Category : Banking, Financial Services & Insurance

Discover the transformative impact of GenAI in payments

Oct 22,2024 / By Basant Baruah / No Comments

Generative AI (GenAI) has become a prominent technology in 2024, sparking significant interest among financial institutions worldwide. Beyond its content generation capabilities, GenAI is finding applications in various domains. This article explores the role of GenAI in the digital payments industry.

GenAI is a branch of artificial intelligence that creates new content, such as text, images, audio, or video, that resembles human-generated data. Unlike traditional AI systems, which often follow predefined rules, GenAI models leverage machine learning to generate new content based on patterns learned from extensive datasets. Key features of GenAI include the ability to produce texts, images, audio, and video; a contextual grasp of the input data or environment; and improved performance due to the processing and comprehension of large volumes of high-quality data.

Applications of GenAI in payments

GenAI has the potential to revolutionize payments by enhancing personalization, security, and efficiency, benefiting both businesses and consumers.

From marketing and sales to customer onboarding, KYC, customer service, and risk management, GenAI can offer comprehensive solutions across the entire payment lifecycle.

Here are some key applications of GenAI in payments:

1. Marketing and Sales:

● Personalization: GenAI models can analyze transaction histories and customer preferences to recommend personalized products, services, or payment options. This enhances customer experience and loyalty by providing tailored suggestions and simplifying transactions.

● Content Creation: GenAI can improve marketing and sales effectiveness by generating targeted content for outbound customer communications. Images and content can be customized for specific customer segments. For example, younger demographics can be reached with relatable and eye-catching content promoting specific offerings.

● Dynamic Product Pricing: GenAI models can analyze market dynamics, customer behavior, and inventory data to create dynamic pricing strategies for products and services. This allows banks and fintechs to optimize real-time pricing based on demand, supply, and other factors. Dynamic pricing models can be applied to products like loans, insurance premiums, and investment portfolios, adjusting pricing based on risk assessments, market conditions, and customer preferences.

2. Customer Onboarding:

● Intelligent Verification: GenAI can streamline customer onboarding by automating identity verification and ensuring regulatory compliance, enhancing efficiency and accuracy.

● Document Processing: GenAI can facilitate onboarding through intelligent document processing and real-time KYC/AML checks.

● Personalized Journeys: GenAI enables systems to adapt to consumer preferences and recommend personalized customer journeys, improving the overall experience.

Example: A major American payment card service has implemented a GenAI system that analyzes regulatory documents and provides recommendations for AML and KYC compliance across various regions.

3. Payments Processing:

● Conversational Payments: GenAI-powered chatbots and virtual assistants facilitate conversational payments, allowing users to make transactions, check balances, and receive support through natural language interactions. This enhances customer experience and attracts new customers.

● Fraud Detection and Risk Management: GenAI can develop dynamic risk-scoring models that assess real-time payment transaction risks. These models assign risk scores based on factors like transaction amount, frequency, location, and user behavior, enabling targeted risk management strategies. GenAI models learn typical payment patterns and create synthetic fraud examples to aid anomaly detection systems. They also analyze transactional data and market trends to proactively identify risks, bolster risk management, and prevent financial fraud.

Example: A Nordic-Baltic banking group has used the generative adversarial network (GAN) model to detect fraudulent transactions, reducing false positives.

4. Operations and Delivery:

● Process Automation: GenAI can automate complex middle-office tasks, such as commercial contracts, proposal requests, and account plans, reducing manual effort and streamlining delivery.

● Code Development Acceleration: GenAI can help companies with legacy systems by automating tasks like bug detection, code repair, and user acceptance testing. It can also analyze existing codebases to suggest alternative solutions or approaches.

● Product and Service Innovation: GenAI can accelerate delivery timelines by allowing teams to focus on critical activities. Its computational and documentation capabilities can also assist in developing new product and service designs.

Example: One of the largest private banks in India is rolling out its LLM-powered website in 2024. The bank also plans a private LLM to write credit assessments and business requirement documents.

5. Payments Reconciliation:

● Automated Data Parsing: GenAI is a powerful tool for automatically parsing structured and unstructured data, improving accuracy and minimizing errors. Regardless of format, it can extract relevant information from invoices, receipts, and bank statements.

● Payment Pattern Analysis: GenAI can provide valuable insights into payment patterns, helping businesses optimize reconciliation processes.

● Enhanced Exception Handling: GenAI can analyze exceptions to identify root causes and recommend automatic suggestions for alternative approaches when exceptions recur. While this use case is still evolving, it has the potential for widespread application.

6. Customer services and support:
● Smart agent assistant: GenAI can provide real-time suggestions and knowledge repository access to customer service agents, thereby improving human agents. It can also draft personalized communications messages to customers.

● Improved self-service options: GenAI can create clear and concise information and personalize FAQs based on user behavior and past interactions. It can also develop interactive tutorials and guides that help customers resolve queries independently.

● Chatbots and proactive customer reach-outs: GenAI can power chatbots and virtual assistants that assist users with payment-related inquiries, provide customer support, and facilitate transactions through NLP. GenAI and AI chatbots serve different purposes despite using the same technology. The content creation capabilities of GenAI can be used to personalize information and content for service agents. On the other hand, AI chatbots are designed to simulate conversations directly with the users through text or voice messages.

Example: A leading commercial bank in the UK has recently announced that it will use GenAI to improve its existing virtual assistant. This is expected to give customers access to a broader range of information through conversational interactions.

Handling risks associated with GenAI in payments

While GenAI offers significant benefits in fraud detection, personalized user experiences, and operational efficiency, investment in GenAI needs serious consideration as it also presents inherent risks related to data privacy, bias, transparency, and security.

Key Risks:

● Risks Associated with GenAI-Powered Recommendations: While personalized recommendations aim to enhance user experience, they can lead to privacy concerns, algorithmic biases, and transparency issues. Recommendations in sensitive areas like sanctions screening, fraud detection, or exception handling may require human intervention.

● Risks Associated with Real-Time Monitoring: While real-time monitoring benefits cybersecurity and fraud detection, it can raise privacy concerns due to processing sensitive customer information. Balancing real-time responsiveness with minimizing false positives is a significant challenge, as excessive monitoring may delay payment transactions and affect service level agreements (SLAs).

● Risks of Bias Perpetuation: GenAI relies on historical data, which can introduce biases if the training data is biased. This can lead to unfair treatment of specific user groups. GenAI technologies should be implemented cautiously to avoid perpetuating biases.

Drivers for adoption of GenAI in payments

While implementing GenAI can be capital-intensive and disruptive, its potential to enhance efficiency, security, customer centricity, and innovation drives its adoption in payments.

The payments domain is well-positioned to adopt GenAI-integrated systems as it embraces new technologies and infrastructure. The increasing demand for convenience in payments, driven by the digital age, is a significant factor. GenAI’s capabilities align with this demand, making it a logical choice for the payment industry.

Data and quality are essential drivers for the payments industry’s growth. The sector generates vast transactional, customer behavior, and financial data. The introduction of ISO20022 will increase structured data availability, facilitating GenAI integration.

Security is paramount in payments, especially with the rise of new channels. GenAI’s ability to generate synthetic data, manage risks, and detect fraud helps organizations achieve their security goals.

While GenAI can increase productivity and streamline operations, organizations must address the potential for job displacement due to automation. Transparent communication and employee training are crucial to mitigate these risks and ensure a smooth transition.

The successful adoption of GenAI in payments requires a comprehensive approach that addresses these challenges and leverages the transformative potential of AI technology.

Increasing efficiency, enhancing security, and delighting your customers with GenAI requires building in-house capabilities or collaborating with external tech partners to develop advanced fintech products and tailored digital experiences.

How predictive analytics is driving personalized banking experiences

Jul 23,2024 / By Vivek Patil / No Comments

Today, consumers have greater control over their financial journeys. Therefore, banks must adapt to customers’ evolving needs by providing seamless, end-to-end experiences.

Data plays a critical role in this transformation. Robust data foundations enable banks to efficiently assess transaction details, stakeholder information, payment processing, compliance, and documentation. Given the increasing use of smartphones and the constantly evolving fintech landscape, it is important to focus on addressing three key areas:

Cost reduction
Improved decision-making
Enhanced customer experiences

Now, let’s dive into how predictive analytics can assist in achieving these objectives.

