FinTech Exam 2 complete exam
questions and answers.
Internet of Things (IoT) - CORRECT ANSWERS a world where interconnected, Internet-
enabled devices or "things" can collect and share data without human intervention
AI and Machine Learning in Finance - CORRECT ANSWERS Used to assess credit, optimize
scarce capital, find signals for higher returns and optimize trading execution, used by public and private
sector for regulatory compliance, surveillance, data quality assessment and fraud detection
Machine Learning - CORRECT ANSWERS Seeks to extract info from large amounts of data.
Goal is to automate decision-making processes by "learning" from known examples to determine an
underlying structure in the data. Emphasis in on the ability to generate structure or predictions from
data without human help.
Deep Learning - CORRECT ANSWERS Relies on sophisticated algorithms to address highly
complex tasks, such as image classification, face recognition, speech recognition, and natural language
processing
Supervised Learning - CORRECT ANSWERS Uses algorithms that infer patterns between a
set of inputs and labeled output. The inferred pattern is then used to map a new input set into a
predicted output
Unsupervised Learning - CORRECT ANSWERS Does not use labeled data. Because the
algorithm is not trained with labeled output data, the algorithm seeks to discover structure within the
data themselves
Applying Machine Learning to Investment Management - CORRECT ANSWERS Exploding
volume and diversity of data, as well as increasing economic value of insights extracted from basic data,
have made a basic understanding of data science an important part of the tool kit for investment
management
, Artificial Intelligence - CORRECT ANSWERS Application of computational tools to address
tasks traditionally requiring human sophistication. Can be applied to the problem of big data
Reinforced Learning - CORRECT ANSWERS Falls in between supervised and unsupervised
learning. Algorithm is fed unlabeled data set, chooses an action for each data point, and receives
feedback that helps the algorithm learn.
4 V's of Big Data - CORRECT ANSWERS Volume, Velocity, Veracity, Variety
Volume - Big Data - CORRECT ANSWERS Huge data size, terabytes - perabytes
Velocity - Big Data - CORRECT ANSWERS High speed of data flow, change and processing
Variety - Big Data - CORRECT ANSWERS Various Data Sources (Social, Mobile, M2M,
structured and unstructured data)
Veracity - Big Data - CORRECT ANSWERS Various levels of data uncertainty and reliability
Blockchain technology - CORRECT ANSWERS A form of distributed ledger technology(DLT).
Transparent transactions that are secure and synchronized. Transactions are put into a block and each
block is connected to the one before and after
Distributed Ledger Technology (DLT) - CORRECT ANSWERS Records the exchange of
money, how goods flow through a supply chain or making contractual agreements
3 Key features that make Hyper Ledger Technology unique to a regulated industry - CORRECT ANSWERS
1. Distributed - works as a shared form of ledger keeping so no one person owns the ledger system
2. Permissioned
questions and answers.
Internet of Things (IoT) - CORRECT ANSWERS a world where interconnected, Internet-
enabled devices or "things" can collect and share data without human intervention
AI and Machine Learning in Finance - CORRECT ANSWERS Used to assess credit, optimize
scarce capital, find signals for higher returns and optimize trading execution, used by public and private
sector for regulatory compliance, surveillance, data quality assessment and fraud detection
Machine Learning - CORRECT ANSWERS Seeks to extract info from large amounts of data.
Goal is to automate decision-making processes by "learning" from known examples to determine an
underlying structure in the data. Emphasis in on the ability to generate structure or predictions from
data without human help.
Deep Learning - CORRECT ANSWERS Relies on sophisticated algorithms to address highly
complex tasks, such as image classification, face recognition, speech recognition, and natural language
processing
Supervised Learning - CORRECT ANSWERS Uses algorithms that infer patterns between a
set of inputs and labeled output. The inferred pattern is then used to map a new input set into a
predicted output
Unsupervised Learning - CORRECT ANSWERS Does not use labeled data. Because the
algorithm is not trained with labeled output data, the algorithm seeks to discover structure within the
data themselves
Applying Machine Learning to Investment Management - CORRECT ANSWERS Exploding
volume and diversity of data, as well as increasing economic value of insights extracted from basic data,
have made a basic understanding of data science an important part of the tool kit for investment
management
, Artificial Intelligence - CORRECT ANSWERS Application of computational tools to address
tasks traditionally requiring human sophistication. Can be applied to the problem of big data
Reinforced Learning - CORRECT ANSWERS Falls in between supervised and unsupervised
learning. Algorithm is fed unlabeled data set, chooses an action for each data point, and receives
feedback that helps the algorithm learn.
4 V's of Big Data - CORRECT ANSWERS Volume, Velocity, Veracity, Variety
Volume - Big Data - CORRECT ANSWERS Huge data size, terabytes - perabytes
Velocity - Big Data - CORRECT ANSWERS High speed of data flow, change and processing
Variety - Big Data - CORRECT ANSWERS Various Data Sources (Social, Mobile, M2M,
structured and unstructured data)
Veracity - Big Data - CORRECT ANSWERS Various levels of data uncertainty and reliability
Blockchain technology - CORRECT ANSWERS A form of distributed ledger technology(DLT).
Transparent transactions that are secure and synchronized. Transactions are put into a block and each
block is connected to the one before and after
Distributed Ledger Technology (DLT) - CORRECT ANSWERS Records the exchange of
money, how goods flow through a supply chain or making contractual agreements
3 Key features that make Hyper Ledger Technology unique to a regulated industry - CORRECT ANSWERS
1. Distributed - works as a shared form of ledger keeping so no one person owns the ledger system
2. Permissioned
