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Frauds have long been a major concern for the finance industry. Traditional processes and models have become prone to numerous risks such as identity thefts, phishing, money laundering, and cyber crimes, etc. Now when the industry is witnessing massive growth, the danger of banking frauds has risen too.

According to Financial Fraud UK report, financial fraud losses across payment cards, remote banking and cheques have resulted in staggering £768.8 million in the year 2016. In a report by McAfee, the security company estimates cyber-crimes and frauds may cost the world almost $600 billion or 0.8% of the total global GDP. Another survey found that 64% of Americans had been victims of frauds resulting in the loss of money.

Current Scenario

It is certain that various companies in the finance sector are moving towards a technological revolution in the hope to enhance their safety quotient. However, failing to take the basic protective measures and products lacking adequate security have held them as an easy target.

As technologies are becoming more advanced, fraudulent schemes have become more complex. At the same time, the finance sector is witnessing breakthroughs with the use of technology to build the fight against frauds.

Regulations and standards governing the financial sector are continuously evolving in order to mitigate risks. Adoption of GDPR and PSD2 directives gives a clear indication that several anti-fraud strategies are being implemented to prevent frauds and safeguard consumers. These directives focus on consumer rights and data protection while promoting innovation in the finance industry (PSD2).

Most importantly, financial institutions are augmenting their banking framework, lending processes and controls to minimize the chance of frauds as well as reduce the chances of detection. They are reframing their methodologies to generate and manage data in such a way that the level of fraud recognized and prevented and losses incurred are identified.

Modern-day technologies like data science, artificial intelligence, and most importantly blockchain enable organizations to dig deeper into data and identify more effective ways to prevent frauds. Furthermore providing secure ways to store and process records online narrowing down the chances of human intervention.

Businesses active in the field

Digital advancements in the domain of data analysis such as deep learning, predictive analysis, data visualization, and other testing are useful to classify and manage data or find patterns, including those related to frauds.

Mastercard has announced to use Artificial Intelligence across its global network to build a more sophisticated business model. The company introduced Decision Intelligence, a comprehensive decision, and fraud detection service. The solution uses artificial intelligence (AI) to assist finance organizations to enhance the accuracy of real-time approvals of genuine transactions and reduce false declines significantly.

Another payment giant PayPal acquired a fraud prevention platform Simility, which offers end-to-end fraud and decision platform to fight frauds using machine learning. It uses a data-first approach to help financial institutions to find suspicious patterns and gain actionable insights into fraudulent activities.

Future of fraud detection

Fraud has been taking place through the finance sector and has only become complex. Fortunately, as technology is advancing, the industry is finding new ways to prevent and reduce fraudulent activities.

Achieving this will reduce overall fraud rates especially in the Fintech industry. AI, machine learning, and blockchain have the potential to shake up the entire banking and finance industry to eradicate frauds from the core.