Understanding the role of predictive analytics in modern banking

Prebuilt predictive analytics platforms aim to enhance personalization. But these platforms continuously fall short due to constantly changing customer behavior.

Banks need real-time analytics capabilities which helps them understand spending patterns linked to major life or financial events, enabling banks to predict and implement the next best actions (more on this in the next section).

Creating real-time predictive models allows banks to tailor hyper-personalized offers, recognizing the unique motivations behind each customer’s activities and events. This approach ensures more accurate and relevant customer engagement, ultimately driving better results for the customer and financial institution.

Types of predictive modeling

Predictive modeling automates targeting, minimizing manual data analysis and dependence on human intuition. Here are a few common types of predictive models:

Benefits of predictive analytics

Predictive analytics in BFSI offers significant benefits for leadership aiming to boost profitability and efficiency:

It reduces costs by preventing fraud, lowering loan defaults, and retaining customers who might otherwise churn.

Real-time data updates enable better decision-making, accurately representing risks and boosting confidence.

Hyper-personalization allows targeted customer segmentation and personalized communication, enhancing overall customer experience and satisfaction.

Banks understand the necessity of establishing a top-notch customer experience. However, many still have crucial operational data confined within legacy IT systems.

How are banks adopting experience driven banking?

Banks and NBFCs are embracing experience-led banking by analyzing customer data from digital banking activities, customer interactions, and transaction records. They use transactional, behavioral, and demographic details. Integrating data from both digital and physical channels is crucial for creating a comprehensive customer profile (360-degree view) and omnichannel experience.

Hyper-personalization is driving a 75% increase in customer engagement in one of our BFSI projects at Robosoft, as shown in the image below.

Next best action model

The next best action model (next best offer) uses AI to suggest the most appropriate decision or action for each customer interaction. We have published a detailed blog on building best-in-class recommendation systems – save it for later reading.

In contrast to the past, today’s customer journeys are non-linear and highly dynamic due to frequently changing personal financial situations. Banks can significantly improve results by proactively addressing customer needs with suitable alternatives.

Outcome-driven personalization in BFSI

BFSI brands can use predictive analytics to improve website personalization, thereby increasing onboarding completion rates and decreasing drop-offs. Brands can nurture long-term relationships by providing guidance and support during the setup process.

Tailored messages, such as reminders for bill payments, updates on loan qualification, credit card offers, or information about nearby branch locations based on past transactions and browsing history, have the potential to re-engage inactive customers and enhance overall engagement and conversions. Same goes for mobile app personalization.

Use cases of predictive analytics in banking

Collateral management: Predictive analytics helps banks forecast payment flows and anticipate end-of-day and intra-day positions, identifying potential collateral shortfalls. For example, HSBC uses predictive models to improve collateral management, ensuring accurate and timely forecasts to mitigate risks. It leverages NLP and machine learning within its PayMe app to understand transaction intent quickly. Their platform also offers personalized recommendations to customers to reduce irregular activities.
Cash management: Predictive analytics enables banks to forecast cash and manage working capital efficiently. For instance, Bank of America compares a company’s working capital and payment efficiency with industry benchmarks. Predictive analytics provides them with deposit balance notifications, dynamic data visualizations, and metrics for assessing payment efficiency, optimizing supplier payments, managing strategic cross-border payment flows, and protecting against account fraud.
Risk management: Predictive analytics helps take proactive anti-fraud actions, enhance internal audits, and refine credit and liquidity risk evaluations. For example, Wells Fargo bank uses analytics to notify customers about unusually high recurring payments and suggests transferring excess funds by checking savings accounts.
Marketing and sales optimization: Predictive analytics helps banks optimize their marketing and sales strategies by identifying the most effective channels, messages, and offers for various customer segments. For example, HDFC and many other banking players use predictive analytics to segment customers and tailor marketing campaigns, leading to higher engagement and value-building for top customers.

Conclusion

The growing demand for super apps, embedded finance, and personalized services has prompted banks to upgrade their digital banking platforms.

To leverage predictive analytics effectively, banks must update their application environment. Key steps include aligning IT and business initiatives, unlocking core systems, securely integrating data, and optimizing APIs through automation. By following this approach, banks can tap into previously unused capabilities to deliver seamless digital experiences much faster.

Many financial institutions have established AI and machine learning innovation centers to enhance data utilization through predictive analytics. This shift requires building in-house capabilities or collaborating with external tech partner to develop advanced fintech products and tailored digital experiences.

Banking, Financial Services & Insurance Fintech

Tackling banking API security challenges to create secure financial landscape

Jul 3,2024 / By Sandeep Verma / No Comments

How to tackle banking API security challenges

The future of banking lies in seamless connectivity. Like veins circulating blood, banking APIs are now the lifeblood of the financial services industry, allowing diverse financial applications and services to “talk” and transact in real time. Behind the scenes, the Application Programming Interfaces (APIs) drive various convenient functionalities such as account management, payment processing, transaction history retrieval, and third-party financial tools. Today, banks collaborate with Fintech and third-party partners using bank APIs, offering personalized financial solutions and adapting to evolving customer needs.

Banks embracing digital transformation rely heavily on APIs to provide innovative financial services. However, with the increased use of APIs come risks and cybersecurity challenges for banking and financial institutions. As more data is shared through banking APIs, potential data threats and cyber-attacks exponentially increase. So, how can you balance innovation in financial services with banking API security? In this article, we have provided insights into 7 key challenges banking institutions face in protecting their APIs and key API security best practices to bolster security posture.

Key challenges in banking API security

As the financial industry continues to shift towards open banking and API-based solutions, some obstacles to the security of these solutions arise. Here are 7 key challenges in banking API security that banking institutions must address for building secure and customer-centric digital solutions:

Data Breaches and Unauthorized Access

Banking APIs, often interconnected with various applications and services, create an expanded cyber-attack surface. The vast amount of sensitive customer information transmitted via bank APIs can have open-ended vulnerabilities such as unauthorized access and data breaches. Attackers can exploit even minute vulnerabilities to access sensitive customer information, such as their personal data, credit card details, and account numbers.

API Endpoint Security

The security of API endpoints is critical to protecting the overall infrastructure. Malicious actors often target vulnerabilities in API endpoints to launch attacks, such as code injection attack attempts.

Code Injections

On the authentication and validation front, bank APIs must have strong security standards in place to avoid any gaps. Banking institutions cannot afford even the slightest gaps in authentication protocols because such gaps can be vulnerable to code injections by attackers. Using such gaps, attackers may send a script to a banking application’s server via an API request. This may lead to Account Takeover (ATO) incidents and put the application’s internals at risk—it may delete data and plant false information in the application environment.

Encryption and Data Integrity

The confidentiality and integrity of data transmitted through banking APIs are always at risk of attacks if the encryption protocols are insufficient to safeguard data in transit and at rest.

Communication Channels

API transactions are facilitated by multiple communication channels between systems and parties that ensure faster transactions. However, these channels can be vulnerable to security threats like data manipulation, eavesdropping, and man-in-the-middle (MITM) attacks.

Regulatory Compliance

The banking and financial services industry is subject to data regulations like GDPR and PSD2 and security standards such as ISO 27001 to protect customer data and ensure a secure financial landscape. Non-compliance with these standards can result in a more expanded cyber-attack surface on top of severe legal consequences and damage to the reputation of financial institutions.

Brand Reputation

Security breaches that expose sensitive customer data can systematically erode the hard-earned trust between banks and their clientele. The resulting damage to the institution’s reputation and perceived reliability presents financial and existential risks associated with losing competitive positioning grounded in customer loyalty. Therefore, prioritizing robust banking API security via routine vulnerability assessments and continuous authentication enhancements is an investment in maintaining customer confidence and institutional reputation.

