Big Data Analytics Fraud Detection and Risk Management in Fintech

Similar to as fraudsters are becoming more comprehensive in their attacks, so too are avenues companies can guard their data. Big data analytics is crucial for fraud detection, prevention, and risk management. As per the Association of Certified Fraud Exmainers’ Reports to the Nations, organizations proactively using data monitoring can minimize their fraud losses by an average of about 54% and identify scams in half the time.

Big data analytics is alternating the patterns in which companies prevent fraud. AI, machine learning, and data mining tech stacks help counteract the hydra of fraud attempts affecting more than 3 billion identities each year.

In short, big data analytics techniques can help identify fraudulent activities and offer actionable reports used to monitor and prevent fraud- for businesses of all sizes.

1. Fraud Detection & Risk
Management in Fintech
Big Data Analytics
By Smartinfologiks

2. 1
2
3
4
5
Introduction
What is Big Data Analytics?
Importance of Big Data Analytics
Risk Analytics and Fraud Analytics
Role of Big Data Analytics in Fraud
Prevention
6
7
Big Data's Influence on Risk Management
in Fintech
Conclusion
Table of
Content

3. According to the Association of Certified Fraud Examiners, organizations
employing proactive data monitoring can reduce fraud losses by an average of
and detect scams in half the time.
Combat fraud and manage risks across various domains. Utilize big data analytics
for fraud detection, prevention, and risk management.
Introduction
54%

4. In this era where the amount of data is reaching a
mesmerizing size, we continuously hear about big data
analytics in every business and every system installed.
Big data analytics has completely revolutionised the entire
process. It refers to the process of examining huge and
complex data sets to uncover patterns, correlations, and
other helpful information that can inform business
decisions.
Widely applicable across business functions, enhancing
operations, reducing costs, and increasing profits.
What is Big Data Analytics?

5. Importance of
Big Data
Analytics
Enables quick decision-making through the
analysis of large volumes of data.
Facilitates predictions, enhances understanding
of customer needs, & optimizes products &
services.
Crucial in sectors like banking and fintech
for fraud and risk analytics.

6. Identify, Assess, and Manage risks using
data analytics.
Risk Analytics
Identifies and prevents fraudulent
activities.
Fraud Analytics
Big data analytics techniques for real-time decision-making.

7. Role of Big Data Analytics in Fraud Prevention
Identifies patterns of fraudulent activity and
anomalies in data.
Mitigates fraud risk by understanding
primary causes of fraud.
Utilizes techniques like data mining,
machine learning, and anomaly detection.

8. Big Data's Influence on
Risk Management in
Fintech
Provides a holistic view of potential dangers
and enables proactive risk management.
Requires robust data collection, integration,
predictive modelling, and real-time
monitoring.
Helps fintech companies respond quickly
to evolving risks and mitigate potential
losses.

9. Big data analytics is pivotal in fraud prevention and risk management in the
fintech industry.
Offers accurate prediction of potential risks and facilitates proactive
measures.
Utilize Smartinfologiks's Analytics101 for advanced business intelligence
and analytics software.
To know more about Big Data Analytics and Its Role in Fraud Detection and
Risk Management in Fintech, read our blog:
Conclusion

10. [email protected]
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