Part II: How Adoption Of AI Is Transforming Financial Sector In Modern Times?


Oct 2018 / jenny

Part II: How Adoption Of AI Is Transforming Financial Sector In Modern Times?

In the previous blog, we learned about the existing innovative AI-powered applications active across leading banking and finance institutes. Now let’s take a little deeper glimpse into all the major ways AI can impact these businesses.

Transformative capabilities of AI-powered banking and finance apps

Here is how companies strategically adopting AI-based solutions for enhanced banking and financial operations are achieving plethora of gains. A few significant areas where these intelligent applications empower the system are:.

Smart AI-enabled portfolio management

AI-based apps can effectively contribute to creating strong portfolio for banking individuals. At present, many finance management institutes are showing interest in investing in developing an AI algorithm that monitors user preferences and behavior, personal account details, credit history and spending, asset status and risks, earning potential, lifestyle choices and their matching goals. Based on current market scenario, AI app software thus suggests a robust portfolio for customers to focus on saving means and finance optimization. As more relevant factors are fed to AI app, more precise the AI responses become and more confident customer feels while determining about their next big move.

Self-learning cognitive system for fraud detection and prevention

It is a cursed state of finance and banking industry that the processes often suffer terrible violation of security architecture, data breaches and privacy issues. This is attributed to public cloud storage of massive business data, insidious cybercrime experts and malware threats. This requires operators to run a constant 24/7 vigil on data exchange between institutions and consumers with much obsession for ensuring zero data loss incidents. Unlike conventional data security rules that confuse genuine transactions as malicious, development of AI-enabled algorithm powered with natural language processing and cognitive deep learning capabilities have substantial potential to detect and minimize the incidents of fraud and data threats to a remarkable extent.

Operational automation: a unique value proposition

Lackluster radical methods and process that lack agility and productivity can be easily replaced with AI-powered applications in banking and finance sector. These apps built to automate mundane transactional and operational routines can significantly alter the status quo of the way finance is managed. By convincing AI algorithm about labor-like repetitive tasks and customer service manoeuvers, AI can in no time take over a gamut of communicative interactions with customers, delivering faster and more productive responses. The processes of customer education, schemes awareness, orientation, persuasive plans are all revamped and automated through AI-powered tools. This ultimately turns out to be a game changer for business entities that wish to experience unique value proposition from investing in high-caliber intelligent technologies.

JPMorgan Chase: COiN Legal intelligence platform

JPMorgan Chase is a brilliant modern-day epitome of a company who has zealously invested in developing an AI-powered platform they have rolled out recently. The technology is designed to function as a viable Contract Intelligence (COiN) solution that analyzes legal documents and relevant important clauses data, processing 12,000 annual commercial credit agreements that, if done using manual force, requires as much as 360,000 hours.

With the implementation of the machine learning technology COiN, JPMorgan Chase can easily review the contract documents in a matter of seconds. COiN is an unparalleled intelligent tool that has great potential to be expanded in future for taking over other additional processes. The company has so far invested more than $9.5 billion in 2016 with a few portion of the total reserved for future innovative initiatives and essential emerging Fintech solutions.

Accurate risk calculation and close analysis

While working on the client’s loan request, the traditional approach involves assessment of risks and credit eligibility of a prospect applicant based on historical data of transactions, credit and income growth. This orthodox practice as practiced by a large number of finance and credit management companies does not produce smooth results and rather imposes many critical challenges such as loss of resources and time, inconsistent performance and actions, inaccurate estimates which means vague prediction of future behavior.

The power of predictive analytics of AI-driven Machine learning algorithm is expected to practically assist wealth and loan analysts in saving manual exertion involved in microanalysis of real-time transactional data, recent financial activities, market conditions, existing asset value, which ultimately signals potential risks in offering credit. This leads to predictive ability to identify and prevent possible frauds.

More accurate and relevant marketing

As machine learning capability of Artificial Intelligence proves to be the best tool for deep-learning from past customer behavior and preferences, finance and banking industry can look to automating their marketing and advertising campaigns with AI and secure desired ROI. They can thus increase their chance to acquire more customers and produce repeat business. Through the data achieved from various digital footprints (interactions, ad campaign engagement and transactions), the AI-powered finance and banking tools enable marketers to create content-rich campaigns tailored for their target audience. Machine can learn from customer’s finance journey to provide the quality support and improve customer experience, which is not quite feasible with straightforward and pre-programmed CRM and ticket management software.

Your takeaway

Companies require a lot more insight and expertise and product knowledge before they implement varied AI-powered solutions such as chatbot, automation of processes, custom recommendations engine, cognitive machine learning algorithm and more. At present, only 10% organizations are relying on AI applications for finance and banking operations and soon the number of companies acknowledging the urgent need for AI adoption will increase.

With Tech giants like Google, Microsoft and Apple are already striving hard to make their AI assistant bots more productive, the demand for dedicated chatbots for customer-friendly financial assistance is going to soar high. If you are one of the entrepreneurs seeking to integrate boundless potential of AI-powered applications for delivering personalized experience, you can explore your chances with talented AI platform developers. Talk to us to get industry-scale expertise and consultation for software solutions powered by artificial intelligence.


Leave A Reply

Your email address will not be published. Required fields are marked *

Get a Free Consultation Today!