10 strategies for tackling banking API security challenges

Banks must implement a comprehensive cybersecurity strategy covering all security aspects to tackle banking API challenges. Here are key banking API security best practices that banks can adopt to enhance their security measures:

Secure API Design

Banks can perform exhaustive threat modeling, risk assessments, and attack surface analysis during API design phases. Identify attack vectors like code injection attacks, MITM attacks, bot abuse, etc. They can architect appropriate countermeasures directly into the API framework with principles of least privilege.

Rate Limiting and Throttling

Banks can implement rate limiting and throttling mechanisms to prevent abuse and protect against distributed denial-of-service (DDoS) attacks. Set appropriate limits on the number of API requests per client or user within a given timeframe.

Input Validation and Sanitization

Banking institutions can adopt a Zero-trust model with input validation and sanitization. They can validate and sanitize all inputs to prevent common security vulnerabilities such as injection attacks (e.g., SQL injection, XSS). Use parameterized queries for database interactions and implement input validation for API payloads.

Logging & Monitoring:

Log all API activities, including requests, responses, and errors, for auditing and forensic purposes. Implement real-time monitoring and alerting to promptly detect and respond to suspicious activities or security incidents.

Secure Coding Practices

Financial institutions can adopt DevSecOps methods with extensive security testing integrated at each API development stage. They can enforce robust coding standards, including proper input validation, data sanitization, and parameterized queries. This protects against common web application security threats like cross-site scripting (XSS) and cross-site request forgery (CSRF).

API Keys and Tokens

Issue unique API keys or tokens to each authorized client to authenticate their requests. Use short-lived tokens and implement token expiration and refresh mechanisms to mitigate the risk of token misuse.

Data Encryption

Employ strong encryption algorithms to encrypt sensitive data end-to-end using standards like AES-256. Banks can implement hashing algorithms like SHA-2 on sensitive data in transit and at rest and apply digital signatures to ensure data integrity. These practices can anonymize or mask any Personally Identifiable Information (PII) data that flows as needed per data privacy regulations.

Web Application Firewalls (WAFs)

Banks can deploy advanced web application firewalls (WAFs) to analyze and filter real-time API traffic. Fine-tuned WAF policies using signatures, anomaly detection, and behavioral analysis can detect and block common attacks like code injection attempts, bot abuse, and DDoS floods.

Regular Security Assessments

Frequent security assessments are crucial to identify vulnerabilities before exploitation by cyber-attackers. Banks must conduct recurring penetration tests, static or dynamic scans, and code audits performed by internal and third-party security teams. This allows the discovery and remediation of flaws like code injection risks, weak authentication, and misconfigurations.

Regulatory Compliance

Banks must maintain compliance with data regulations like GDPR and security standards such as the National Institute of Standards and Technology Cybersecurity Framework (NIST CSF) and ISO 27001 to keep bank APIs resilient to emerging threats.

The banking API security imperative

Maintaining robust banking API security measures is paramount as the banking industry continues to embrace API-driven platforms. Financial institutions can accelerate their digital transformation by utilizing banking APIs while also being vigilant to ensure a robust security posture. By taking the necessary secure API development measures, banks can reinforce customer trust, system resilience, and reputation as stewards of sensitive financial data.

Ultimately, API connectivity promises greater convenience, personalized services, and streamlined banking. However, banking institutions can only achieve this on a foundation of security and compliance first by following banking API security best practices. At Robosoft, we partner with leading banking and financial services organizations across the globe, enabling them to streamline operations and provide millions of customers with secure and seamless digital experiences.

Banking, Financial Services & Insurance Finance Fintech

Legacy Modernization: Assessment Methodology, Analysis & Roadmap and Benefits

Jan 17,2024 / By Mahesh Kumar / No Comments

Legacy modernization is the process of transforming outdated business technology systems, known as legacy systems, into modern infrastructure and functionalities. It is the process of updating or replacing outdated software using modern programming languages, software libraries, or protocols and giving a makeover for the digital age. This article outlines the blueprint for modernizing legacy systems and lists key benefits that accrue from this initiative.

Assessment Methodology for Legacy Modernization

The legacy modernization exercise commences with an assessment of the existing application landscape to determine the ability of the existing technology systems (application and infrastructure) to support evolving business needs. A detailed roadmap is drawn up subsequently to complete the exercise. The assessment involves gathering data points around different aspects of the technology landscape. This is supplemented with structured interviews with key stakeholders representing business and technology to understand current pain points and future requirements.

Quantitative Data Points

Quantitative data delves into various platform dimensions, including application stability, business criticality, technology stack, process discipline, infrastructure, and non-functional requirements. Specific data points might include outage frequency, unresolved ticket counts, planned enhancements, technology stack details, interface protocols, data volumes, compatibility of software development tools, adherence to best practices, hosting configurations, disaster recovery plans, and performance scalability metrics.

Qualitative Data Collection

Qualitative data gleaned through stakeholder interviews sheds light on future business goals, technology preferences, regulatory constraints, and pain points. This input enriches the quantitative analysis, painting a holistic picture of the current and future aspirations.

Analysis and Roadmap

Armed with this comprehensive data, we embark on the analysis phase. This involves meticulously examining software code, database structures, and the interplay between quantitative and qualitative inputs. The culmination of this analysis is a robust blueprint for the legacy transformation exercise.

The blueprint addresses critical challenges and proposes targeted solutions, each delivering distinct benefits. For instance, monolithic architectures plagued by high ownership costs can be transformed into loosely coupled microservices, enabling simpler deployments and improved scalability. Performance bottlenecks can be tackled by introducing auto-scaled middleware and databases, paving the way for future business growth. Similarly, implementing caching layers and monitoring tools can enhance performance and operational efficiency.

Benefits of Legacy Modernization

Some of the key benefits are listed below:

Improved functionality and security: Modern technologies offer better performance, scalability, and security features compared to older systems.
Reduced costs: Maintaining outdated systems can be expensive, while modernizing can lead to cost savings on maintenance, licensing, and energy consumption.
Enhanced agility and flexibility: Modern systems are easier to adapt to changing business needs and integrate with new technologies.
Better user experience: Modern interfaces are more user-friendly and accessible, leading to improved employee and customer satisfaction.

Conclusion

Legacy modernization holds lessons for the entire financial services industry. It demonstrates the power of technology to unlock economic potential, empower migrant workers, and strengthen local communities. By embracing innovation and adaptability, financial institutions can thrive in the competitive landscape and contribute to a more inclusive and equitable global economy. By partnering with a reliable and proven digital transformation partner, legacy modernization in one market can inspire and pave the way for similar advancements across the globe, ultimately benefiting communities and individuals.

Banking, Financial Services & Insurance

Digital Banking Benchmark Analysis for Technology Advancements

Nov 9,2023 / By Mahesh Kumar / No Comments

As digital banking is evolving at a rapid pace, it continues to be a necessity in the modern financial industry. Almost 78% of Americans opt for banking through mobile apps or websites rather than traditional banking—in-person visits to a bank branch. Customers expect seamless, secure, and user-friendly experiences across various digital platforms they use on a day-to-day basis. Technological integration has led to innovative solutions such as Internet banking, mobile wallets, and mobile digital banking. However, with this evolution comes the need for continuous improvement and optimization. The rapid adoption of digital banking solutions has led financial institutions to constantly seek ways to optimize their technology infrastructure and stay ahead in the competitive landscape.

This is where the technology benchmarking of digital banking platforms comes into play, offering financial institutions a way to measure their performance of the digital banking platforms against industry best practices and identify growth opportunities. Comparing the digital banking platform performance, processes, and outcomes against industry best practices – technology benchmarking – is essential. For digital banking platforms, this means assessing aspects such as current IT applications and services—internet and mobile banking applications, mobile wallet services innovation, remittance system efficiency, security protocols, and overall customer experiences.

Leveraging Technology Benchmarking for Future-proof Digital Banking Solutions

The banking industry is witnessing an influx of disruptive technologies reshaping customer expectations and experiences. From seamless mobile wallet integrations to swift and secure remittance services, customers now demand convenient, user-friendly, and technologically advanced solutions. Banks or financial institutions must leverage digital banking benchmark analysis for technology enhancements to continuously align their offerings with industry-standard practices by addressing shortcomings and adapting their digital banking platforms to deliver superior customer experiences.

