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Risk assessment with machine learning

Risk assessment logo

In many companies, the risk assessment process is antiquated.

Customers provide extensive information for evaluation, a process that takes a long time and, in many cases, is subjective.

Advanced analytics makes it quicker and more accurate for customers to get a quote while maintaining privacy boundaries.


  1. Objectives.
  2. Benefits.
  3. Approach.
  4. Conclusions.


Risk assessment refers to how a company identifies hazards and risk factors associated with the activity they develop that may cause any possible harm.

Depending on the activity sector of each company, several risk factors could arise. Some examples are credit and reputation risk for banks or the associated risk to evaluating a client's profile that takes out insurance for insurance companies.

Due to their exposure to clients and financial markets, banking and insurance are two of the main sectors to which risk assessment can be applied.

This helps to minimize the credit or market risks, among others, for banking and the risk of a wrong evaluation of the profile of a client that asks for insurance.

Some variables that can influence the risk are the following.


The results help companies better understand the existing assessment, significantly enabling them to streamline the process.


Use all the available information to identify potential hazards and risk factors and characterize them.


Assess how dangerous the risks are and evaluate the probability and reason of occurrence.


Draw a plan to eliminate the hazard if possible or set measures in motion to prevent the harm.


A correct risk assessment reduces the number of unexpected events avoiding losses due to bad decisions and increasing benefits.


Neural networks, thank to their ability to generalize knowledge, are an effective tool to quantify the risks of different activity areas of a company.

They also allow assessing the likelihood of risk occurrence based on objective reasons based on previous experiences.

Neural Designer is a machine learning software that can manage large amounts of data using the most suitable mathematical methods for the user's objective.

Neural Designer analyzes all the potential risk factors and their characteristics and assesses each of them according to the probability of occurrence and its severity so that your company can adequately act to prevent any possible harm. This information is arranged in a data set.

Depending on the case of study, the dataset could contain different information going from characteristics of a client to financial details of a company.

The accuracy of the assessment depends on the quality of the variables included in the dataset.

Neural Designer study the variables in-depth, so the most relevant ones are selected for the analysis.

The following image represents a neural network that could be used for this case.

Neural network

As inputs, it receives information about personal characteristics, family history, academic variables, and any other external variables that may be considered relevant.

As output, the neural network assesses the risk.


In conclusion, risk assessment enables companies to identify and avoid hazards and risk factors associated with their activity that may cause any possible harm.

Neural Designer uses artificial intelligence to discover the reasons and factor in order to avoid them and reduce losses.

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