Category: FinTech

The future of work

The Future of Work: How Fintech Startups Can Adapt and Thrive with Technology

August 23, 2024

Fintech has been a key buzzword in the banking, financial services, and insurance (BFSI) sector worldwide. It essentially encompasses a broader range of technological innovation aimed at elevating, automating, and simplifying financial services and products. Of course, now we associate fintech jobs with everything from mobile banking, blockchain and cryptocurrencies, AI and machine learning, and even peer-to-peer lending to Chatbot driven customer service, automated underwriting, and more. But what does the future of work look like for fintech startups? How can they adapt and thrive by leveraging technology? Here’s a closer look below. Fintech Customer Experience A major part of fintech innovation and technological upgrades are expected to be directed towards boosting customer experiences even more in the near future. Going beyond 24-7 access, swift transactions, and automated service and support, there will be increased emphasis on hyper-personalisation and financial inclusion. Fintech startups are expected to come up with simpler and more effective products and offerings that help them cater to wider audiences that are otherwise unbanked or under-served by the conventional financial services sectors. Here are some other technology-driven aspects that may come into play. Fintech Security Challenges This is another aspect where fintech startups will leverage technology for thriving in the new digital age and also to combat these challenges head-on.  Here are some key pointers worth noting: Fintech Jobs- How they May Evolve With the growing emphasis on fintech innovation, there will be an impact on jobs in the sector in the future as well. Here is how it stacks up for fintech startups. Some Other Ways in Which Fintech Startups are Expected to Evolve Here are some other pathways that fintech startups may take in the near future, according to industry watchers. Tech Innovation Case Study- Square Often times, fintech innovation is not just about up-skilling, adapting to newer requirements, or transforming the workforce. It is sometimes about taking something that exists and making it better. Square was launched in 2009 by Jack Dorsey, the co-founder of Twitter, and it wanted to fill up a major gap in terms of payment processing for small businesses. While this already existed in multiple forms, it was mostly expensive and complex for this target audience. Square came up with a unique POS (point-of-sale) system with a micro card reader that could easily be plugged into smartphones. This portable card reader was easy to set up and Square also retained its relevance by offering additional like analytics, inventory management, and loans. By 2023, the company had 4 million+ sellers on the platform with $4.68 billion with sizable revenue increases and more. Square has also expanded its entire ecosystem, offering everything from payroll to cryptocurrency trading via its Cash App. The customer-centric focus and user-oriented design were major USPs along with the ability to offer integrated solutions swiftly. This eventually built customer trust and ensured huge lifetime value, particularly with flat-rate pricing and overall transparency. What’s the Key Approach for Fintechs Going Forward? Fintech startups will have to continually innovate, adapt, and learn. These are the three buzzwords that should define the approach for the future years in an increasingly complex regulatory environment and fast-changing technological ecosystem. Fintech startups will have to leverage technological expertise and skilled personnel towards staying relevant and adapting towards industry changes. There will be more training and up-skilling needed for the present workforce, while new recruitments will mostly revolve around domain experts with sizable expertise in core areas like blockchain, AI, machine learning, and so on. At the same time, fintechs will also have to keep pushing the boundaries higher in terms of customer service, personalisation, data analytics, and also Cybersecurity and data privacy. These are all areas which will require sizable investments of time and resources to not just survive but also thrive in the global financial landscape. FAQs 1. What are the biggest technological trends shaping the future of work for Fintech startups? Some of the major technological trends that are shaping the future of work in the space include the pivot towards AI and machine learning-driven personalisation, automation, data analytics, blockchain, and decentralied finance. 2. How can Fintech startups leverage technology to attract and retain top talent in this competitive landscape? Fintech startups can make use of dynamic technological tools to find the top talent in a more competitive landscape. AI and machine learning can play a major role in skimming through vast datasets to come up with professionals who can be the right fit. At the same time, Applicant tracking systems can also manage applications and communicate with candidates. 3. What technological challenges will Fintech startups face in the future, and how can they prepare? Some of the future technological challenges for fintech startups include regulatory complexities, data security and privacy hurdles, and so on. At the same time, there will also be a challenge related to finding competent professionals to manage the next level of tech-driven solutions. 4. What specific technologies can Fintech startups adopt to improve efficiency, security, and customer experience? Some of the technologies that fintech startups can adopt for higher security, efficiency, and better customer experiences include automation, AI, machine learning, blockchain, and IoT (Internet of Things). 5. How can Fintech startups stay agile and adaptable in a rapidly evolving technological environment? Fintech startups can stay more adaptable and agile in a fast-evolving technological environment through setting up frameworks to continually track and implement new regulatory laws, and explore new technological products/solutions. At the same time, they will also have to invest in lifelong learning and up-skilling models for the workforce.

