10 Remarkable Ways AI is Transforming the Financial Industry

By Susan Hu

Introduction

Artificial Intelligence (AI) has already brought paradigm shifts across industries around the world. It has enabled teams to operate more efficiently and more effectively. AI is addressing traditionally unsolvable problems and challenges with comprehensive approaches, providing new space for innovation. According to a PwC report, AI could contribute up to $15.7 trillion to the global economy by 2030.

Among all industries that have been adapting AI, the financial industry has been at the forefront. Financial institutions handle enormous amount of data and work with complex processes every day. Thanks to the development of AI, they are now able to redefine day-to-day workflow and revolutionize everything from process automation to advanced analytics and advisories.

In this post, we will explore 10 remarkable ways AI is transforming the financial industry and how your organization should be using AI to up its game as well.

10 remarkable ways AI is transforming the financial industry

Anti-Money Laundering

A recent Dow Jones-sponsored ACAMS surveyreveals that false positives are one of the most challenging area for financial institutions when it comes to the fight against financial crimes. AI has been playing a game changing role in banks' efforts against such crimes, including money laundering by significantly reducing the false positives and increase accuracy.

Many banks are now using AI to automatically learn behavior, relationships and flow risks to reduce false positives and detect unknown unknowns in money laundering activities. Using AI, banks are now able to process and store data in a more structured way, detect abnormal activities and identify suspicious money laundering activities more effectively and accurately.

Ecommerce Anti-Fraud

Fraud is one of the biggest concerns the financial industry faces, especially with the rapid increase of ecommerce and online transactions. Now banks are able to utilize AI to detect various of fraud activities in real-time effectively.

AI Ecommerce Anti-Fraud system analyzes complex information of a transaction. For example, it considers one's online behavior, buying history, location, interests, etc. When abnormal/unusual transaction happens, AI can notice it based on the established spending pattern and trigger an alert. It is so much more accurate than the traditional rule-based anti-fraud approach implemented in the past.

Trade Finance Due Diligence

Due diligence involves verifying various of documents and information about a customer or a business, to ensure they are providing true, accurate information about themselves. Banks and financial institutions can now use AI to analyze institutional customers, detecting any abnormal activities, and therefore access the risks associated with each customer including their possibility of fraud, or engagement in other financial crimes.

AI is able to transform a traditionally manual, time consuming and incomplete process to a highly efficient automation.

Regulation Interpretation and Audit

AI has an ability to detect patterns in a vast amount of information within a short period of time. Using Machine Learning (ML) and Natural Language Processing (NPL), Ai can recognize regulations, reason auditing reports, and analyze impacts.

AI quickly establishes understanding of complicated, every changing regulations. It helps to analyze and classify documents, extract useful information and keep financial institutions up to date with any regulatory changes so they are compliant and ready for audits.

Know Your Customer (KYC)

KYC is a complex process that is often required for Due Diligence and AML. Banks and financial institutions need to acquire and verify customer's information and make assessments on the customer's potential risks. AI can analyze individual customer data and institutional customers, knowing their businesses in much more efficient and complete way. Saving banks enormous manual labor and time.

Non-Performing Loan Prediction

AI offers a faster, more accurate assessment when it comes to Non-Performing Loan prediction.

By utilizing Graph Database (DB) and Machine Learning (ML), AI analyzes different aspects of an account including its relationship with accounts, largely improving the accuracy of predicting non-performing loans risks, especially comparing to rule-based methods traditionally used. AI is able to identify high default risk applicants based on their related accounts, credit history, among other complex information.

Investment risks and decision prediction

AI has an enormous computing power to process huge, unstructured data within a short time and give real time feedback. Financial services are now utilizing AI to assist Investment companies on finding potential targets, estimating risks, etc.

AI is especially powerful when it comes to real-time analytics of any given market. Its accurate prediction is valuable for any organization to access investment risks and make decisions.

Market Intelligence

AI powered Market Intelligence automatically collects public information, forming knowledge graphs and database. It is constantly monitoring what's happening in the marketing on a large scale. Extracting relevant information and create alerts related to the portfolio.

AI reason behaviors in a large scale, analyze motivations, predict impacts & propagation, judge whether a piece of information is true or fake, gauge intention, analyze geospatial and cultural impacts, etc. Such market intelligence provides much insight for analysts, subscribers, AI traders, etc., to assist them to better understand real-time market changes.

AI Traders

Data-driven investments have been rising steadily over the last few years and closed in on a trillion dollars in 2018. Known as algorithmic, quantitative or high-frequency trading, AI Traders are now in the market helping people make investments.

AI traders often provide many different personalized strategies and personalities that are customizable for each user. The AI traders act on behalf of the customer and execute different strategies based on each AI trader's learning experience, which is based on past trade records.

Robo Advisory

Robo advisory is becoming more and more common across all industries. Within the financial industry, institutions are now using AI to provide intelligent wealth management advisories based on various of factors including alternative database, market intelligence, AI trading strategies, etc. Some are even offering robo-investment advisories in addition to human analyst advisories.

Closing

Without a doubt, AI already has a huge impact on banks and financial institutions. Many are redefining their services, processes and data to enable an AI empowered workforce across the financial industry.

It's not too late to rethink your organization and how you can start implementing AI to improve efficiency, security and productivity. Remember Rome was not built in a day. Rather than completely revolutionize your bank, start small and slowly you will transform the landscape.

Graphen offers all these gaming changing solutions for financial services. Learn more about our next-gen AI approach for the forward-thinking financial institutions.

If you want to learn more about how to adopt and implement AI in the financial industry or want to dive right in with Graphen's AI Finance solutions, please reach out to me at susanhu@graphen.ai.