Resilient and thriving ventures across the sectors have identified the technological capabilities and adopted them to create sustainable, profitable businesses. This enables successful businesses to drive customer-centric processes by creating hyper-personalized solutions for the end customers. The financial industry has witnessed a paradigm shift in a business model where customized solutions are provided throughout the customer lifecycle, thanks to digitalization. Today, financial institutions strive to offer tailor-made solutions right from customer acquisition to the collections stage using Artificial Intelligence (AI) and Machine Learning (ML). This process of using big data, analytics, and automation to help institutions sell the right product to the right customer at the right time essentially leads to hyper-personalization.
A recent study published by FICCI and PWC suggests that 83% of Indian financial organizations say AI helps enhance customer experience. Emerging technologies have replaced the brick-and-mortar way of doing business. This enables financial institutions, including NBFCs, to harness the data to create well-defined products, assimilate information, provide context-specific solutions, evaluate the customer profile and provide robust security to prevent a data breach. Financial brands have embraced an omnichannel strategy to gain visibility at a granular level to connect with all the primary, secondary and tertiary audiences. This allows the customers to choose whether they want to opt for traditional branch visits or access the online services from the comfort of their homes. Digital tools such as Data Analytics, Data Mining, Robotic Process Automation (RPA), Virtual Assistants and Natural Language Processing (NLP) are employed by new-age and customer-centric financial organizations to provide an enhanced user experience throughout the customer lifecycle.
Predictive analytics help deep dive into the data to analyze the customer’s buying pattern, social behavior, financial profile, and historical data to offer ultra-personalized solutions. For instance, specialized niche NBFCs that offer education financing solutions evaluate multiple parameters such as academic scores, entrance test scores, pedigree of university/course to determine students’ employability potential using technology, and traditional and new-age data. So, these new-age NBFCs prioritize the students’ profiles instead of relying on the financial background of the co-applicants. Since students are first-time borrowers, technology helps evaluate the risk and, thus, onboard the right credit.
Contactless, RBI-compliant, paperless digital solutions have changed the gamut of the onboarding process. The customers are not under any obligation to visit the branch. Instead, they can choose online platforms to complete various tasks such as video KYC from the comfort of their homes. The digital customer onboarding backed by RPA reduces the back-office operations by automating the document capturing and CRM processes. The painstakingly long and time-consuming tasks are now performed seamlessly at a lightning-fast pace.
According to a recent survey conducted across 5,000 customers in 500 financial institutions in 8 countries, respondents prefer hyper-personalized and individualized financial services. Financial players incorporate segment-definitive guidelines using digital technologies to provide the best suitable financial solutions. Data analytics dives deeper into petabytes of data, which aids in drawing accurate inferences from digital transactions and buying patterns of the customers to provide value propositions. For instance, a customer’s digital transaction history can shed light on key patterns or buying habits. Based on the evaluation, compelling financial solutions may be presented to them. This increases the chance of lead conversion and gives NBFCs an opportunity to widen their relationship with the customer by cross-selling and upselling.
Implementing robust and, in some instances, even draconian security is the need of the hour to combat data breaches, cybercrimes, data exfiltration, and phishing. Hence, tools such as voice recognition, facial recognition, biometrics, e-KYC, and deep learning-based models driven by AI and ML play a crucial role in preventing and detecting security breaches. The stringent KYC verification process helps reduce identity theft. The companies have invested in superior platforms to build strong firewalls to help retain the privacy of customers’ sensitive data such as bank or credit card details. The multi-level security ensures data privacy and prevents payment fraud.
AI and ML-based technologies have enabled a personalized payment experience by offering multiple payment gateways that users can choose based on their preferences. Customers no longer have to queue up at the branch office to process their repayment as digital payment options such as debit card/credit card and digital wallets are easily available. Moreover, the automated services even go a step further by sending reminders to ensure timely debt collection so customers can avoid late fee payments.
Lenders have ditched the traditional way of analyzing the risks and now prefer following AI and ML-powered scorecard-based credit decisions. The creditworthiness of the potential customers is now evaluated using technology by examining multiple parameters. The sophisticated ML algorithms and AI assist in predicting future outcomes and are the primary source of identifying the red flags on a case-to-case basis, thus mitigating the risks. Decision intelligence and scoring algorithms identify potential NPAs in advance, prompting businesses to make appropriate choices. At the same time, digital tools also identify the accounts that might turn overdue. This helps financial institutions to educate their customers and send timely reminders, making the overall lending system seamless and boosting the collections team’s productivity.
Nowadays, customers have multiple options to choose from, given the large pool of players in the financial sector. However, customer service is what differentiates most businesses as it is no longer about meeting customer expectations but about exceeding them. It is no secret that the financial sector will continue to flourish if it enhances the user experience by offering ultra-personalized solutions by embracing AI and ML technology. Lenders can improve the customer journey by providing an easy lending experience, excellent customer service, minimizing traditional bureaucracy, robust security and quick services by deploying AI and ML-based technology.
Source: cxotoday.com
Kollect Systems is an innovative tech platform provider with BankTech and FinTech software solutions which leverage AI based decisioning and workflow technologies to help lenders perform Debt Collections & Recovery (BankTech) processes effectively and for mid-size to large scale enterprise companies (FinTech), to automate Receivables, e-Invoicing & Payments better. Kollect Decube is an online platform to manage Data governance, compliance, lineage, data catalog and data observability for managing the Data Assets of an organization.