Start learning 50% faster. Sign in now
In the finance industry, predictive analytics thrives on real-time transactional data because it allows for timely and accurate risk assessments. For instance, detecting anomalies in real-time credit card transactions can prevent fraud or mitigate financial loss. Risk modeling depends on continuously updated data, enabling financial institutions to adjust predictions and make decisions proactively. Unlike static data, real-time data captures evolving trends, ensuring models reflect the latest customer behaviors and market conditions. This agility is particularly vital in risk-sensitive domains like finance, where timely action can prevent severe consequences. Why Other Options Are Incorrect: • B: Intuitive dashboards aid in communication but don’t directly contribute to predictive analytics. • C: Static data limits the ability to adapt to real-time changes. • D: Weather data is rarely relevant to financial risk modeling. • E: Visual reports are supplementary to quantitative models, not a replacement.
Match List-I with List-ll and select the right code -
On September 22nd, 2022 RBI had directed which Financial Services to immediately cease carrying out any recovery or repossession activity thr...
Calculate the spray fluid concentration when 1.5 l of monocrotophos 36 SC is applied over 2 hectare of chilli crop by making 1000 l of spray fluid. �...
LIC's women-focused initiative "LIC Bima Sakhi" is designed primarily to:
What is the capital city of Kazakhstan?
The aggregate demand in an economy severely outweighs the aggregate supply, is a situation occurs in which type of inflation in the economy?
What was the theme of World Environment Day 2024?
Lafarge, the world's largest cement manufacturer, founded in 1833 by Joseph-Auguste Pavin de Lafarge, is currently a part of which group?
Which part of the Indian Constitution deals with directive principles of state policy?
Cricketer Suresh Raina's autobiography was published in the year 2021 by which of the following names?