AI has occupied a wide area in the current digital finance space. However, understanding the important challenges of AI deployment is critical for enterprises. Discussions around using AI in FinTech are becoming intense as more machines overtake the functions.
AI tools are invaluable for automation and servicing in finance and FinTech companies. They are useful for all functions- customers or business-related,
There are genuine concerns when allowing machines to make important decisions using data. Ethical considerations are important to follow to avoid incorrect use of AI that can damage outcomes for customers and businesses.
The Emerging Opportunities of AI in FinTech
AI can drive innovation and efficiency in the financial services and FinTech sector in several ways.
AI can help to create a savings and investment roadmap for customers based on their financial history.
It can also help businesses provide better customer connections by automating financial activities. Its ability to process large data sets results in speedy, scalable financial services.
It can also help in other services like risk assessments, personalized services, and fraud detection in finance and banking.
Today, AI is a strategic need for FinTech brands to stay ahead of the competition.
Challenges in AI for FinTech
Despite its widespread and accepted benefits, implementing AI is fraught with challenges.
Companies need to mitigate these before drawing any benefit from it.
Here are some of the challenges in the use of AI:
- If AI technologies are misaligned with the financial process, there are high chances of using incorrect AI-driven insights. It can lead to information asymmetry and complexity of data information.
- Misaligned algorithm parameters may lead to inappropriate decision-making from data to customer.
- Businesses may lack the resources and skills to implement AI. This will reduce the ability of companies to use the power of AI tools in the right places.
- AI is useful in cyber security applications—detecting, monitoring, and mitigating severe threats in the finance industry. Conversely, AI also adds bite to malicious apps that attack financial apps and databases.
- Biased algorithms may give rise to ethical bias in the tools. This will give unethical bias to the insights derived. The result could be completely unacceptable activities, communications, and decisions in the FinTech platform.
How does FinTech Mitigate These Challenges?
FinTech brands need to look for ways to eliminate these challenges. Only then can they use the power of AI to grow.
The protection of customers and financial processes, along with systems, should be a priority. Before companies use this powerful technology, stakeholders should set a strategy to implement AI.
A few more pointers will explain the importance of ethics while using AI:
- Fight Bias for reputation and trust: FinTech firms handle sensitive financial data and transactions. So, sticking to ethical considerations helps to create and maintain trust among customers, stakeholders, and partners. This also helps companies build a positive brand image, contributing to long-term economic success.
- Compliance with regulations: FinTech companies must adopt and meet regulations required in the financial sector. They need to comply with updated regulations and operate in a legal and compliant environment. Inability to comply with legal requirements will mean penalties, legal issues, and reputational damage.
- Protect and improve financial data: Companies should take proactive measures to avoid developing platform monopolies while implementing AI.
- Ensure data privacy: FinTech must comply with privacy regulations to protect against misuse of customer data. Companies should have strict privacy policies to prevent mishandling of data. Adding to it, there should be steps to handle data breaches or any other data discrepancy.
As per Gartner’s study in Hype Cycle for Privacy, 2021
- Transparency of AI use: Companies should be transparent about how AI algorithms work in their processes. There should be complete clarity on the data used- its source, type, and usage. It is an important step in removing biases and, thus, increasing consumer trust.
- Determining AI’s functionality: AI tools automate many routine and repeated financial tasks. Each step’s process scope should be well-defined to ensure accuracy and transparency.
- Regular upskilling of employees through training and education. This ensures that AI is deployed only after adequate training and skilling of the user team.
Also Read: Top Benefits of AI in FinTech
Conclusion
Using AI in finance brings significant opportunities and challenges for customers and businesses.
Without proactive efforts to understand and implement AI ethics, companies will find difficulties in taking advantage of the tech. Companies will also be unable to leverage their potential and power.
With proper mitigation strategies, FinTech and financial companies can use AI to innovate and design solutions for customer satisfaction.
