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Summary Theory FSAN

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Alle theorievragen financial services analytics (K. Boudt)

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Financial Services Analytics: list of theory questions

Lecture 1
1. What are the four drivers of the trend towards digitalization in financial services?
 Technology has changed
o More communication on digital device
o More data stored, saved and processed
o More decisions data-driven and automated
 Customers have changed
o More demand in terms of user experience
o Require personalization
o Require low costs
o Embrace digitalization (trust in IT firms, interact with robots and digital devices,..)
 Banks’ profitability under pressure
o Exposed banks vulnerabilities
o Low margins due to overcapacity: cannot cover costs in LT
o Solutions: M&A
o Be efficient
o Meet customer’s needs
 Competition has increased
o New entrants specialized in one service

2. What are the hurdles in the transformation from a traditional physical bank to phygital or digital bank?
 Cost of transformation
o Balance with gains from automation and digitalization
 People: war for talent
 Technology: fast evolving
o Stay up to date is challenge
 Vision: proactivity and persistence, as it takes time
o Different C-functions: chief digital officer, information officer,..

3. Explain following concepts
 Phygital approach
o Different branches in one network e.g. Belfius mobile banking + interaction platform
for customer services
 Data driven
o To be informed by advanced data analytics
 Digital first
o Basis: digital interactions with customers e.g. solutions for customers’ financial needs
via mobile applications
 Robo-advice
o Robot provides relevant and personalized solutions
 AI learning
o Robot/chat bots continuously improve
 Personalization
o Personal advice
 Augmented workforce
o A blend of human employees and technology workers on tasks together e.g. routine
tasks by robots, other jobs are created to monitor, install and maintain these robots

,Questions 1-3 could be integrated into a new question that integrates related concepts from Lecture 10

4. Explain how the business problem of an insurer can be mapped into a data problem
 Business problem
o Attract people to pay premiums
o Premiums sufficient to cover claims, costs and have profit
 Data problem
o Which data is useful to determine premium
o Avoid fraud
 Data solution
o Collect data on client characteristics and past claims
o Determine model
 Business solution
o Digital or phygital platform to attract clients
o Let them fill in questionnaires to calculate premium

Might be linked with a question from Lecture 8

5. What is FSAN?
 Analytics: analysis of data with goal
o Improve decisions
o Growing business
o Optimizing cost
o Managing risk
 Financial services
o Banking
o Insurance
o Payments services
o Wealth & asset management

, Lecture 2
1. What is the server log?
 Tracks user’s clickstream data
 Very detailed
 Challenges
o High volume of data
o Raw, unfiltered descriptions
o Doesn’t tell why customer visited
 Transform clickstream in time series
o Time > threshold  contact the user with an offer
o Find threshold with grid search

2. What is the grid search approach to optimizing a function?
 Force approach to find best value
o Define lower and upper bound
o Evaluate function for a sequence between lower and upper
o Set the solution to the trial value with highest value for objective function

3. What is a 10 month moving average stock price series and how can it be used in market timing?
 Trading to rule: stay invested as long as the current P exceeds 10-month moving average

4. What is a rolling window approach and how can it be used to monitor risk?
 Compute annualized volatility for every window of 21 days
 High volatility means high risk

5. What is optimization?
 Make decision that achieve best value (=global max) with respecting constraints
 x for max f(x) will also be x for min -f(x)
 Value first derivative = x
 Value second derivative > 0  convex (min), if < 0  concave (max)
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