Adapting to the evolving landscape also involves understanding the changing regulatory environment by being vigilant of the latest industry standards. Compliance and security are paramount in the digital banking landscape, and digital banking benchmark analysis for technology on a level with industry standards helps banks and financial institutions ensure that their platforms meet stringent requirements and prevent or mitigate risks effectively.

The methodology of the technology benchmarking of digital banking platforms entails analysis of the existing technology landscape with a focus on the following:

Existing Technology Stack for Scalability and Performance: A comprehensive digital banking benchmark analysis for technology stack can gauge its capacity for scalability and performance in future business needs. The goal is to ensure the platforms can seamlessly handle increasing loads and efficiently cater to growing user bases.
Service-oriented Architecture: The structural backbone of the architecture of digital banking platforms is scrutinized for its alignment with service-oriented principles. The digital banking benchmark analysis for technology assists in the identification of opportunities for enhancing flexibility and streamlining processes.
Database Design and Scalability: The digital banking benchmark analysis for technology also involves evaluating the efficacy of the database design with an eye on scalability. By optimizing database structures, digital banking platforms can ensure seamless data management as their operations grow in size.
Security and Compliance: A paramount consideration in the digital banking benchmark analysis for technology is security and compliance, which entails a rigorous assessment methodology. This dimension involves evaluating the technological measures in place to safeguard sensitive customer data and ensure compliance with the applicable regulations and industry standards. Some key aspects to be considered include encryption protocols, authentication methods, fraud detection, and the platform’s adherence to compliance requirements such as GDPR, PCI DSS, and other regulations.
Competitor Analysis: A thorough understanding of the competitive landscape is crucial to benchmark digital banking platforms effectively. This involves analyzing key competitors’ market presence, feature gap analysis, technological offerings, and performance. By comparing and contrasting these factors, we can get valuable insights that help fine-tune strategies and differentiate the platform in a crowded market.
Innovation and Future-readiness: This aspect requires evaluating the digital banking platforms’ capacity for innovation and future readiness. Benchmarking evaluation for this dimension involves advancements in user experience, integration of emerging technologies (e.g., AI, blockchain), agility in adopting advancements, and the ability to meet evolving customer needs and expectations.
Customer Support and Engagement: A well-functioning digital banking platform enables seamless transactions and prioritizes customer support and engagement. The digital banking benchmark analysis assess the efficiency and responsiveness of customer support systems, including the availability of multiple support channels, response times, issue resolution rates, and personalization. On the personalization front, specific features like spend analysis (which helps customers track and manage their expenses) and associated service recommendations (offering tailored suggestions based on a user’s financial behavior) enhance customer engagement.

Robosoft’s Approach to Digital Banking Benchmark Analysis for Technology

At the core of our approach to the technology benchmarking of digital banking platforms lies the meticulous definition of scope, gathering insights, and providing actionable recommendations. We collaborate closely with our clients to understand their goals and ensure the digital banking benchmark process aligns with their strategic vision. We delve deep into understanding the unique identity of digital banking platform, their customer base, and their expectations.

Our process for evaluating technology benchmarks entails gathering quantitative data via questionnaires and qualitative inputs from key technology stakeholders via stakeholder interviews. By utilizing this approach, we gather essential insights that serve as the bedrock of our digital banking benchmark analysis. We comprehensively analyze the technological facets and operational complexities to view the existing ecosystem against the industry’s best practices. This perspective allows us to provide valuable observations and benchmarking recommendations that empower our clients to make well-informed decisions.

For one of our clients with the requirement of technology benchmarking for digital banking platforms, our methodology involved these facets:

Assessing Technology Stack for Scalability and Performance
Architecture and Infrastructure Scalability Assessment
Database Design Assessment
Benchmarking Analysis for Security

Assessing Technology Stack for Scalability and Performance

We assessed the technology readiness of the existing IT applications to support the financial services businesses’ long-run scalability and ensure alignment of IT to business strategies. This involved benchmarking the current products or services (online banking, mobile digital banking, and mobile wallets) and the technology landscape against competitors in targeted geographies. Also, the assessment included determining the future roadmap in terms of the technology stack for the remittance application.

Remittance Application: Observations & Recommendations

Digital Banking Suite (Mobile Wallet, Online and Mobile Digital Banking): Observations & Recommendations

Benchmarking Analysis for Architecture and Infrastructure Scalability

At this stage, our digital banking benchmark analysis process involved a holistic assessment of the current architecture and infrastructure for remittance application, mobile digital wallets, and digital banking. Through this evaluation, we focused on understanding the performance benchmarks exhibited by these systems and applications, enabling us to identify potential areas for enhancement and optimization.

Remittance Application: Observations & Recommendations

Digital Banking Suite (Mobile Wallet, Online and Mobile Digital Banking): Observations & Recommendations

Database Design Assessment

We conducted digital banking benchmark analysis to measure the database design within the technological framework for digital banking platforms. Our assessment involved the industry’s best practices by comprehensively exploring various facets that collectively define the structure and efficiency of the existing database design.

We assessed the key aspects such as indexing strategies, query optimization, archive database, partitioning of tables, and database design revamp suitable for microservices. We could gauge the database’s responsiveness, reliability, and overall performance by focusing on these components.

Remittance Application, Mobile Wallet, Online and Mobile Digital Banking: Observations & Recommendations

Benchmarking Assessment for Security

At this stage, our digital banking benchmark assessment for security aspects involved the evaluation of the vulnerabilities or risks of the applications with severity classification for each vulnerability. We conducted the digital banking benchmark analysis to examine the security aspects and pinpoint potential vulnerabilities that could be exploited in the form of attacks, breaches, or unauthorized access attempts.

In this process, we ensured the safety and security of the systems and applications. We utilized industry best practices to assess and fortify our systems against potential threats, upholding high security and safeguarding sensitive data, financial transactions, and user information.

Remittance Application, Mobile Wallet, Online and Mobile Digital Banking: Observations & Recommendations

Wrapping Up

The digital banking industry is constantly changing and characterized by disruption. To keep up, financial institutions need to implement the best practices for the technology benchmarking of digital banking platforms. This allows them to transcend conventional boundaries, innovate, and achieve excellence in digital banking.

Financial institutions can use digital banking benchmark analysis for technology enhancements of their digital banking platforms to create solutions that meet current customer expectations while also being resilient and adaptable to future disruptions. This approach ensures that the platforms are future-proof and can continue to provide quality service to their customers.

Banking, Financial Services & Insurance

Green Deposits: Propelling Responsible Investing in India

Aug 11,2023 / By Basant Baruah / No Comments

Environmental, social, and governance (ESG) impact is a theme that has already gained momentum across the globe. The term “ESG” is believed to have been first coined in 2005 in a study titled “Who Cares Wins.” However, eighteen years have passed since then, and ESG has now become a vital corporate discipline and a significant agenda across various global discussions, encompassing politics, business, and climate change.

Responsible investing, in simple terms, entails integrating environmental, social, and governance factors into investment processes and decision-making. Green Deposits are a way to mobilize money from public and institutions to specifically invest that money towards sustainability project.

According to a report published by Forbes, “ESG factors cover a wide spectrum of issues that traditionally are not part of financial analysis, yet they may have financial relevance. This could include evaluating how corporations respond to climate change, their proficiency in water management, the effectiveness of their health and safety policies in preventing accidents, supply chain management practices, the treatment of workers, and the existence of a corporate culture that fosters trust and innovation.”

RBI’s Initiatives for Green Finance and Banks’ Role in Sustainability Efforts

As ESG permeates all aspects of business, banks are emerging as driving forces in sustainability efforts. The financial services sector plays a pivotal role in mobilizing national resources and managing their allocation. The banking industry in India, including non-banking financial services companies, has positively impacted the country’s socio-economic progress. However, for India to achieve its net-zero target by 2070, the banking industry needs to take on a more central role in leading the ecosystem towards sustainability.

Recognizing the industry’s significance, the Reserve Bank of India (RBI) has established regulatory guardrails and frameworks to promote the raising and deployment of green finance in the domestic market. This move allows banks and other deposit-accepting NBFCs to enhance their fundraising abilities and build a corpus of green funds dedicated to environment-friendly and sustainability-linked products. Consequently, businesses can gain easier access to green loans, ideally at better rates and with more favorable conditions, to finance their journey towards sustainable growth.

