There is a significant upsurge in the tech-centered financial services companies in recent years. The fintech has emerged as a significant player in the way we manage our money. It is responsible for a whole range of innovative financial products, from money-transfer apps to mobile payments, shares trading and investments to crowdfunding and peer-to-peer lending. Digital solutions allow instant access to banking services without sacrificing simplicity, security, and user experience.
The financial sector has been storing data for a long time and has massive pipelines of structured and unstructured data. Many intelligent technologies like artificial intelligence (AI), machine Learning (ML), and advanced analytics can leverage this data for analysis, which can help companies to make informed decisions about their business processes. Here is a detailed analysis of the impact of intelligent technologies on the finance sector:
Eradicating Risk: Financial companies conduct high-value transactions every day, making them prone to risks. A small error can cause a catastrophe for an organization. Implementation of Robotic process automation (RPA) can mitigate the risk of human error or any deliberate fraud. RPA can also be beneficial in areas like compliance regulations, anti-money laundering activities, know your customer (KYC) initiatives, etc.
Fraud Detection: Cybercriminals are always on a lookout to find loopholes in the security of financial services companies. Artificial intelligence tools can provide promising defense as these tools can be used for various applications like customer authentication, suspicious transaction examination, and many others. ML techniques and advanced analytics can provide fraud score to transactions, enabling companies to differentiate between fraudulent and authentic transactions.
Operational Efficiency: Finance companies are one of the most operationally intensive companies. The operations involve various manual as well as automated tasks. While RPA can be instrumental in automating manual as well as repeated tasks, Adding AI and ML capabilities can improve the robustness of the automation initiatives and drive sustainable improvement for overall operations.