the financial services industry leveraging ai to help in fraud management

The Financial Services Industry Leveraging AI to Help in Fraud Management

What is AI?Artificial Intelligence or machine learning is a simulation of human intelligence and an application of technology that learns and works on problem-solving issues just like humans. It is used to enhance efficiency, effectiveness, and outcomes of any process or operation. AI is simply the machine intelligence that mimics human intelligence to understand and resolve problems arising in the operations of different industries.

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How AI is being used in the Financial Services Industry?The financial services industry is a vulnerable industry with much to put at the highest security possible. With a lot of data and money to secure from the sophisticated frauds and hackers, it is challenging for the financial services sector to not cope up with the upcoming trends in technology when the frauds are using it to disrupt their business.

For a better interface and to protect not just the banks and the whole sector but also the customers, it is crucial for the financial services industry to adopt technology and digital platform such as AI to avoid fraudulent behavior.


Let’s see what’s causing the fraudulent behavior in the first place

There are smart people who do wish to break into the security of such sectors. How do they do it is simply something that is for another time but what is making them do it is simply the availability of such high technology standards which are helping them to be better at it. With overseas frauds, it is quite clear how fraudulent behavior has become easy for them with the help of technology adopted by everyone. Also, the increasing usage of digital platforms for transactions by people is making it a strong point for the frauds to take advantage of it. But what we need here is to find such a tool/application that can break their level of technology and keep the data and money secure and safe.

This is where AI comes into view. AI is capable of expanding the existing models based on rules simultaneously strengthen the human fraud analysts significantly. This helps in enhancing the accuracy of the derived results while simultaneously offering efficiency and cost reduction.


AI helping in fraud management AI helps in fraud management with the help of use cases that are, however, a technical requirement for AI algorithms. Every use case prioritizes the technical requirements including- monitoring the transactions with the highest level of response rate, error rates, precision explicability, training data availability, quality, and ease of model building as compared to the other uses cases such as the fraud investigation and reporting

With a standard and high-quality data analytics, AI tracks and provides the ones present with errors or the ones found in an awkward position as per the AI algorithms.


Using the right Use Case for each Fraud Case

There are different kinds of frauds attempted and carried out which demands different algorithms from AI to detect and track them. So, AI uses different algorithms including knowledge graphics, supervised, and unsupervised learning, etc. What the financial services do is, they use and match the AI algorithm to common use cases, for example, the supervised learning algorithm dominates in the use case of transaction monitoring that demands exceptional performance and accuracy. Similarly, the use case of reporting demands the visualization tools, and the clustering algorithms are based on unsupervised learning.

A peek into the financial services frauds

AI and machine learning (ML) is saving the day with better tools to lead fraud management solutions in financial services. Helping in high security and risk management, AI technologies majorly provides a huge aid in the assessment and protection of data, services, and transactions. As cyber security is the prime requirement and demand for customers due to the widespread use of digital platforms and technology, online transactions require better protection and data security from hackers and smart fraudsters.

The frauds have definitely taken a rise since digitization became a normal and new way of transactions. With this increasing fraud, it is quite challenging and difficult for the financial services sector to protect itself and its customers.



Moreover, as per a Juniper Research report, cybercrime currently costs the global economy approximately USD $600 billion (i.e. 0.8% of global GDP) annually, out of which online transaction fraud accounts for the biggest chunk – this is expected to hit $25.6 billion by 2020. Also, Ravi Shankar Prasad, India’s minister for information technology, mentioned that there were more than 25,800 cases of digital fraud in the country in 2017, resulting in the theft of nearly ₹1.8 billion rupees. The financial services sector now aims not only on the financial risks mitigation but also aims at detecting fraud in real-time. The fraud strategists are seeking to attain more of a holistic view of the landscape of threat and risks in the financial services sector for effective detection and deterrence. They are also moving forward to adopting a multi-layered defense system for balancing the strategy. AI is helping the sector to work and gain a balance between robust measures to counter the fraudulent behavior and offer a secure and positive customer experience

How ML & AI Prevent Fraudulent BehaviorWith a majority of cases coming up of fraud behavior, the majority of financial institutions and banks are turning to advanced solutions technology such as ML (machine learning) and AI (artificial intelligence).

ML is the reason for the stir that occurred in the fraud detection domain due to its high quality.

Learn how ML helps in fraud detection:


It has the ability to deal with a huge amount/large volume of data present or collected from numerous sources.

It is capable of identifying and spotting the abnormal patterns and links in the data, unlike humans.

It acts as the most viable tool for fraud detection due to its high-quality outcomes that have high validity too.

Fraud Detection MethodsThe fraud detection methods are getting better with each passing day and with more and more technology and digital adoption by the financial services sector.


ML, if trained correctly has the ability to identify patterns and consumer behavior.

ML is used as a method to protect companies from the frauds happening at the internal level by studying and accessing data present within the organization.

ML has the ability to even read and mark any kind of irregularity in an individual's system or data differing from the day-to-day work and the exposure of data to unauthorized people.

When ML collaborates with AI, it gets the ability to run over the algorithms study or the only method of detecting fraud to the smart methods one.

AI helps the machines to be programmed to learn on their own without any supervision to track the transaction patterns and filter out the ones which do not match the regular or normal pattern in such a way that they can be provided support in real-time.

AI & ML as the aiding factor for the BFSI With the help of AI along with ML, the BFSI industry has gained a lot of profit not just in preventing fraudulent behavior but also protecting its customers and gaining their respect and value. Now, both the advanced solutions technology not only helps in the prevention of frauds and protection of data and money of the people, but it has also led it towards growth in the market with a boosting revenue along with valuable insights into the customer behavior, their reference, and expectation from the companies. Understanding customers and fulfilling their expectations is the prime need of every business and with this, the BFSI sector is going towards greater success.

Also, as per a National Business Research Institute survey, over 32% of financial institutions globally use AI for predictive analysis.



Also, as per a National Business Research Institute survey, over 32% of financial institutions globally use AI for predictive analysis.

PwC’s Global Economic Crime and Fraud Survey states that 49% of global organizations have experienced financial crime in the past two years. As global transactions over digital channels are increasing, the possibility of electronic fraud is also increasing with it.

https://www.pwc.com/gx/en/forensics/global-economic-crime-and-fraud-survey-2018-summary-infographic.pdf


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the financial services industry leveraging ai to help in fraud management

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