Effective June 1, 2023, retail and institutional investors have access to green deposits. As per the RBI, a “green deposit” refers to an interest-bearing deposit received by a Regulated Entity (RE) for a fixed period, with the proceeds earmarked for allocation towards green finance. The RBI mandates regulated entities to establish a comprehensive board-approved policy on green deposits, outlining in detail all aspects related to issuing and allocating such deposits.

Utilization of Green Deposits Funds: Supported Sectors and Projects

In its circular dated April 11, 2023, the RBI stipulates how regulated entities should use the proceeds from green deposits or green finance. The current provisions within the framework allow the utilization of green deposits funds in the following sectors:

1. Renewable Energy:

Solar, wind, biomass, and hydropower energy projects that integrate energy generation and storage.
Incentivizing the adoption of renewable energy.

2. Energy Efficiency:

Design and construction of energy-efficient and energy-saving systems and installations in buildings and properties.
Supporting lighting improvements.
Supporting the construction of new low-carbon buildings and energy-efficient retrofits for existing buildings.
Projects to reduce electricity grid losses.

3. Clean Transportation:

Green Projects promoting the electrification of transportation.
Adoption of clean fuels, such as electric vehicles, including the building of charging infrastructure.

4. Climate Change Adaptation:

Projects aimed at making infrastructure more resilient to the impacts of climate change.

5. Sustainable Water and Waste Management:

Promoting water-efficient irrigation systems.
Installation and upgrading of wastewater infrastructure, including transport, treatment, and disposal systems.
Flood defense systems.

6. Pollution Prevention and Control:

Green projects targeting the reduction of air emissions, greenhouse gas control, soil remediation, waste management, waste prevention, waste recycling, and energy/emission-efficient waste-to-energy.

7. Green Buildings:

Projects related to buildings that meet regional, national, or internationally recognized standards or certifications for environmental performance.

8. Sustainable Management of Living Natural Resources and Land Use:

Environmentally sustainable management of agriculture, animal husbandry, fisheries, and aquaculture.
Sustainable forestry management, including afforestation/reforestation.
Support for certified organic farming.
Research on living resources and biodiversity protection.

9. Terrestrial and Aquatic Biodiversity Conservation:

Projects related to coastal and marine environments.
Projects related to biodiversity preservation, including the conservation of endangered species, habitats, and ecosystems.

The Green Finance Ecosystem (GFS)

With a view to drive a green finance ecosystem (GFS), the RBI framework aims to supports and enable investments in environmentally sustainable projects and initiatives. The GFS aims to create a financial system that supports the transition to a low-carbon, resource-efficient, and sustainable economy, while also addressing the risks and opportunities associated with environmental issues such as climate change, pollution, and biodiversity loss. As per RBI’s circular, the purpose or rationale behind the green deposits framework is, “To encourage regulated entities (REs) to offer green deposits to customers, protect interest of the depositor, aid customers to achieve their sustainability agenda, address greenwashing concerns and help augment the flow of credit to green activities or projects.”

This new framework may seem extremely opportune given India’s strong narrative around the ‘Make in India’ campaign and its commitment to be net zero by 2070. This move lends tremendous credibility to India’s aspiration to be seen as a responsible, sustainable and a global economic power. It reflects India’s commitment, at a policy level, to address the growing global issues concerning ESG impact. Commitment with a follow up action like this will go a long way in positioning India is a global partner of choice across manufacturing, research, and bilateral trade. Considering the possibilities that it opens; the RBI’s green deposits framework has clearly given India another ‘India Shining’ moment after the Unified Payments Interface (UPI) and Central Bank Digital Currency (CBDC) initiatives.

Banking, Financial Services & Insurance Digital Transformation Fintech Insurance

Digital Rising: Opportunities for the Wealth Management Sector

Jan 31,2023 / By Basant Baruah / No Comments

Wealth management was once the exclusive purview of financial advisors who managed the portfolios of a select, affluent few. Personalized portfolio plans and personal relationships drove such advice. The advent of digital technology has democratized many industries – and wealth management is no exception. As we know, in financial services, digital solutions are at the heart of the consumer experience.

The rise of fintech brands, especially those that help manage investments, is dependent more on technologies than on bespoke human advice, as it is all about scale. This has resulted in redefining wealth management as a service. According to a report by FactSet, investors across the wealth scale—from the mass affluent customer with $100 to invest to the ultra-high net worth (UHNW) client worth $10 million—are already embracing online platforms.

The key to digitalization success is targeting the right business areas, bringing in the right skills, and identifying the key processes to maximize value delivery. A comprehensive hybrid-advisory approach leveraging automation, data analytics, digital, and cloud solutions are the need of the hour.

The Key Pillars of Digital Experience in Wealth Management

Rapid technological advancements, changing investor preferences, and increasing financial awareness are prompting wealth managers to reconsider their customer engagement and business strategies. Digitalization helps modern wealth advisors create and understand their client personas better, moving away from “one size fits all” to a more customized approach. The right technology framework will lower infrastructure costs and improve the efficiency, speed, and scalability of the whole wealth management value chain.

Improving customer prospecting through AI/ML and digital onboarding

Digitalization through AI/ML can help wealth managers identify the right prospects and drive customer acquisitions through data-led personalized marketing. Its ability to combine data from various sources enables it to efficiently classify customer segments based on a variety of criteria, identify prospects using real-time data signals from social media, and generate dynamically personalized content for potential clients, all of which help to increase customer acquisition.

Digital Onboarding: Customer onboarding has traditionally required time-consuming manual documentation. However, many broker-dealers and other wealth management companies are digitizing and automating the process to enhance the client experience and save money.

The foundation for a long-term client relationship is established during the wealth management onboarding process, which includes the first serious interactions between an adviser and a client. Client onboarding processes include

Prospecting
Product selection
Regulatory checks
New Account Opening (NAO)

As a result, businesses are now able to onboard and serve more clients in less time and with fewer resources, maintaining their competitiveness in a market where investors and regulators are driving down fees. Firms with a robust digital onboarding experience will have a solid competitive advantage in the industry.

Achieving investor centricity through data analytics and management

Wealth managers need accurate and real-time data to assess investor sentiments, understand critical market parameters, and produce insights for quick investor decisions. Data can provide timely, pertinent, and actionable insights that can be used to create new (and enhance existing) product and service propositions, optimize channel management, generate higher returns through informed portfolio choices for the investor, and boost customer engagement, and customer retention.

Wealth managers can make wise decisions and appropriate portfolio modifications by using a quantamental investment technique that leverages sentimental analysis, alternative data, and return analytics. Most wealth managers have advanced their client analytics and advisory capabilities and are in various phases of development.

At present, wealth managers have most of their data locked in product silos and legacy systems. Before using advanced analytics, it is understood that access to precise and complete data is necessary. Wealth management companies need a client-focused, precise master data architecture that combines data from all points along the value chain. By increasing their investment in data management and analytics as part of their digitalization initiatives, wealth managers have a better chance of generating higher returns.

Personalized client experience at the front and center

Personalization is one way that advisors can stay competitive with other firms that may offer lower fees or higher returns on investments. According to a survey, investors are increasingly in need of personalized, goal-based planning and other specialized services. In the next two years, 58% of respondents said they would like personalized financial guidance.

Personalization as its name says is unique to each client. To build solutions that will work with whatever position the clients find themselves in, advisors have for decades always thrived on understanding their clients’ backgrounds and perspectives on risk. For instance, knowing information about a client’s household size, state of residency, and annual income are crucial data points in creating customized options that may be more suited for particular people.

Wealth managers can now offer personalized services at a reasonable cost, enabling them to better compete with firms that offer lower fees or higher returns on investments. Automated rebalancing and custom indexing are two examples.

Advisors can automate trading and rebalancing via automated portfolio allocation. And with the help of automated reporting tools, the adviser can inform a large number of clients about portfolio changes.

