Risk management is important for companies to make better investment decisions and avoid losses. It involves identifying and managing internal and external risks through plans and policies. Companies use data analytics in risk management for various purposes like risk management planning, fraud detection, forecasting losses, and contingency planning. Data analytics allows companies to analyze past data to identify issues, formulate risk policies and strategies, detect fraud, predict losses accurately, and create robust contingency plans by assessing risks. This helps companies minimize risks and promote growth.

1. Analytics in Risk
Management
Mathangi N
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2MAECO

2. Risk Management
Risk and uncertainties have a great impact on the functioning of a company.
It determines the entrepreneurial activities, investment decisions and the
policies that the company implements and follows. It is one of the biggest
hurdle in the way of the growth of a company. Hence, the management of
the risks both short term and long term enables the companies to take up
better investment decisions and to not sustain losses. Hence identification
and management (through plans and policies) of internal and external risks
has become one of the major concerns of companies. The risk management
team of a company has to make a list of the risks the company may come
across according to the severity of the risk. The more severe the risk, more is
the adverse impact it has on the growth of a company and hence they
require more attention and faster management. Companies like McKinsey &
Company, Deloitte etc provide risk management services by use of data
analytics.

3. Data analytics in Risk Management
• Risk management planning.
• Fraud Detection.
• Forecasting losses.
• Contingency planning.
• Credit scoring.
• Compliance measurement.

4. Risk management planning
Data analytics in risk management is not only important for growth of
businesses but also for withstanding the existing competition. Analysis
of the what went wrong in the past and diagnosis of the issues in the
organisation is possible with the use of data analytics. The companies
that make use of data analytics in risk management can formulate
policies and strategies against risk or to minimise it.

5. Fraud Detection
All companies come across fraud and one of the most efficient ways to
deal with it is the use of data analytics. The data analytics tools can
handle large quantities of information at the same time. It enables the
identification of the red flags that could cause problems . The company
can accordingly adopt policies and strategies to combat these issues
and stop spending large amounts on fraudulent claims and increase
safety of the workplace.

6. Forecasting losses
Losses are a huge cost of doing business. Continuous and huge losses
are unhealthy for the company and hence there is need for correct
prediction or forecasting of losses. A risk plan that has been formulated
on the basis of data analytics will enable businesses to prevent losses
and promote further growth.

7. Contingency planning
Contingency planning is the plan B that each company is to have as a
protection against uncertainties. They are plans made in response to
risks. Every organisation or company or industry faces its own unique
set of risks. An assessment of these risks, identification of potential
threats etc is crucial so as to formulate a robust contingency plan and
this risk assessment is done with the help of data analytics. The
company must trial run its contingency plan and update it from time to
time.

8. THANK YOU