There is hardly any banking expert who will disagree with the fact that Artificial Intelligence (AI) is on the verge of transforming the banking sector this decade. However, if we dive a bit deeper, we will realize that the AI disruption is not just going to be limited to banking. It will transform the very nature of financial services. For instance, smart AI algorithms can aid bank advisors in receiving funding or suggesting agendas that suit customers.
AI technologies can aid in boosting revenues through improved personalization of services to both employees and customers. They can cut costs through efficiencies yielded by a higher level of automation, reduce errors rates, and optimize resource utilization. They can also uncover new & unrealized opportunities, thanks to their superior ability to process and render insights from huge volumes of data.
Impacts Of AI In Banking
Banks amass a ton of data about the customers, which has mostly remained unharnessed till now. Realizing the highest potential of this data mine requires AI.
The massive magnitude of collected data is just the tip of an iceberg. The proliferation of digital technology will furnish an abundance of new data to every financial organization. From users’ phones to social networks to public service APIs and third-party banking APIs, the data points are numerous.
Despite its hurdles, Artificial Intelligence is improving the finance industry in the following ways:
- It provides an easy way to immediately spot suspicious activity.
- It enables financial organizations to make more informed investments and serve a larger consumer base.
- With its enhanced accessibility & flexibility, it provides a more user-friendly experience for customers.
Let’s take a detailed look at some fields where banking experience can be drastically improved by AI:
1. Better & Personalized Offers
AI can be utilized to deliver precise client credit ratings which are not solely dependent on the bank’s profile and credit history. AI can be used to take into account offline behavior on social profiles, resulting in personalized recommendations for each customer. It also minimizes the risks of banks.
Also, personalized offers make it easier to match the users’ demands with the right product, at the very moment they require it.
AI systems in banks are capable of moving the bulk of verification technicalities to the background. This can not only instill trust among customers for digital banking but also move it to make it a smooth and faster experience without any need to confirm identification at various steps.
Also, AI can run cyberattack simulations to assess a bank’s cyber-defenses and anticipate potential damages that can threaten the security systems. Additionally, it also aids organizations to safeguard PII (Personally Identifiable information), which is a major requirement for banks.
3. Better Advisories Can Boost Engagement
By constructing assessments based on individual profiling and massive data processing, AI will aid in gaining insights into the difficulties of customers along with their requirements. It will allow customers to regain control of their finances by opting for better decisions and exhibiting healthy financial behavior, by identifying their poor habits.
4. Enhanced Investment Evaluation
Interest income is merely one aspect of generating income for the banks.
Banks are constantly on the lookout for lucrative possibilities to invest in and profit from.
An AI-powered system is capable of providing smart investment recommendations that are appropriate for the risk appetite of these institutions. Furthermore, given the difficulty of accurately understanding industry information manually, AI can analyze client funding offers much better.
Human analysts are still in charge of making investment decisions. Investment analysis algorithms run by AI make the whole procedure easier and accommodate additional variables.
If a banking institution has interests beyond its national borders, accessing and assessing information can take time. However, the deployment of the right AI software can be instrumental in speeding up the process.
5. Alternative Processing
AI can usher banking in a new era of alternate interfaces for banking, like voice, gestures, VR and AR, and much more. This will allow financial solutions to be integrated into a variety of human experiences tied to the digital world.
Obstacles Preventing Banks From Deploying AI
Firstly, the incumbent banks must balance two sets of goals that appear to be at odds. While all banks wish to leverage speed, deftness, and deep analytical insights, they must also maintain a certain level of security standard, meet the regulatory obligations, and scale their operations.
The core technology of banks was designed for stability and has performed admirably over the years, especially in sustaining traditional payments and lending operations.
Before deploying AI technologies, banks must address multiple flaws in the legacy systems. To begin with, most of these systems lack the power and flexibility needed to handle the variable computation requirements, data-processing prerequisites, real-time analysis necessary for closed-loop AI applications, etc.
Core systems are more challenging to replace, and their upkeep is resource-intensive. Furthermore, the data repositories of many banks are dispersed across multiple silos (operated by different business & technology teams). Thus, AI analytics efforts become limited to certain use cases under such constraints.
Without a centralized data backbone in place, it becomes very hard to analyze relevant data and provide competent recommendations.
If data is treated as a bank’s fundamental resource, it should be governed and easily available (in a secured way) for data analysis. Data from both internal and external sources from millions of customers must be available at the “pinpoint of decision” across the organization.
Artificial Intelligence is no longer a cutting-edge technology with limited commercial use. Today, it is one of the most widely used technologies in practically every business, particularly in financial services and banking.
AI and its numerous applications can help banks build a more stable environment for their customers and prevent cyberattacks.
For most banks, enabling the widespread deployment of AI technologies is no longer optional, but rather a strategic compulsion.
Banks must undertake a holistic strategy to tackle the constraints that impede the organization-wide implementation of AI technologies.
Banks should invest in modernizing capabilities across all layers of the integrated capability pyramid to become AI-friendly: engagement, AI-powered decision-making, the core technology, and associated data layer, and lastly, the operating model.
To dive deeper into any query regarding AI implementation in banking, connect with our experts today!