It s complex, requires programming and specialized knowledge of each Hadoop technology Which would you prefer? Push automatically generated computations into Hadoop It s code-free, speaks Hadoop for you, and is x faster to implement 2016 RapidMiner, Inc. All rights reserved
8 Impact of RapidMiner & Data Science A representative sample only Survey of ML algorithms used (stated briefly for confidentiality purposes) Classification & Class Probability Estimation Regression Similarity Matching Clustering Co-Occurence Grouping Profiling Link Prediction Causal Modeling Most use cases typically revolve around a single view of Entity 2016 RapidMiner, Inc. All rights reserved
9 Digital Transformation 2016 RapidMiner, Inc. All rights reserved
10 The digital journey in banking 2016 RapidMiner, Inc. All rights reserved
11 Cyber Security 2016 RapidMiner, Inc. All rights reserved
12 Cyber security 2016 RapidMiner, Inc. All rights reserved
13 Customer Segmentation 2016 RapidMiner, Inc. All rights reserved
14 Customer segmentation process 2016 RapidMiner, Inc. All rights reserved
15 Regulatory Risk Management 2016 RapidMiner, Inc. All rights reserved
16 Proposed Solution Hortonworks Data Platform Golden Source & Feeds Master Data Transaction sqoop/hadoop fs/ nfs LANDING DATA ZONE L0 RAW Data hdfs) Hive/Spark/Scala STANDARDIZED DATA ZONE L1 Standardized Data (Hive/Orc) CANONICAL DATA ZONE L2 Canonical Transaction Data (Hive/orc) Scala/Python/R etc Scala/Java REPORTING/ ANALYTICS ZONE L3 Scenarios Results (Hive/orc) Regulatory Reports Internal Reports Balances Contrats Positions Kafka/Storm Java/Scala Original Data (hdfs) Unstructured Data (hdfs) Hive/Spark/Scala MHive/Spark/Scal Standardized Data (Hive/Orc) Standardized Data (Hive/orc) Hive/Spark/Scala Hive/Spark/Scala Canonical Position Data (hive/orc) Materialized View (Hive/orc) TBD?? Hive/Spark Data Aggregations (Hive/orc/ Hbase) Analytics/ Reports (Hive/orc/ HBase) External Reports Market Data Hive/Spark/Scala Hive/Spark/Scala Hive/Spark Revision History (Hive/orc) Search Factors/ Scenarios Common Repositories/Meta Data Management Apache Atlas/Falcon/ Custom Solution Security Apache Ranger/ Atlas and Custom/Partner Solution 2016 RapidMiner, Inc. All rights reserved
17 AML Compliance 2016 RapidMiner, Inc. All rights reserved
18 Fraud/AML/Compliance Reference architecture 2016 RapidMiner, Inc. All rights reserved
19 Fraud Monitoring & Detection 2016 RapidMiner, Inc. All rights reserved
20 Fraud Detection Reference architecture 2016 RapidMiner, Inc. All rights reserved
21 Modern Data Architecture with HWX and RM 2016 RapidMiner, Inc. All rights reserved
22 RapidMiner Radoop Big Data Predictive Analytics Extends RapidMiner s visual predictive analytics to Hadoop and Spark We speak Hadoop so you don t have to Translates predictive analytics into native Hive, MapReduce, Spark, Pig and Mahout you concentrate on competitive analytics, not Hadoop programming COMPLETE insights into your Big Data Pushes analytic instructions into Hadoop for computation, so you can analyze the full breadth and variety of your Big Data Structured and non-structured Not just drag & drop: use your favorite Hadoop scripts, too! Incorporates your favorite SparkR, PySpark, Pig and HiveQL scripts within your predictive analytics workflow Safe and sound Integrates with Kerberos authentication, supports data access authorization for Apache Sentry and Apache Ranger seamless for users, easy admin for IT 2016 RapidMiner, Inc. All rights reserved
23 Vamsi Chemitiganti General Manager Financial Services Hortonworks #1 Agile Predictive Analytics Platform for Today s Modern Analysts 2016 RapidMiner, Inc. All rights reserved. CONFIDENTIAL
Introduction to Big Data Analytics p. 1 Big Data Overview p. 2 Data Structures p. 5 Analyst Perspective on Data Repositories p.
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