In recent years, it has become easier to gain accurate customer data without worrying about issues like fraud or counterterrorism. Artificial intelligence has been widely used to analyze big data and obtain valuable insights to recognize a user.
This technology has primarily been helpful in tools like name matching software, a tool used by public and private entities alike. Machine learning makes it easier than ever to drive intelligent decisions and recognize users. Failure in accurate recognition can lead to security issues.
But can you rely on machine learning? Let’s find out.
What is Machine Learning?
With rapid technological advancements, machine learning has emerged as one of the most promising tools. It is employed in modern software systems to help with data-driven and intelligent decisions based on the data that has been analysed.
For example, it is widely used in recommendation engines. Based on the user’s data, machine learning can suggest tailored products or services to potential customers. In addition, matching uses machine learning to detect fraud and help with anti-money laundering applications.
In 2021, the market for AI and machine learning was valued at $15.44 billion. As technology continues to find applications in all spheres of life, the market promises to reach a value of $209.91 billion by the year 2029.
Intelligent Name Matching with Machine Learning
Consider an example to understand machine learning applications in this domain better. Suppose there are four names:
- Ed
- Edward
- Edwerd
- Eddward
It is easy to recognize that all of these are variations of the same name. Ed might be short for Edward, while the other two might be typos. While humans recognize these faster, it is simply not feasible to manually pick out every name through thousands of documents. The fatigue and repetitiveness might result in an impaired decision.
How Machine Learning Can Help
Computerized systems do not limit their abilities with tiredness or long hours. Machine learning can scout through thousands and potentially millions of records to match the names.
The best part? It keeps on learning. So, even if it makes errors initially, it will improve and facilitate better recognition in the future.
However, rarely do any errors happen. This is because the system is fed with data from all over the world, allowing it to recognize the correct name quickly.
Ways to Improve Machine Learning
Although machine learning is not a nascent technology anymore, it has significant potential for growth. However, the present form of machine learning can be improved by following the methods listed below:
- Define the problem case and identify the datasets to be used
- Optimize the model by retraining it with a different set of hyperparameters
- Rely on a random search to cover all bases
- Incorporate a robust baseline model that can serve as a reference for future model development
Despite these areas of improvement, machine learning plays a vital role in effective name matching. It will continue to get better as it is paired with more technologies.
While machine learning continues to make strides, it is gaining importance in multiple domains. Recommendation engines have traditionally relied on it. However, advanced applications like matching have helped unlock more technological applications.
