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Typical banking sources of BIG DATA include WHICH WOULD EQUATE TO 275 billion 1 mp3’s of stored data How banks put BIG DATA to work BIG DATA in banking BIG DATA problem solving for financial institutions Anti-money laundering procedures and fraud detection Customer risk assessment Stock trade surveillance and pattern analysis Compliance and regulatory reporting Customer relationship management THE BANKING BUSINESS FINDS A NEW ASSET Banking volumes Credit card histories Web interactions Call logs Customer bank visits Transaction types Social media U.S. banks currently have SOLUTION Preventing Customer Churn Setting Effective Staffing Levels Understanding Customer Needs Managing Rising Security Costs The costs of developing new prod- ucts and services can be staggering Customer transactional data such as timing of visits and duration of teller transactions can be analyzed to find gaps in product offerings Consumer payment patterns and law enforcement databases supply the data Insights for Product Development Banks need to cut lending risks while improving customer marketing Scoring Credit Risks SOLUTION SOLUTION A customer churn prediction model based on big data analysis of social media customer sentiment and purchasing power helps identify customers at risk of leaving Staffing models based on transaction times and account holder traffic patterns data make annual resource planning easier and more effective 50% In 2012 Of coustomers changed banks or were planning to change banks 66% of a branch bank’s costs Staffing costs account for SOLUTION SOLUTION Customers face a bewildering number of banking “journeys” through websites, call centers, branch bank personnel and more Big data from customer waiting and assist periods and online banking habits helps track the paths customers follow and how they affect purchasing decisions Big data from cross channel security alerts and international money transactions creates compliance analytics for performance models that reduce alerts while delivering ongoing monitoring More stringent federal security regulations require banks to have safeguards for anti-money laundering in place $ ? NEW credit bureaus store over For comparison, the FBI’s Investigative Data Warehouse has only 1.5 billion documents. 800 billion records SOLUTION to be sliced, diced and analyzed for more accurate credit risk scores. www.alacergroup.com 1. McKinsey Global Institute | 2. 2012 Global Consumer Banking Survey, Ernst & Young | 3. Bancography | 4. International Institute of Analytics, 2013 | 5. ACLU

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Page 1: Alacer Banking Big Data - Alacer Group€¦ · 50%In 2012 Of coustomers changed banks or were planning to change banks 66% of a branch bank’s costs Staffing costs account for SOLUTION

Typical bankingsources of BIG DATA include

WHICH WOULD EQUATE TO

275 billion1mp3’s

of stored data

How banksput BIG DATAto work

BIG DATA in banking

BIG DATA problem solving for financial institutions

Anti-money laundering procedures

and fraud detection

Customer risk assessment

Stock trade surveillance and pattern analysis

Compliance and regulatory reporting

Customer relationship management

THE BANKING BUSINESS FINDS A NEW ASSET

Banking volumesCredit card historiesWeb interactionsCall logsCustomer bank visits Transaction typesSocial media

U.S. banks currently have

SOLUTION

Preventing Customer Churn Setting Effective Staffing Levels

Understanding Customer Needs Managing Rising Security Costs

The costs of developing new prod-ucts and services can be staggering

Customer transactional data such as timing of visits and duration of teller transactions can be analyzed to find gaps in product offerings

Consumer payment patterns and law enforcement databases supply the data

Insights for Product Development

Banks need to cut lending risks while improving customer marketing

Scoring Credit Risks

SOLUTION SOLUTIONA customer churn prediction model based on big data analysis of social media customer sentiment and purchasing power helps identify customers at risk of leaving

Staffing models based on transaction times and account holder traffic patterns data make annual resource planning easier and more effective

50%In 2012

Of coustomers changed banks or were planning to change banks

66%of a branch bank’s costs

Staffing costs account for

SOLUTION SOLUTION

Customers face a bewildering number of banking “journeys” through websites, call centers, branch bank personnel and more

Big data from customer waiting and assist periods and online banking habits helps track the paths customers follow and how they affect purchasing decisions

Big data from cross channel security alerts and international money transactions creates compliance analytics for performance models that reduce alerts while delivering ongoing monitoring

More stringent federal security regulations require banks to have safeguards for anti-money laundering in place

$

?

NEW

credit bureaus store over

For comparison, the FBI’s Investigative Data Warehouse has only 1.5 billion documents.

800 billion records

SOLUTION

to be sliced, diced and analyzed for more accurate credit risk scores.

www.alacergroup.com

1. McKinsey Global Institute | 2. 2012 Global Consumer Banking Survey, Ernst & Young | 3. Bancography | 4. International Institute of Analytics, 2013 | 5. ACLU

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