Enhancing digital investor management and advisory services

For the wealth management sector, it is crucial to offer a more holistic customer and advisory experience. In addition to the human touch, new-age investors are extremely drawn to digital personalization. Wealth managers may increase client acquisition by creating personalized content for potential investors using AI and data-enabled marketing. By increasing customer engagement, a redesigned digital experience can increase customer retention and give advisers more leverage.

A few of the main touchpoints are-

Omnichannel engagement experience: Extends “zero-touch” service by using customized solutions built on video conferencing, on-demand virtual meet (with human advisor), and bot-enabled self-service. Portfolio review and building can be performed over user-friendly virtual solutions accessible over multiple channels.
Data-empowered custom solutions: Includes chatbots and avatars that create a personalized and smoother investor experience, thereby promoting customer retention, upselling, and cross-selling. Many established firms are providing AI/ML-powered offerings to query investor portfolios and their holdings and provide data analytics on the performance of the securities in their portfolio.
Advisor mobile apps: Enables wealth advisors to organize their activities and handle customer interactions. These apps (for example, MyMerrill) can include functionalities like advisor dashboards and 360-degree visualizations of customers and their risk appetites.

Adopting a cloud architecture to improve scalability and operational efficiency

The Information Technology (IT) landscape within wealth management firms consists of legacy systems that maintain a high volume of financial data, which requires increasing maintenance efforts and costs. An increase in financial data will drive automation processes and solutions as automation and AI/ML become more integrated into wealth management services.

Cloud infrastructure can offer a more reliable alternative to internal legacy systems for handling the increased inflow of data at scale, as well as higher operational efficiency and improved agility/time-to-market. By identifying the migration’s decision paths, which will guide the cloud migration strategy through the assessment, design, build, and migration stages, wealth management firms can optimize their existing application portfolio for cloud adoption.

Robo-advisory: taking the stress out of investing

Robo-advisors use automated, algorithm-based systems to provide portfolio management advice. These services are created with customer-centric thinking, and the technology is developed based on their wants and needs.

Customers are drawn to Robo-advice for a variety of reasons. First of all, it entails lower transaction fees and smaller investment requirements. Secondly, it entails more effective investment management. This is because the majority of Robo-offerings offer portfolio management using algorithmically based automated investment solutions that automatically rebalance the customer’s portfolio’s asset allocation without requiring any activity from the user. Thirdly, it provides less experienced investors with more comprehensive advice. Finally, Robo-advice offers more transparency on each investment and how they are likely to perform. The digital interface of many Robo-advisors makes it easy for an investor to analyze their returns versus benchmarks and progress toward goals.

Robo-advice services, whether new-age start-ups or established ones, also have the potential to widen the availability of investment advice from high net-worth individuals to less wealthy investors. Designing robo-advice services for the mass affluent presents a challenge because the customers may have good investment knowledge or little to no investment knowledge, and there is no human advisor there to make sure that the customer has understood the advice they have received.

Robo-advice services that are well-designed assist customers in receiving the best advice for their financial situation and reduce the likelihood that they will purchase the incorrect product. An agile, customer-experience-led, iterative strategy that designs and tests various interaction patterns is the most effective way to do this; whether that be an interactive Web or Mobile App, Chatbot, or combination of multiple technologies, that is right for the persona of a customer using the service.

Source:Inc42: How Robo Advisors Are Changing The Financial Advice Industry

Enhancing Digital Experience across the Wealth Management Value Chain

Opportunities for digitalization are seen throughout the wealth management value chain. An integrated digital transformation that addresses all the relevant user touchpoints would make it possible for investors and advisers to have a generally improved user experience. Every component of the wealth management value chain can be linked to a digitalization lever (Front office, Middle office, and Back office).

Customer experience is adversely affected by front-office digitalization. The focus is on seamless engagement and improved digital user experience to reduce the turnaround time, increase process efficiency, and ensure a smoother customer journey by Big Tech and Fintech experience.
The middle office, which drives the core line of operation in wealth management, is firmly focused on data analytics. However, given the sensitive nature of client data protection concerns and legislation like GDPR and equivalent laws coming into place around the world, a controlled approach to data management and cloudification is the way forward.
Automation and cloudification are the main digitalization potential in the back office space. The user experience quotient is not very high primarily because the activities are more in-house driven rather than external stakeholder driven.

The Road Ahead

The need to stay digitally connected and have a lasting influence on investors and asset managers have accelerated after the global pandemic. The focus is on creating a digital ecosystem built on tools and measures for a touchless remote experience without compromising on quality, which may have permanently changed how people work.

From a service and product perspective, the focus is steadily moving toward personalization, driven by effective data analysis. The emphasis is now on specialized products, personalized advisory services, and flexible pricing structures for different investment classes. One key factor that unites these shifts is the proactive application of technology and accelerated digitalization, whether inorganically or organically.

Effective use of technology through an omnichannel delivery model is essential for people-centric and relationship-driven industries like wealth management to promote the right level of customer engagement. Firms can look forward to investing in in-house technology and aligning with tech vendors, for the timely implementation of modern investment solutions, keeping relevant to a variety of customer segments, and staying ahead of ever-increasing competition.

Banking, Financial Services & Insurance

CBDC: eRupee of India, by India, for India

Dec 12,2022 / By Lakshmipathy Bhat / No Comments

Since 1990, India has taken progressive steps towards innovation in digital payments. Starting with Electronic Clearing Service (ECS) in 1990 to the implementation of the Unified Payments Interface (UPI) in 2016, the Indian payment system has made steady progress in modernising the payment infrastructure and institutionalising a robust payments ecosystem.

Taking yet another step forward, the Reserve Bank of India (RBI) launched the Central Bank Digital Currency (CBDC) pilot with select banks on December 1, 2022. Even though the UPI and COVID-19 pandemic has accelerated the adoption of digital payments, in the Indian context, cash is still king. Therefore, the moment was opportune for the RBI to step-in and bring in necessary digital interventions to reduce this serious dependency on cash. And when the CBDC pilot was launched on 1st December, it was received positively by the industry.

Managing and monitoring cash is not just a regulatory burden but is an expensive affair for businesses as well. And within this context, the CBDC pilot can be viewed as watershed moment that will have far reaching consequences for the Indian economy.

What is CBDC?

The RBI defines the CBDC as a legal tender issued by a central bank in a digital form. It is the same as a sovereign currency and is exchangeable at par with the fiat currency. It will be accepted as a legal tender, and a safe store of value by all citizens, enterprises, and government agencies.

It is a fungible legal tender for which holders need not have bank accounts. And as exchange of cash between parties happen outside the banking system, payments made using CBDC (or e-rupee) will not go via the traditional interbank payment settlement processes and will never appear in customer’s bank statements. In effect, the e-rupee will function exactly like cash in our pockets or wallets and will be available in the same denominations.

What are the key benefits of CBDC?

As per the RBI’s Concept Note on Central Bank Digital Currency, the key motivations for exploring the issuance of CBDC in India were to reduce operational costs associated with physical cash management, fostering financial inclusion, bringing resilience, efficiency and innovation in payment systems, boosting innovations in cross-border payments and providing the public with uses that any virtual currency can provide, without the associated risks. Therefore, unlike cryptocurrencies, CBDCs will provide the benefits of virtual currencies while ensuring consumer protection.

Benefits for the public:

The biggest benefit for the general public is that they would not be required to carry and manage cash. Hence, there is no risk of losing cash. In the e-rupee system, even if someone loses the phone, the wallet can be re-installed, and the money can be recovered.
People can transact freely without having to worry about managing and replacing torn notes.
In due course, it will enable underbanked and unbanked people to directly receive government grants and cash benefits.
With e-rupee wallet, people will have access to better financial services, especially in the remote areas.
Safeguards people from losing money due to the circulation of counterfeit currencies.
Instant settlement of transactions via wallet-to-wallet transfers. In due course, people will be able to transact in offline mode as well.

Benefits for the society:

Today India spends close to Rs. 5000 crore per year (approx. $6 billion) in printing physical cash. Not to forget the countless trees that are felled and the consumption of enormous quantities of ink in printing currency notes. For one, the transition to e-rupee will be a significant gain to the exchequer and the environment. Moreover:

Retail outlets, stores and banks will reduce substantial overheads to manage high volumes of cash.
It will allow the government to address the growing concerns around the circulation of counterfeit notes. With e-rupee, every rupee will be verifiable.

