Artificial intelligence is likely the biggest contributor to the disruption of the fintech space in recent times. Traditional financial services have been buying up AI-powered tools and technologies to help them move into fintech as they aim to launch their own fintech apps in the industry to remain relevant. Incorporating AI into their fintech products helps their customers manage their finances more efficiently, in a convenient and safe environment. These AI-powered fintech products also provide valuable insights that help financial institutions innovate and provide improved services to their clients.
It’s no wonder then that artificial intelligence is taking the industry by storm. So, what are the different ways these financial institutions are using AI, and how can you leverage this emerging technology that is undoubtedly here to stay?
Read on for 10 ways to incorporate AI into your fintech product.
Artificial intelligence offers improved methodologies for better security measures, which are invaluable for businesses operating in the financial services space. The financial industry is particularly plagued by cyber risk, and AI and machine learning tools offer fintech the best opportunities to protect their user’s information and wealth.
One such opportunity is the use of AI models for chatbot integration that assists fintech users in recovering lost passwords and providing additional access. Identification via facial, speech and fingerprint are other security measures that present security opportunities to fintechs. Traditional passcode methods are more susceptible to cyber threats by hackers than personalised identification tools, which make your fintech product more secure and trustworthy.
2. Fraud Detection
Cyber risk isn’t the only threat to financial services. Credit card and loan scams, and fraudulent insurance claims are some of the other risks posed to fintech. Financial businesses are also required to balance customer experiences and maintain a positive reputation, as well.
Artificial intelligence is a great tool for enhanced cyber security to combat fraudulent activity. Specialised systems and algorithms can be implemented to monitor transactions and flag any suspicious or abnormal behaviour. A process that would otherwise require a substantial workforce as it is time-consuming and labour-intensive. AI makes fraud detection a simplified, streamlined process, allowing fintechs to react quickly and efficiently to correct fraudulent activity.
3. Algorithmic Trading
Algorithmic trading conducts stock trades by relying on pre-programmed instructions that help the system identify trading decisions and report on that data. This machine learning tool has been around since the 70s but has seen some recent upgrades since the introduction of AI.
Compared to older models, the artificial intelligence model has the capability to analyse millions of data points and provide keen insight to traders, all in real-time. This enhanced version of algorithmic trading is faster and more precise than older statistical models, thanks to its ability to identify further insights than previously possible.
What’s more, AI-enhanced algorithmic trading models are still progressing, and we’ll likely see more efficient iterations in future that are able to identify trading trends, react with relevant market trading, and pinpoint anomalies to take corrective action. All made possible by AI in fintech.
4. Robotic Process Automation
We’ve touched on chatbots as a front-end security measure for fintechs, but businesses operating in the financial services sector will be all too familiar with the back-end operational demands, and that’s also where chatbots, specifically robotic process automation (or RPA) can assist.
RPAs can automate a range of tasks, such as customer onboarding, inbound calls for general queries, as well as security checks, all tasks that are more client-facing. They are also able to process routine operations, such as loan applications and account information pertaining to credit cards or the closure of accounts. This integration helps fintechs save time and valuable resources to focus on the parts of the business that need their attention.
In the past, if financial services businesses wanted to analyse their historical data and report their findings, they would have to deploy teams to dedicate extensive amounts of time and resources to interpret the information. Artificial intelligence and machine learning solutions have revolutionised decision-making for fintechs, as they are capable of processing large amounts of data in a short period of time to produce accurate insights that are actionable.
Credit scoring and loan predictions are some of the top financial technology developments in recent times, thanks to the capabilities of AI. Financial institutions are better able to analyse clients’ credit scores to determine their risk and approve loans faster. They’re also able to make improved decisions regarding market trends.
6. Data Automation
Credit scoring is a valuable tool for understanding whether a client is capable and/or willing to repay loans. Artificial intelligence integrations for data automation, particularly in the field of credit scoring, are considered one of the most useful fintech product incorporations.
Credit scores are based on a statistical model that interprets multiple data points to provide insights. AI enhances this function by combining those data points, as well as further information such as income, credit history, and transactions, to relay individual credit assessments that are based on real-time factors. This provides financial institutions with accurate data analysis to make less risky decisions when it comes to providing loans. Not to mention that the accuracy of AI data automation makes providing financing to a broader audience safer and more accessible.
7. Analysis of User Behaviour
Artificial Intelligence Application Programming Interfaces (or AI APIs) are just another product integration that is powering the future of fintech. AI uses predictive analysis to determine user behaviour and respond accordingly by providing the information the user will likely request next.
AI achieves this by combining artificial intelligence and machine learning models so that users can better understand their data with detailed insights. Data automation not only processes the user’s initial requests but pre-empts the next request and provides that data at the same time, making the fintech product more efficient while minimising the number of input requests.
8. Customer Service
The digitalisation of services and artificial intelligence have made customers accustomed to fast, 24-hour service. The threat this poses to financial services is the possibility of losing those customers when instant gratification cannot be provided.
Artificial intelligence techniques like chatbots and virtual assistants can provide support to customer service (human) teams by responding to commonly asked questions and handling inquiries that can easily be automated. This allows customer service centres to focus on resolving concerns customers may have or tend to specialised queries.
Advanced sentiment analysis is another AI tool that seeks to understand the customer and solve their pain points, leading to retained users, referrals, and increased profits for the fintech.
Personalised services are a great advocate for brand loyalty, but the problem financial institutions face is the large number of customers they serve. Providing services that are tailored to the individual would be all-consuming, and in many instances impossible, if not for artificial intelligence.
Artificial intelligence processes user data to provide insights, make predictions and analyse behaviour, and it can use that same data to make suggestions to the user on how to tailor their fintech app to suit their needs, as well. This could take the form of financial advice, tracking metrics, or recommending product features.
10. Cost Savings
Artificial intelligence not only streamlines procedures and makes them efficient, but it also helps fintechs save capital, labour-related costs, and valuable resources. AI solutions take over routine operations that would otherwise be managed by human counterparts, so they can shift their focus to other areas of business. Artificial intelligence models are also more effective, quicker, and accurate, making AI a valuable resource for cost-reducing activities.
AI technology can be deployed across a range of business activities, as we’ve already seen throughout this article, and may take care of tasks such as providing accurate data and insights, recognising and reporting fraud or laundering, and underwriting credit, to name a few. This support means that financial institutions can offer improved services to their clients, saving costs but increasing profits.
One of the more recent use cases of AI in fintech that has caught our attention, is that of Goldman Sachs acquiring Clarity Money, a personal finance app that uses AI and machine learning algorithms to help users manage their finances, in 2018. This acquisition led to the development of Goldman Sachs own product: Marcus by Goldman Sachs. The very same digital banking platform that powers Apple Card, who have been in the news recently for offering a 4.15% return on cash in their savings account. Most banks offer a return of 0.01%, so this is big news and a very clear clue to how the incorporation of AI into fintechs is driving innovation and growth for the industry.
Artificial intelligence has progressed the fintech space leaps and bounds in a short period of time, offering startups and established financial service businesses alike opportunities to save costs, become more efficient and deliver an improved customer experience. The overarching goals of AI in fintech are to improve productivity and drive profitability, something that is readily achievable thanks to AI’s features like automation and predictive models.
Identifying key opportunities to incorporate AI into your fintech is a winning strategy that can only be supported by a team that understands, and can implement, AI-powered tools and techniques for your product. Reach out to Blott Studio’s team of developers to chat about artificial intelligence for your business.