Please enable JavaScript.
Coggle requires JavaScript to display documents.
Digital Financial Management, Digital Financial Management, Digital…
Digital Financial Management
Convenient Access & Neo Banks
24/7 branchless service
Low overhead costs
High acquisition costs
Personalized & Embedded Finance
AI & Big Data insights
Embedded in daily apps
Open Banking data sharing
Robo-Advisors
AI-driven portfolios
AUM-based fees
Pros: Scalable & low entry barriers
Cons: Tech risks & less human touch
Alternative Credit & Lending
Digital footprint scoring
Pros: Financial inclusion
Cons: Higher default risk
Digital Financial Management
Convenient Financial Access & Neo Banks
Break time and space limits: 24/7 digital services without physical branch wait times
Operating cost advantages: No physical branches or ATMs, significantly lowering overhead costs
High automation efficiency: E.g., processing two years' worth of relief loans in about 1.5 months
Operational challenges: Neo banks face high customer acquisition costs and initial profitability hurdles
Personalized & Embedded Finance
Big Data & AI analytics: Understand customer behavior to provide tailored financial solutions
Open Banking APIs: Support real-time information exchange and embed banking functions into other apps
Seamless daily integration: E.g., LINE and Rabbit for transit payments in Thailand, Cheers AI cashierless stores in Singapore
Data governance & privacy: Requires clear data-sharing rules, customer consent, and encrypted transfers
Digital Investment & Robo-Advisors
Operational model: Algorithms and AI analyze client data to deliver tailored portfolios
Revenue model: Usually charges an asset-under-management (AUM)-based fee
Advantages
High scalability to easily expand service volume
Lower entry barriers, allowing retail clients with less capital to invest
Disadvantages
Limited human interaction; cannot satisfy clients needing complex advice
High reliance on technology leads to technology outages and cybersecurity risks
Easily copied business models lead to limited differentiation and price competition
Alternative Credit Assessment & Lending
Operational model: Assesses credit using digital footprints and non-traditional data instead of traditional credit histories
Advantages
Expands financial inclusion, helping underserved populations access credit
Can provide loans more efficiently with competitive advantages
Disadvantages
Non-traditional data can be unreliable or unstable
Borrowers often lack collateral, leading to higher default risks
Increases the burden of risk management and underwriting costs for providers
Digital Financial Management
Convenient Access & Neo Banks
24/7 access: No physical branch wait times
Low overhead: No branches or ATMs
High efficiency: Automated loan processing
Challenges: High acquisition costs & low initial profit
Personalized & Embedded Finance
AI & Big Data: Tailored financial solutions
Open APIs: Embed banking into other apps
Daily integration: E.g., transit payments & AI stores
Data governance: Clear rules, consent & encryption
Digital Investment & Robo-Advisors
Model: AI-driven tailored portfolios
Revenue: AUM-based fees
Advantages
High scalability
Lower entry barriers for retail clients
Disadvantages
Limited human interaction
Tech outages & cybersecurity risks
Easily copied models & price competition
Alternative Credit & Lending
Model: Credit scoring via digital footprints
Advantages
Expands financial inclusion
Efficient & competitive lending
Disadvantages
Unreliable non-traditional data
Lack of collateral & higher default risk
Higher underwriting & risk management costs