Every industry is moving to adopt AI, even as initial glowing reports about its capabilities are dwindling into acceptance that Generative AI (GenAI) still has a long way to go before it can solve all our problems. At the same time, it’s already ringing in new opportunities for cybercrime.
But financial institutions have urgent reform needs, and they can’t wait for the dust to settle before they adopt aspects of autonomous finance. The financial services industry should move swiftly or risk getting left behind.
There are many great reasons why companies should adopt GenAI, yet experts warn that malicious operators have the same access to the same automation tools that everyone else has and that the industry should approach GenAI with an emphasis on cybersecurity.
The Perpetual Threat Of Cybercrime
The financial industry is highly cyber-dependent. It relies on digitisation, mobility, and high-speed connectivity. At the same time, the public has a low awareness of cyber security threats. Scammers and hackers operate with astonishing ease, leading to skyrocketing figures for cybercrime.
Even as the financial services industry stands poised at the cusp of renewal, cybercriminals have already adopted GenAI wholescale. They use it to create new malware, write ransomware encryption tools, discover new exploits, and turbocharge their scam and fraud syndicates.
Customers Are Taking The Financial Industry to Task For Cybercrime
Could the financial services industry grab this opportunity to improve customer protection? It would mean adopting a cybersecurity-first approach where they reward people’s awareness of digital privacy, threat detection, and malware protection. They’ll have to play a prominent role in educating people about the most common financial threats, how to spot scams and stay safer online.
The many ways AI can improve the industry:
- Customer-facing auto-assistance: Chatbots or virtual assistants that have been trained on proprietary data can provide accurate, detailed answers to customers’ questions. They can be used to provide basic assistance, such as account queries, for improved customer support. But a more ambitious project could be to improve customer education. Chatbots can be used to democratise access to knowledge about, e.g., regulatory compliance, accounting principles, financing, or stock analysis.
- Automating Workflows: Streamlining repetitive and time-consuming tasks, such as data entry and processing, to free up people’s time and plug skills gaps.
- Document analysis: Extracting valuable information from voluminous financial documents like annual reports or financial statements.
Marketing and growth strategies: GenAI will have a profound impact on businesses’ ability to craft personalised marketing messages. It can fine-tune content to ensure that it resonates with individual customers.
- Financial reporting and documentation: Financial reports, forecasts, or cash flow statements need close attention by skilled humans to escape errors and inconsistencies. GenAI could soon create error-free financial reports based on the data it ingests. It will save time but will also ensure consistency and accuracy across organisations.
- Trend analysis: AI can spot those subtle patterns which humans may miss when dealing with very large databases. It’s better than humans at identifying complex trends that may influence business decisions.
- Predictive analysis: It can generate complex scenarios if you provide it with different macroeconomic factors and other variables. It may be better than most humans at predicting future trends, asset prices, and economic indicators.
- Portfolio optimisation: GenAI can be set up to consider personal factors to navigate unique risk landscapes. Asset managers could, for example, include personal factors such as risk tolerance, goals, personal preferences, or even medical profiles in financial planning scenarios.
- Credit risk management: GenAI can significantly speed up credit applications by analysing a set number of factors, e.g., income, credit history, age, employment status, and more.
- Using AI to accelerate digital conversion: Apart from basic projects like digitising documentation and moving from physical to cloud storage, GenAI can also improve digital architecture and platforms. For example, many banks still depend on legacy software written in vanishing legacy programs like COBOL. GenAI is good at writing code. It can help to maintain old software or rewrite the code in modern languages to modernise software.GenAi in fraud detection scenarios
If organisations adopt automated workflows, they can enhance customer compliance with Anti-Money Laundering (AML) and Know Your Customer (KYC) protocols.
But they can also use GenAI’s expertise in manipulating Big Data for faster detection and prevention of fraud. GenAI is the ideal tool to spot anomalies or fraudulent activity in real time. It could be a game-changer in the fight to prevent financial losses and protect sensitive information. And incorporating GenAI into fraud detection systems will improve any organisation’s cybersecurity posture.
The Simple Ways To Detect Scams Don’t Work Anymore
But even while financial institutions build cybersecurity into each operation, their customers may still be blissfully unaware of the dangers of GenAI. Criminals are using it to enhance phishing and malware attacks. The cybercrime statistics are eye-watering and set to increase.
If financial institutions keep falling prey to data breaches at the current rate, they may be forced to take more responsibility in keeping their customers safe because criminals use the hacked information from data breaches to weaponise GenAi and improve swindles and scams.
Financial institutions are on the brink of transforming how they operate, analyse data, and make decisions. But the industry is cyber-dependent, and any transformation should be done with cybersecurity and customer protection in mind. It may have to play a far more active role in helping to secure the landscape and teach people how to stay safe.