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Master’s Thesis Tallinn University of Technology Department of Computer Engineering Computer Systems Design
DECISION SUPPORT SYSTEM FOR FINANCIAL LIQUIDITY PLANNING
Author: Erik Kaju Supervisor: Tarmo Robal (PhD)
15.06.2015
THE OBJECTIVE
The objective of this thesis is to use information technology facilities and build a minimum viable product solution that would potentially enhance a liquidity planning process in the world’s fastest growing money transfer service.
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TRANSFERWISE
TRANSFERWISE
TransferWise (TW) is an international money transfer platform. It makes it up to 10 times cheaper to send money abroad compared to using similar services offered by banks. TW’s technology is based on peer-to-peer system and has helped customers to move more than £4,5bn – an approach that has saved customers£180m.
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THE PROBLEM
IMBALANCE OF OF CURRENCY FLOWS
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DIFFICULTY OF FORECASTING
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DIVERSITY OF FACTORS
THAT INFLUENCE
THE DEMAND FOR MONEY
RAPIDLY CHANGING
ENVIRONMENT RANDOMNESS
FACTORS ANALYSIS
INTERNAL • Liquidity buffer account balance • Suspended transfers • Liquidity in transit
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EXTERNAL • Recent volume descriptor • Growth trends • Weekly patterns • Monthly patterns • Exchange rate movements • Frequency of extra large payments • National holidays
WEEKLY PATTERNS
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MONTHLY PATTERNS
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TIME SERIES ANALYSIS
A time series is a collection of observations of well-defined data items obtained through repeated measurements over time.
COMPUTATIONAL MODEL
WEEKLY PATTERNS
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MONTHLY PATTERNS
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VISUALISATIONS
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FORECASTING ALGORITHM
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LIQUIDITY RECONCILIATION DECISION SUPPORT SYSTEM
THE IMPLEMENTATION
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GRAILS GROOVY JAVA
THE PROTOTYPE
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THE PROTOTYPE
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THE PROTOTYPE
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TESTING
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TESTING, RESULTS
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THE OUTCOME
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THE PROPOSED NEXT STEPS 1. Include more factors into
calculational model 2. Enhance the proposal
algorithm 3. Carry out tests and compare
the efficiency vs. current human factor
4. Based on results decide whether more determinants need implementing
5. If needed, repeat steps 1,2,3 6. Go live 7. Continuously improve the
solution
PLAN: WHAT TO DO NEXT
THANK YOU
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QUESTION FROM REVIEWER
Q: Kuidas suhtute mõttesse, eemaldada andmetest põhitrendid ja siis katsetada jääki juhuslikkusele ja alles seejärel tuua sisse lisafaktoreid? How do you find the idea of removing main trends from data and test the irregular component and only then introduce extra factors. (perform seasonal adjustment)? A: Aegridade teooria järgi oleks selline lähenemine õige, aga kuna seadsin antud tööle järgneva tuleviku väljavaateks just olulisemate ettevõtteväliste ja sisemiste sesoonsusest sõltumatute lisafaktorite mõju uurimise ja vähendamise, siis põhitrendide analüüsi jätsin teadlikult kõrvale. According to the theory of time series, such approach is correct. I have set a goal for future development after this thesis to mitigate the impact of main internal and external determinants that are independent from seasonalities. For that reason I decided not to perform classical seasonal adjustment.
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Reviewer: Enn Õunapuu
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