IM5 6 - lecture5,6 PDF

Preview

Summary

lecture5,6...

Description

Information Management – Lecture5&6: Smart Banking; Business

Intelligence Systems; Information Systems Development Smart banking  Connectivity 

Anywhere, anytime, any device

 

Self-service/ customer-centered service Global project that needs global partnership across teams

Growth  

Payment transformation

Invest in customer growth in contactless payments analytics contributes to banks' role in the Use digital payments network while cutting technologies to further into interchange revenue improve customer and brand recognition. experience in both business and retail  banking



Determine whether or prudent underwriting standards overlooked



not  are

Learn from nonbank technology firms and establish an exclusive partnership to create innovation and a competitive edge

Compliance management

and

Meeting expectations

risk

regulatory will

require

management to extend its focus from

improving specific processes to fully integrating

risk management, compliance, Seek innovative ways to use and ethics into banks’ culture. customer spending data for specialized promotions and  Reinforce 加 固 a strong services

‘tone at the top’: defining

Look for new ways to be top of wallet and differentiate the

the management and board of director’s leadership and their commitment to being honest and ethical Encourage boards 董 事 會 to challenge senior management’s activities

customer experience 



Empower

chief

risk

officers 首風險官 to pursue collaboration with business lines 

Incorporate management compliance responsibilities

risk and into

performance management programs and employee training

Data management

Cybersecurity

As the data and analytics function within

Banks will be forced to devote greater bank evolves, institutions should be shifting resources to enhance security, vigilance 警 覺 , toward a proactive 積 極 stance to ward off 擋 and resilience 有彈性的 of their cybersecurity 住 further regulatory pressure. model. 

Creating a central regulatory  management to office to help drive greater efficiencies

Adopting new methods, such as war gaming, attracting specialized talent, and increasing collaboration with other



Relying on chief data officers to establish tighter connections with front-office  functions and derive greater value from data assets 

members of the ecosystem Beefing up their intelligence apparatus 設 備 to detect new threats in a timely manner Expanding the role of the chief information security officers (CISO) to include

clear

and

prompt

communications with the board

Smart e-payment: pay for online purchases Credit cards

Direct debits: Stored value facilities (SVFs): Purchase amount is debited directly from E.g. Octopus & O!ePay, PayPal, a bank account, no need to apply for Alipay wallet, Jockey Club Betting credit

Account, Apple Pay, WeChat Pay,

e.g. EPS (electronic payment service)

Tag & Go, TNG Wallet

PPS (Payment by phone service)

Business Intelligence help in smart banking  Data available from different interactions, transaction data from branch, ATM, phone banking, fax, ebanking Big data: High-volume, high-velocity, and high variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making. Operational DBs,

Business intelligence application

Purchased data, Acquire data

Analyze data: reporting, data mining, BigData

Knowledge workers Publish business intelligence

Project management

Organizations use of Business Intelligence Problem solving Deciding

Typical uses for Business Intelligence Identifying changes in BI for entertainment: Netflix purchasing patterns: important uses data to determine what life events cause customers to people actually want, not what they say they want change what they buy

Informing

Predictive policing: analyze data on past crimes (location, date, time, day of week, type of crime, etc.) to predict where crimes likely to occur

Use of data warehouses and data marts to acquire data  Obtain or extract data from operational, internal and external databases 

Cleanse data

 

Organize, relate, store in a data warehouse Catalog data using metadata

Extraction, transformation, and loading (ETL) A process that 

Extracts information from internal and external databases



Transforms the information using a common set of enterprise definitions



Loads 加載 the information into a data warehouse Data warehouse: information

Internal database + External database

Marketing data mart Inventory data mart Exploring and mining

Data warehouse

Data mart Large repository 資 料 庫 of data collected Data collection that addresses needs of a from different departments within an particular department/ functional area of organization business; a subset 大集合 of data warehouse Common Business Intelligence techniques Multidimensional analysis:

Cluster analysis:

