The financial industry has long been suffered losses because of financial fraud and to minimize fraudulent transaction, financial institutions have deployed a lot of human capital to monitor transactions. With increased global transactions, the prominent to financial fraud occurrence increases, fortunately, today Artificial Intelligence (AI) has enormous potential to reduce financial fraud with smart, powerful and automated detectable tools. With AI the outlook of the future financial industry will exponentially improve.

Financial fraud a nightmare for institutions

Organisation hit by a financial fraud suffers from negative impacts on its reputation and also  it deters future prospects. To repair the situation and to gain back customer trust the organisation ends up paying for the losses. Moreover, as institutions tighten up their measures and system, the criminals also smarten up their tools and this makes things complicated to fight financial fraud. Most organisations are vulnerable to financial fraud and financial institutions top the list given a large amount of data and transactions being undertaken in that sector. Therefore it is indispensable to stop the fraud from happening and the wise way is to predict all suspicious action beforehand. AI comes to the rescue with the potential of setting up automated data science processes with deep learning algorithms that have the ability to detect suspicious transactions in advance.

Artificial Intelligence beats financial fraud 

With opening up of global markets, global transactions give rise to exposure of volumetric transactions and large volumes of customer data, which give prompt to the occurrence of financial fraud.

How AI helps to fight the growing financial fraud threat:

  • Identifying behaviour patterns: AI has the potential to identify credit card behaviour patterns and when irregular pattern and transaction place, customers can be informed before payment is released and thus preventing fraudulent credit card transactions in real-time. Moreover, the amount of details  AI can include together while finalising reports includes; from customer’s location, the device used, and other contextual data points to build up a detailed picture of each transaction. This increases customers trust towards financial products and also make transactions safer, a plus for both consumers and providers. 
  • Precision in Data Analysis: Vast amount of data and transaction can be analysed easily with AI tools that can simultaneously flag suspicious transactions in the financial system in real-time. When a fraudulent transaction is reported in real-time rather than after it happens, this already makes a big difference as in real-time the damage can be stopped. This system works as a high risk-based analytics approach making operationally efficient while detecting more fraud.
  • Eliminate the role of Fraud analyst: Financial institutions dedicated team of fraud analysts to detect suspicious transactions as a large amount of data are to be analysed. With AI automated tools and algorithms, the role of fraud analyst will be done by smart tools. The innovative approach of AI enables real-time extraction of cross channel data without much intervention of human capital. There the cost of human resources in the fraud analyst department will be hugely minimised with AI and the result will be more efficient and quick.
  • Smart decision with real-time detection: AI capabilities of liaising and dealing with a vast amount of data simultaneously enables effective attack detection on the spot. Anomalies detected can be remedied before they develop into a fraudulent transaction helping financial institutions to maintain reputation, customers to be safe along with smart human capital deployment and savings in many areas.
  • Achieving regulatory compliance: AI leverages policies adaptation as the supervision of the financial institutions is done in a more effective and efficient manner with minimal manual input. Decisions are unbiased as a large amount of data are considered simultaneously and human is involved at the minimal in reportings and final intelligent. This gives possibilities to constantly adopted policies for maintaining regulatory compliance saving banks time and minimize the potential of costly fines.