big data banking: customer vs. accounting

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BIG DATA BANKING Customer vs. Accounting Henry Sampson Lead, Engineering & Research DreamOval Limited @henrysampson

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Post on 18-Nov-2014

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Core Banking Systems have evolved from treating customer data as a peripheral of transactions to more and more a central focus of the system. Thi s presentation explores how DreamOval is positioning Bank Nurse to meet this new reality of store more customer data than transactions

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Page 1: Big Data Banking: Customer vs. Accounting

BIG DATA BANKING

Customer vs. Accounting

Henry Sampson Lead, Engineering & ResearchDreamOval Limited@henrysampson

Page 2: Big Data Banking: Customer vs. Accounting

CORE BANKING SYSTEM (CBS)

CORE Banking:

“a back-end system that processes daily banking transactions, and posts updates to accounts and other financial records” Gartner

C.O.R.E Centralized Online Real-time Environment

Page 3: Big Data Banking: Customer vs. Accounting

EVOLUTION

Page 4: Big Data Banking: Customer vs. Accounting

DESIGN EVOLUTION OF THE CBS

Decentralized Branches

Centralized Branch

Network

SOA Based CORE

Banking

Page 5: Big Data Banking: Customer vs. Accounting

DECENTRALIZED BRANCHES

Each branch has it’s own serverTransactions take at least one day to reflect in account

Data sent to Head Office at EoD I.T. Operations Nightmare for EoD staffCustomer transaction oriented design

Page 6: Big Data Banking: Customer vs. Accounting

CENTRALIZED BRANCH NETWORK

One datacentre and many “dumb-clients” at branches

Branches access application via radio

All transactions are real-time

Less hustle at EoD

Mostly concentrated on core banking functions like Deposit Accounts Loans Mortgages  Payments

Easier multi-channel integration

Customer transaction oriented design

Page 7: Big Data Banking: Customer vs. Accounting

SOA BASED CORE BANKING

New architecture to promote service modularity

Easier to integrate existing banking application

Give more flexibility to banks to use the best tool for each function

Meets most current demands of banks of today Deploying services at the speed of thought SLA monitoring on services Creating impossible services

Customer services oriented design

Page 8: Big Data Banking: Customer vs. Accounting

BUT IS SOA THE FUTURE?

Page 9: Big Data Banking: Customer vs. Accounting

WHAT HAS DRIVEN THE CHANGE?

Page 10: Big Data Banking: Customer vs. Accounting

EVOLUTION OF CUSTOMER DATA

Central Bank’s KYC Requirements What ‘s next?

Page 11: Big Data Banking: Customer vs. Accounting

WHAT’S NEXT?

Understanding what’s next for the customer

What additional data is required? Relationships Family, friends, co-workers, etc. Interests Music artiste, car brands, home décor, photography, etc. Events wedding, birthday, graduation, etc. Location What kind of places do s/he visit and how often? Aspirations Dream car, dream house, dream job, etc.

CUSTOMER’S LIFE STORY

Page 12: Big Data Banking: Customer vs. Accounting

HOW TO STORE AND USE CUSTOMER’S LIFE STORY

Page 13: Big Data Banking: Customer vs. Accounting

WHY IS STORAGE AN ISSUE

The data being stored has three distinct attributes Volume Velocity Variety

Traditional Relational Databases reach their breaking point on commodity servers very fast

Buying specialized hardware is not feasible for most businesses

A solution that is widely accessible must use commodity servers to do what is reserved for mainframes and supercomputers

For Africa, an extra requirement is that the software must be reasonably priced

}BIG DATA

Page 14: Big Data Banking: Customer vs. Accounting

DREAMOVAL’S OPEN SOURCE BIG DATA STACK

Page 15: Big Data Banking: Customer vs. Accounting

OPEN SOURCE BIG DATA STACK

Hadoop

Mon

goD

B

Mahout Application Layer

Apache Pig

Page 16: Big Data Banking: Customer vs. Accounting

WHY OPEN SOURCE?

Page 17: Big Data Banking: Customer vs. Accounting

OPEN SOURCE

Better control over price

Removes vendor lock-in

Reduces barrier to entry

Reputation of creators

Wider community of users (Best alternative in the absence of standardization)

Apache Licenses are Enterprise Friendly

Page 18: Big Data Banking: Customer vs. Accounting

HOW TO USE CUSTOMER’S LIFE STORY

Page 19: Big Data Banking: Customer vs. Accounting

REALTIME ANALYTICS

Map customer’s upcoming events to financial products

Map customer’s friend’s upcoming events to fianacial products

Map upcoming social/professional events to customer preferences (may add financial products)

Map customer shopping wishlist to financial product

Map spending pattern to social data

Page 20: Big Data Banking: Customer vs. Accounting

LEARNING TO BE BETTER

Learn about the classifications that worked and those that didn’t

Learn about patterns that may not be evident with clustering

Use clustered to data to form new classifications

Basic question being answered is:

Given the demographic, professional, social and transaction data of a customer what service would be the best next sell?

Page 21: Big Data Banking: Customer vs. Accounting

WHERE TO GET LIFE STORIES

Page 22: Big Data Banking: Customer vs. Accounting

SOURCES OF LIFE STORIES

Social Media Networks – Relationships, interests, events, check-ins, etc

eCommerce websites – Shopping history and whislists

Telcos – Mobile money and locations data

Device Manufacturers – All mobile data

BEST Strategic Partnership Device Manufacturers

Page 23: Big Data Banking: Customer vs. Accounting

POSSIBLE ISSUES

Although regulations allow such data to be used with customer consent abuse may lead to tighter laws

Customers may not trust bank with such data

Page 24: Big Data Banking: Customer vs. Accounting

CONCLUSION

Page 25: Big Data Banking: Customer vs. Accounting

The next frontier of banking is to use big data technologies to rightly predict customer needs. The competition will be who has the clearest crystal ball.

Page 26: Big Data Banking: Customer vs. Accounting

QUESTIONS?