Despite various steps taken in strengthening financial inclusion, a lot still needs to be done. Challenges like limited physical infrastructure in remote areas, poor connectivity, lack of integration of credit with livelihood activities or access to other financial services may be overcome by providing the public with a safe sovereign digital money for meeting various transactional needs. It may be hoped that e-rupee shall make financial services more accessible to the unbanked and underbanked population.

Unlike UPI or any other form of electronic payment, e-rupee transactions will not be settled via the current settlement process and therefore, will reduce the stress on the current inter-bank settlement processes.

In the current context, physical exchange of cash leaves no trail. Therefore, it is almost impossible to track & trace how the cash changed hands. However, if it is required, the e-rupee will assist the government in tracing all transactions done via e-rupee.

As is the case with most digital interventions, the moment these interventions go public, diverse and wide-ranging use cases emerge. The industry always finds unique and innovative ways to exploit opportunities in a manner that serves the interests of their organisations and their end-customers. As the pilot goes on and as the product matures, we are certain we’ll see far more uses for the e-rupee than we see today. With a sense of cautious optimism, we hope that the e-rupee truly transforms the way India transacts across cities, towns and villages.

Banking, Financial Services & Insurance Fintech Insurance

InsurTech Challenges and Role of Technology for Growth of Insurance Sector

Nov 4,2022 / By Basant Baruah / No Comments

In a world of unpredictable yet unavoidable change, individuals, companies and even governments turn to the insurance sector to be prepared. Insurance needs are changing in many ways, such as including risks related to climate change like floods or bushfires, or even novelties like ‘hole-in-one’ insurance (where a golf tournament insures itself to pay the prize bonanza on the off chance that a hole-in-one is achieved). With an increasingly online generation, even as traditional insurers bank on the credibility and trust they have accumulated, the new age InsurTech companies chip away at the market with digital experiences and new models.

When it comes to innovating with technology, InsurTech companies have an advantage over traditional insurers. They are nimble and flexible with their offerings, able to quickly establish low-cost digital platforms and new operating models. InsurTech companies’ biggest advantage is the hold they have over the customer’s pulse. With smartphones becoming commonplace, customers find that InsurTech offers comfort, convenience, and speed in making important insurance-related decisions and transactions.

Research indicates that 28 of the 280 FinTech firms that have turned unicorns to date have played an instrumental role in driving innovation or disrupting the way insurance is done. From claim management to reinsurance, asset management, customer onboarding, and engagement, InsurTechs have earned their colors across the insurance value chain and are here to stay.

Challenges to InsurTech

Despite these gains, experts believe that InsurTech market growth will have to endure several constraints. Foremost among them is a lack of awareness about the value InsurTech can deliver, and dearth of professionals who can expertly work with advanced technologies. These factors could restrict InsurTech companies from scaling their technology capabilities to the extent desired.

However, it is undisputed that the future of insurance will be tech-driven in the form of embedded ecosystems, AI & ML, blockchain, low code technology, and more. 85% of insurance companies recognize the need to prioritize digitalization, so it may not be long before traditional market leaders catch up with their technology capabilities or look to buy out smaller players. InsurTech start-ups have their work cut out in gaining the kind of trust and credibility enjoyed by established insurers. Now, they must rethink strategy to retain their technology advantage.

If we look at the US which is the global market leader, InsurTech is expected to grow at more than 7% CAGR over the next five years. The competition is definitely heating up here.

Business opportunities for insurance will continue to flow in as the world becomes increasingly digital. More aspects such as health, travel, auto, and home will be included under the umbrella of online insurance.

InsurTech companies will need rely on their strength – technology – to offer a wider, more personalized range of benefits shaped by data, new offerings like social insurance, and cost saving tools like virtual agents powered by conversational AI etc.

McKinsey research opines that five rapidly advancing technologies will significantly redefine the future of insurance. These include applied AI, distributed infrastructure, future of connectivity, next-level automation, and trust architecture. By putting the full force of their tech advantage here, InsurTech players can solidify their business and expand their portfolio.

1. Powering up core processes with AI

Since the pandemic, at least a quarter of life insurers in the US have expanded their automated underwriting practice to simplify the application process. From reducing claims processing time and cost to improving fraudulent claim detection and claim adjustment processes, AI and automation are proving be invaluable.

Take for example, the AI-enabled platform offered by Bdeo, available on their mobile app. It comes with a chatbot that uses Natural Language Processing principles to liaise with claimants, get first-hand info on the accident/damage that has occurred and helps them share photographic evidence of acceptable quality on the platform. The insurer can use the app to inspect and investigate the incident remotely using computer vision models. Doing so helps avert errors in evaluation and improves the overall claim processing experience for both the insurer and claimant.

Studies predict that AI will disrupt underwriting, claims, marketing, distribution and other core processes by enabling more human-like interactions across various customer touchpoints. There is a plethora of opportunities that can be exploited. For example, the associated customer data can be used for predictive analysis and forecasting, which can in turn, inform the development of new product and service lines.

2. Enabling intelligent insurance with distributed infrastructure on the cloud

Many core insurance processes that have been weighed down by legacy systems are finally modernizing. This allows insurers to leverage cloud-native infrastructure, ramp up to manage workloads without impacting customer experience and speed up their innovation efforts. Thanks to cloud computing, they will be better placed to harness the massive amounts of claim-related data available to benefit their customers and increase profitability.

This is a huge opportunity for traditional insurers to collaborate with InsurTech to form partnerships that leverage their strengths and quickly enable plug-ins, distribution channels, and other value-adds. For instance, InsurTechs can offer digital solutions to efficiently sift through vast historical data of established insurers, to identify and interpret customer patterns and insights to determine the kind of new product/service lines to be developed. In fact, at least 75% of insurers were found to be seeking out InsurTech collaboration to improve their customer experiences according to a Capgemini survey.

3. Developing insurance products using telematics

Telematics technology is increasingly being used to monitor, interpret, even influence consumer behavior. For example, innovation stimulated by IoT adoption is being applied in connected home devices to track humidity, temperature and other parameters, which potentially cause damage to property. Insurers can leverage the data generated on these devices to estimate risk over time. Similar innovations are being explored across the domains of insurance to life, health, auto, manufacturing, commerce etc. The advent of 5G will enable real-time data sharing and make it possible for insurers to turnaround services faster than ever.

For example, being covered against ride cancellations is a value-add for customers and digital solutions can be developed to enable this as a timely service using real-time availability of data. Another example of value-add is the coverage against bodily harm to earners and riders of every trip offered by Uber in partnership with a leading insurer.

4. Enabling human decisions via bots

While robotic process automation (RPA) has proved its worth in automating back-office functions in the insurance industry, there’s a lot it can do in terms of next-level process automation that will shape the future of insurance. For example, the IoT-enabled, real-time monitoring of factory equipment can predict maintenance needs and prevent repair or damage that result in insurance claims.

RPA also has a distinct role to play in supporting human decisions in a cost-effective and timely manner. As an example, it can expedite claims processing wherein photos of the damage to a vehicle are automatically assessed and verified for authenticity without requiring an in-person visit by a claims adjuster to the damage site. Likewise, building optical character recognition features into RPA will help extract text from claim applications in large volumes and ensure that the information it contains is distributed to the right functions for further processing.

5. Laying the foundations for trust with blockchain

Increased digitalization of insurance is raising security concerns due to the sensitive nature of customer data that is being shared across the insurance ecosystem. Building customer trust will be a priority for insurance players, which is where blockchain comes to the rescue.

Along with its advantages of transparency and efficiency, blockchain will play a leading role in helping carriers safeguard customer data from cyberattacks and data breaches. It will also simplify user authentication, identity management, and fraudulent claim detection etc. Through blockchain-based smart contracts, policies can be converted to decentralized lines of codes that will make consumer’s data immutable and easily available for immediate verification in the event of any claims made to the insurer. If it proves to be fraudulent, the contract will immediately be discontinued, and the premium amount paid returned to the insured. This kind of data transparency and responsiveness of the system will help build trust between all concerned parties.