Association detection:

a system of multiple queries

class of techniques that are

reveals the degree to which

that scrutinize data from

used to classify objects or

variables are related and the

different

cases into relative groups

nature and frequency of these

called clusters

relationships in the information

perspectives,

or

dimensions

 Business Intelligence tolls  help creating multidimensional view of data 1. Dimension: a particular attribute of information

possible to one another and the different groups are

of

Online analytical processing (OLAP) is a reporting technology that can perform  multidimensional analysis: enables users to easily and selectively extract and query data in order to analyze it from different points of view

exclusive groups such that the members of each group are as close together as 

2. Cube: common term for the representation multidimensional information

A technique used to divide an information set into mutually

as far possible

apart

as 

E.g. to segment customer information and identify behavioral traits

*set dimensions, analyze clusters  define actions

reveals the relationship between variables along with the nature and frequency of the relationships. (similarity,

mode

and

pattern) determine likelihood of events occurring together at a particular time business application: market basket analysis:  analyze items such as checkout checkout scanner detect information to customers’ buying behavior and predict future behavior by identifying affinities 相同 among customers’ choices of products and services



develop used to marketing campaigns for cross-selling 交 叉 銷 售 products

and

services,

inventory

control,

shelf-

product

Cubes for information Dimensions: store x product x promotion Value: sales What is the impact on sales of promo II for all stores of product B Operations: and dicing

slicing

Business intelligence: identifying opportunities Project management: managing projects to realize opportunities Project Management Qualification: Project Management Professional (PMP)  industry-recognized certificate for project managers  4 year degree + 3/+ project management experiences + exam Planning the project： ： Initiating the project:  Perform project assessment/ feasible  Assess detailed project requirements, analysis constraints, assumptions   Meeting sponsors (internal/ external) Develop budget plan  Define scope Develop project schedule Develop HR management plan Executing the project: through training, Monitoring and controlling the project:  during execution knowledge sharing, meeting, etc  Execute tasks defined (by your  Measure project performance  company/ others) Ensure project deliverables conform to



Implement approved changes Maximize team performance Closing the project  Obtain final acceptance

quality standards Communicate project status to stakeholders



Transfer ownership Obtain financial, legal, and administrative closure

System Development Life Cycle (SDLC)

Change management  Vital component of Information System development and implementation projects to increase the chances of success of a project  When managing change, special attention should be paid to 1. Resistance to change 2. Organizational culture 3. Project participants/ stakeholders

Setting & managing objectives so that they are linked to vision and purpose of change Planning details and required resources Possible adjustment of plan or modification of actions to ensure achievement of objectives

Implementing plan with continuous monitoring

Systems development is difficult and risky  Many projects are never finished.  Those finished are often 200-300% over-budgeted  Even some finished within budget and schedule, they may not accomplish goals  project managers’ key task: make sure project can be completed under resources constraint (time, money, manpower, etc.) in achieving goals~ Major challenges Difficulty

of Changes

determining

requirements

requirements:

in Difficulties involving scheduling budgeting

and

Changing

Diseconomies

technology

scale:

of

(average

contribution falls when

additional

workers added)  Law: business Brooks’ more analysts/ project ‘adding managers carry people to a late out the impact project makes the analysis and project later.’

 Bigger system, business  longer project analysts/ project  more managers requirements calculate all time change and budget and  business report the return determines if the New staff must be analysts/ project analysts/ project on investment new tech should trained by managers use managers to be incorporated productive (ROI)

what specifically is system to do? e.g. design, function, scenarios  business

diagrams illustrate feature

of

to determine what management key changes could be new handled within

members lose

who

productivity

while training

systems, supplemented with

resources

business

constraints

analysts/ project managers plans

detailed

specifications

carefully for team sizes and timeline

1.

What of the following statements is true of business intelligence (BI) systems?  Business intelligence systems analyze an organization’s performance to make predictions

2.

The use of an organization’s operational data as the source data for a business intelligence system is NOT usually recommended because it ______  Requires considerable processing and can drastically reduce system performance

3.

A ______ is a data collection, smaller than the data warehouse that address the needs of a particular department or functional area of a business  Data mart

4.

Users in a data mart obtain data that pertain 關於 to a particular business function from a ____  Data warehouse

5.

___ is an unsupervised data mining technique in which statically technique identify groups of entities that have similar characteristics  Cluster analysis

6.

Which of the following statements is true of Big Data?  Big Data refers to data sets that are at least a petabyte/ 250 bytes in size

7.

Which of the following is NOT a domain knowledge of project management?

 8.

Hire new project staff

Which of the following trends of banking is NOT related to information management and information systems?  Merger and acquisition 合併與收購

9.

BI tools create multidimensional view of data through common operations, including pivot, and _____  slice and dice...