AI as a New Hope for the Financial Industry
Artificial Intelligence organizes data chaos and offers a completely new, personalized experience for users of financial services. Thanks to mechanisms that build loyalty, AI helps banks and insurance companies to keep existing customers while gaining new ones. Artificial intelligence also assists in the detection of anomalies and prevents frauds. Contrary to appearances, it does not prohibitively expensive and does not require extensive, long-term implementation. What else do you need to know about AI for finance?
Technology is driving the industry faster than you think
Banks and insurance companies have invested heavily in technology to provide the customer experience that is standard in other sectors. The development of technology has enabled the financial industry to attract consumers and has made personal finances and future planning, including retirement, more understandable and accessible to ordinary people.
Mobile banking has become standard over the last few years, as we have access to mobile payments while using smartphones and other ways of streamlining financial transactions. Online banking is easy and we can get offers on loans, insurance and other products by text message or email. We can make transfers from our phones and make use of applications that enable even more possibilities.
Thanks to developments in fintech, banks have leveraged technological enhancements into a revolution in the services they can provide while transforming the traditional customer experience. Intelligent systems also help in the fight against frauds and hackers while delivering more secure connections through, for example, biometric logins.
The side effects of progress
This technological revolution in the financial industry has made life easier for all of us, but it has also brought side effects in the form of a huge amounts of new data created by clients of banks and insurance companies, e.g. through the use of mobile applications. Managing this data is a challenge for financial institutions, which, in fairness to them, cannot be managed by any person or even an entire department of people. Getting real business value out of this data is a challenge that requires other approach.
This is why modern banking management is embracing the use of Artificial Intelligence, which has become essential to meeting customer expectations and staying competitive in the marketplace. Solutions based on AI, however, open the door to more than just customer engagement. Specialized platforms are now capable of not only helping with customer retention, but of generating powerful insights into the behavior of users for the purposes of creating personalized offers and experiences while identifying anomalies and generating new profits.
AI to the rescue
Solutions built on Artificial Intelligence algorithms, help in four important areas in the development and security of every financial institution. They provide:
- Credit risk management
- Increase in operating profit (e.g. by up-sale or cross-sale through AI recommendations, personalized offers and churn management)
- Streamlining of processes and automation of repetitive tasks
- Optimization of sales and the operations of B2B and B2C sales
AI’s vision into the future
For banking, the predictive powers offered by solutions based on Artificial Intelligence is particularly important. Algorithms can significantly improve the work of analysts who have to make decisions regarding credit. Calculations that can be made in real time by machines based on AI allow them to predict creditworthiness and better estimate the risk involved.
The calculations use data based on customer histories and many other demographic and behavioral factors. Artificial intelligence builds real-time scoring based on current expenses and other metrics that create better customer profiles that evaluate their ability to repay loans. There are also advanced anti-fraud systems that detect anomalies and, for example, block the accounts of persons who suddenly begin to perform operations that are inconsistent with their previous behavior. All this allows for better control of financial risk.
AI in the financial industry can also significantly optimize processes. Analysis of customer activities within financial products allows to shorten the average time to solve emerging problems in the availability of services. Also, repetitive processes can be simplified due to their ongoing analysis.
AI provides insights on the basis of which relevant departments can simplify processes, moreover, the simplest ones can be automated, e.g. a customer interested in a specific offer (website visited), included in an automatic communication or promotion path, enabling faster conversion.
AI can also have a significant impact on reducing the time needed to onboard new customers in the banking system. Based on the most frequently visited or clicked system components, the bank or insurance company is able to determine the key resources that the user should know, and then customize the appearance and availability of the application for them.
It is also important for the various departments of financial institutions to deliver continuous growth. At a time when customers are empowered as never before and competition increases, providing better sales results has become more difficult.
AI offers a lot in this area, including creating propensity modeling capabilities. This makes it possible to separate from the database of identified and anonymous clients those who have the highest chances for conversion, and then focus sales and marketing activities on them.
Understanding clients and increasing income
Segmentation based on Artificial Intelligence algorithms also makes it possible to shorten the sales cycle and learn more about customers. Understanding the decision path and purchasing propensity, in this case the propensity to sign a contract, is crucial to increasing the number of new users of financial products.
Measuring the source of traffic
Another tool that AI provides to marketing departments is attribution models that make it possible to check which activities and which content distribution channels have the most effective reach and conversion efficiency. Platform solutions like Synerise provide a complete tool that allows both the analysis and execution of personalized communication and an increase in the efficiency of marketing channels.
Increasing opportunities to make a sale are also enhanced by "next best offer" abilities, solutions that allow you to make offers on the basis of current user-owned products.
Artificial Intelligence plays a supporting role in this area, analyzing client decisions on an ongoing basis and selecting products that complement their needs. This is essentially a more advanced recommendation model of the type that we see when shopping online. A new keyboard and mouse will be useful for the new computer, and it would be worth choosing an individual savings account for the life insurance policy.
AI algorithms can also support customer relationships by deciding whether it’s best to present a sales offer (NBO) at a given moment, or choose the "next best action" model and offer the customer an action that is not directly related to sales, but which will strengthen customer confidence in the bank.
Always and everywhere
Banks and insurance companies, despite the fact that a large part of their resources have been allocated for online activities, still remain one of the largest owners of the network of fixed physical locations where customers can go. Can AI have any impact on process improvement in this context? Omnichannel activities can be supported by Artificial Intelligence.
On the basis of previously collected customer data, AI platforms can provide consultants in institutions with a range of useful information. Using this data, they will be able to promote the most tailored and beneficial offer when the client appears in person. It is also possible to integrate with the call center of a bank or insurance company, giving consultants a live view of client histories.
Based on detailed knowledge of customer behavior (like price sensitivity, readiness to buy, etc.), AI algorithms can inform a banking advisor on how to talk to a specific customer and can even display a conversation script tailored to the client's character.
In online channels, such as a website or mobile application, and even at ATMs, it is possible to personalize offers, including adapting the appearance and functions to specific user needs. Thanks to the mobile SDK, without the need to constantly update the application in the App Store and Google Play, platform operators can supply dynamic content in real time and even decide on the order of the displayed items.
The capabilities of AI are not just confined, to theory, however. They have proven themselves in practice as well. According to Synerise internal data one of the banking leaders in Poland increased conversions from mobile campaigns driven by AI algorithms by over 300%, and the number of inquiries for new credit cards by more than half. The campaign was personalized for customer segments selected by Artificial Intelligence.
This is just one of many examples of the use of Artificial Intelligence in banking. Today, it is worth having an intelligent friend who is able to sort through massive amounts of data and identify the information that is essential for business development. Also, in light of regulations regarding sensitive data, companies in the financial industry can choose to implement such a solution on their own infrastructure (on-premise).
To ensure real-time data processing, cloud servers (Microsoft Azure) or a dedicated bank infrastructure (the aforementioned on-premise) and, in the case of Synerise, an ultra-fast database are used for their analysis. The price of a solution like this is dependent on the number of queries processed by the system. Regardless, maintenance costs are disproportionately low to the profits that AI can generate in banking, making the technology worth the investment.