The future of digital insurance paved by tech-led design

As insurance becomes more digitally driven, user experience (UX) will be all the more crucial for branding. While an omnichannel insurance experience is the norm today, creating memorable user experiences at all possible touchpoints will be paramount to carving out stronger market positions for the InsurTech brand.

For example, the silver agers generation are no longer the most dominant consumers of insurance. In fact, studies that the interest now being shown by millennials and Gen-Zers towards insurance products exceeds that of the older generations.

Or, as this chart indicates, nearly half the individuals in the 65+ age category are unlikely to use an insurance app. If the insurer wants to attract more consumers from this cohort, they will need to leverage data to understand preferences, simplify interfaces, customize their offerings and so on.

According to the World InsurTech Report 2021, half of the insurance customers are willing to explore solutions offered by new-age digital players. The insurance market will experience disruption and a new order will emerge. Traditional insurers are more likely than ever to engage in partnerships with InsurTechs to stay relevant. Niche players and start-ups in InsurTech will not only need to leverage emerging technologies but also understand the complexities of insurance better and closely follow changing needs of their target demographics.

Led by research, data analytics, and empathic and intuitive design of user-centric interfaces, InsurTech players will be able to create market differentiation that can help them explore opportunities to build partnerships with traditional players so that both survive and thrive.

Banking, Financial Services & Insurance Fintech Insurance

BNPL – Passing Fad or Promising Future for Fintech?

Sep 6,2022 / By Pooja Bal / No Comments

Taking a loan to pay for higher education is a common phenomenon in the US. But who would have imagined that due to food inflation, even essentials such as groceries will be considered for the ‘Buy Now Pay Later’ (BNPL) phenomenon? On Klarna, a leading player in this domain, more than 50% of the top 100 items bought on the app belong to grocery or household items.

As more younger consumers go online, they have been experimenting with alternative payments methods. The rise of smartphones and e-commerce, now integrated with social media platforms is among the top trends impacting online sales and payments. The creator economy too is fueling social commerce. Such trends have attracted a new demographic – the millennials and teenagers. Now wonder that Fintech players are crafting new solutions to meet this demand. Pre-paid cards and digital bank accounts for teenagers are meant to address this trend. Fampay, Junio in India and Revolut <18 in the UK are a few examples.

BNPL: ‘credit’ where due

Over the last couple of years, the BNPL trend also referred to as ‘Pay in 4’ model, is meant to address a market opportunity. The post-COVID scenario and inflation in many countries has made it even more attractive – especially for a demographic with limited income resources.

In a 2021 research in the US, it was found that 60% of those surveyed had used a BNPL service. The main incentive of course is the interest-free instalment option which reduces the spending pressure and provides an incentive for online purchases. Klarna, claims a 41% increase in order value and 30% increase in conversion through their BNPL solutions.

The adoption of BNPL is a worldwide phenomenon. According to research in 18 countries from YouGov, Indonesians made the highest proportion of purchases using a BNPL plan (27%) – almost double the global average of 15%.

Source: YouGov

The same survey also mentions that in India, BNPL services grew a mind-boggling 637% in 2021. Naturally, such solutions are popular among the younger demographic. A whopping 75% of BNPL users in the US are Gen Z or millennials. Credit card penetration in India is still in single digits. BNPL was seen as the answer to a demographic which could be denied a credit card.

Fintech brands too were quick to spot the opportunity. In mid-2021 there were already 50+ companies offering ‘Buy Now Pay Later’ services across the world. The number is likely to have gone up in the ensuing period. In India, brands such as UNI have positioned themselves as a revolution in credit offering payment options in three or two instalments.

BNPL players are also tying up with large retailers such as Amazon, Macy’s and Target – thereby gaining access to a large, ready customer base. Aside from the smooth user experience, some serious technology is at play behind BNPL experiences. Apparently, Affirm uses over 200 consumer data points for risk management, while its existing loan users improve its AI algorithm.

Some of the aspects BNPL players must pay attention to, from tech POV are:

Infrastructure: The cloud infrastructure should help scale up operations easily, provide new products and services using on-demand computing. It should also safeguard consumer data and aid in maintaining regulatory compliance.

Risk Management: machine learning comes into play here in developing models for better risk identification and management, real-time credit score prediction, and payment management.

Security: BNPL players are expected to maintain the essential infrastructure in accordance with security standards. Major players such as Klarna collaborate with AWS’s compliance and security assurance teams.

Analytics: The integration of data workflows should make it simple for data to be absorbed from a variety of structured (such as transaction and payment history) and unstructured sources (such as social media activity, credit bureaus, and spending behavior). Such information gives early warning signs of credit degradation during times of difficulty and assists in the creation of a 360-degree perspective of the consumer. The data analytics tools aid businesses in understanding the preferences of their customers and the performance of their own products.

Tech partners: to create better products and solutions, fintech companies merge or partner with services who add value. Block (formerly Square) acquired Afterpay a pure play BNPL company. To enhance its underwriting capabilities and speed up automated credit decision making, particularly to draw in millennials and Gen Zs, Klarna purchased the Italian payment business Moneymour. Additionally, Provenir, a provider of credit risk analytics, and Klarna have teamed up. Credit scoring, underwriting, and real-time decision-making at the point of sale are bundled as a result of their combined efforts.

So does all this point to a rosy future for BNPL? According to industry experts it may be prudent to exercise caution as regulators have taken steps affecting the business model of several players, in markets like India. What’s driving such actions is the fear of triggering overspending leading to credit risk and worse still, poor financial discipline among a young audience.

Buy Now, Pain Later?

In June 2022, the Reserve Bank of India issued a circular banning non-banks from loading pre-paid instruments (PPIs) such as digital wallets or cards using credit lines. Several brands suspended their BNPL offerings following this development. According to Euromonitor:

The Financial Conduct Authority (FCA) in the UK has named the key risks the model holds for consumers and the wider credit market. These include, but are not limited to, the lack of information for consumers around the features of BNPL, the lack of consumer creditworthiness assessment, and the potential creation of over-indebtedness.

Nearly 70% of BNPL users admit to spending more than they would if they had to pay for everything upfront, according to LendingTree. What’s more, 42% of them have made a late payment on them. While consumers maybe attracted by simple onboarding experience and ease of payment, the offline experience has not always been pretty in India. According to reports, lending apps have used unsavory methods to coerce users who have defaulted on payments.

These developments point to the industry being regulatory dependent in the near future and rightly so. What could be the broad contours of solutions for both end consumers and Fintech players? According to financial industry insiders, full-service banks seem to be better placed to make the most of the real demand for ‘pay-over-time’ services. Pure-play BNPL service providers may have to tweak their core offering based on the regulatory oversight in their home markets.

Trust, convenience and ease of use are three critical aspects of BNPL success. Traditional banks score better on trust – a critical factor in financial service products. According to YouGov study, only 36% in the 18-24 age group trust BNPL companies as compared to 61% in the same group for traditional banks.

Source: YouGov

The implications for the ecosystem

There are several pointers for both end-consumers and the fintech ecosystem from this emerging trend.

Brands in the BNPL sector have a real obligation to educate users about financial prudence, especially to the younger demographic. It must be made clear to the end-user in every touch point that this is a loan and there are consequences for missed payments. Consumers must also be educated about the risk of over-spending and its fallouts. This is important as a key metric for BNPL players is the re-use of a service. According to PayPal 70% of their customers use the service within six months of first use. In the US, as BNPL is offered at more merchants the older demographic too is coming into the fold. So, it’s not just the Gen Z’s and millennials who will be target audience in the future.

For brands, convenience could translate to ubiquitous acceptance across online portals and POS at physical locations. Clubbing all BNPL payments with one brand would also make it easy to manage for the end user. Ease-of-use comes into play with respect to the app experience. The onboarding should strike a balance between being friction-free and conveying the details of the financial terms in a transparent manner, especially the repayment schedule and penalties for delay.

In sum, BNPL is a useful and convenient product feature especially for those with limited leeway in upfront spending capacity. But industry growth aided by great digital experience will depend on regulatory constraints and educating the consumer about the need for financial prudence.

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