CFP InsurTech & Lending Technology Flashcards
6 cards from real CFP practice questions. Tap to flip, then mark Knew It or Still Learning โ missed cards come back until you master them.
Read the first 6 CFP InsurTech & Lending Technology flashcards as text
What is 'InsurTech' in the context of financial technology?
Answer: The use of technology innovations to improve the efficiency of the insurance industry
InsurTech refers to the use of emerging technologies such as AI, IoT, and big data to disrupt and improve the traditional insurance value chain.
Which technology allows InsurTech companies to use real-time driving data to price auto insurance policies?
Answer: Telematics and IoT devices
Telematics devices collect real-time data on driving behavior (speed, braking, mileage) to enable usage-based insurance pricing models.
What is 'peer-to-peer (P2P) insurance' in InsurTech?
Answer: A model where groups of people pool premiums to cover each other's claims
P2P insurance pools premiums from small groups of individuals with similar risk profiles, with unused funds returned to members at year-end, reducing moral hazard.
What is the primary advantage of using machine learning in credit underwriting for lending fintechs?
Answer: Analyzing thousands of data points to improve risk prediction accuracy
Machine learning enables lending fintechs to analyze diverse data sources beyond traditional credit scores, improving risk prediction and expanding access to credit.
What does 'marketplace lending' (also called peer-to-peer lending) refer to in fintech?
Answer: Online platforms matching borrowers directly with individual or institutional investors
Marketplace lending platforms like LendingClub connect borrowers seeking loans with investors seeking returns, bypassing traditional bank intermediaries.
Which U.S. federal law prohibits discriminatory lending practices that disproportionately harm protected classes?
Answer: Equal Credit Opportunity Act (ECOA)
The Equal Credit Opportunity Act (ECOA) prohibits creditors from discriminating against applicants based on race, color, religion, national origin, sex, marital status, or age.