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Data-Driven Decision Making: How Advanced Analytics Is Shaping Fintech Strategies

Data-Driven Decision Making: How Advanced Analytics Is Shaping Fintech Strategies

November 21, 2023

Data-driven decision-making and better fintech strategies are a result of advanced analytics in fintech, a trend which is making the whole sector sit up and take notice of their immense potential. Open banking and big data analytics are shaping the financial sector as it prepares for a more customer-centric and digital shift in the near future.  How has Data Analytics in Finance Been a Game-Changer for the Industry? Advanced analytics in fintech has completely changed the operational rules of the game for these platforms along with other financial institutions at large. Customers now have more control over their finances with open banking and expect more personalised experiences as a result. Big data analytics in finance is forecasted to continue its growth momentum, leading to newer fintech innovation opportunities. More platforms and market players will look at leveraging big data to deliver better services to customers along with tailored and personalised products and experiences.  Here’s how advanced analytics in fintech can help industry stakeholders in the current scenario:  As can be seen, advanced analytics in fintech has several potential benefits that will usher in a whole new era of smart banking and finance solutions in the future. Companies can easily optimise customer acquisition with data-driven marketing and personalisation. They can also scale up customer retention as a result, while identifying better opportunities for up-selling or cross-selling along with communicating better with customers in a personalised manner. They can also combat cyber-security issues and fraud better through machine learning algorithms that identify unusual patterns, anomalies, and other suspicious activities. AI and automation can be used to swiftly gather insights from vast amounts of information while also enabling automated customer service and communication via Chatbots.  Sounds interesting? Analytics and AI are poised to bring in a whole new world for customers and fintech players alike. The best part is that there are only upsides for all stakeholders in the process.  FAQs How is advanced analytics revolutionising data-driven decision-making in the fintech industry? Advanced analytics is helping fintech players make data-driven decisions related to personalised customer communication, marketing, offering tailored products and services, meeting customer demand, and also in terms of evaluating market conditions and responding to them more accurately.  What types of data sources and analytics tools are fintech companies leveraging to gain a competitive edge? Fintech companies are leveraging various data sources including their own databases, online channels and social media platforms, POS transactions and other transaction histories, and more. They are also leveraging AI and machine learning along with automation and big data analytics to gain a competitive edge in their respective market segments.  How can data-driven insights lead to more personalised fintech products and services for customers? Data–driven insights help fintech companies build personalised customer profiles and offer customised products and services to customers based on their transaction history, behavioural habits, preferences, and other parameters.  What are the key challenges and considerations when implementing advanced analytics in fintech strategy development? Some of the major considerations or challenges while implementing advanced analytics in fintech strategy development include regulatory norms, customer consent and data privacy, and the safety of customer data.

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5 ways Tech is building better customer experiences in Insurance and Banking

5 ways Tech is building better customer experiences in Insurance and Banking

September 28, 2023

Tech innovations have steadily reshaped the insurance industry and banking landscape in recent years. There are several ways in which this digital transformation is enabling superior customer experiences in the space. Multiple financial technology-driven innovations are steadily coming to the forefront and are completely reshaping the sector. For instance, reports state that several insurance players are looking at AI and only a few have upgraded their abilities throughout the spectrum.  One of the biggest trends will be applying AI for disrupting claims, distribution, services, and underwriting, which will create models more familiar as humans in the loop. This enables better customer touch points along with scaling up productivity simultaneously. Distributed infrastructure and cloud will be crucial game-changers along with virtualization and automation in addition to trust architecture. Let us first look at how tech stacks up in the space before examining the ways in which it is creating improved customer experiences.  Where does tech stand in the scheme of things?  Tech innovations are already revamping the insurance industry and here is where they stand currently.  As can be seen, customer experiences can improve in the near future, with suitable financial technology implementation. Here is a closer look at the ways in which the insurance sector has steadily evolved over the last few years.  Benefits that tech brings to customer experiences  Some of these advantages include the following:  Many customers may testify to their insurance experiences improving over the years, particularly with technological advancements. Apps and online platforms have changed the game while multiple background or back-office procedures have also become more streamlined. Technology has also enabled higher cost and time savings for insurance companies while enhancing customer experiences considerably in turn.  FAQs 1. What is customer experience in insurance? Customer experience or CX is the entire process and stages of interaction between insurance companies and customers. This covers queries, inquiries, responses, feedback, guidance, paperwork, applications, claims filing, processing, and more.  2. How can the insurance industry improve customer experience? The insurance industry can considerably enhance customer experiences by lowering claims processing timelines with AI-driven automation. With accurate and swifter evaluation, companies can lower claim payment times considerably. At the same time, they can leverage modern technology to update and remind customers periodically, while using technological tools for responding to customers and providing them ample guidance whenever they need the same.  3. Why customer experience is important in the insurance industry?  Customer experience matters immensely in the insurance industry since it can make or break relationships. Customers may discontinue or not renew policies due to poor experiences in terms of solving their problems, getting information, or completing claims processing or paperwork.  4. What is the best way to improve customer experience?  The best way to boost customer experiences is to focus on resolving customer processes and formalities (including paperwork) in the quickest possible time. At the same time, there should be an emphasis on directing customers to the right resources whenever needed. 

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RBI plans to introduce wholesale CBDC in the call money market soon

September 19, 2023

India is already synonymous with futuristic technological advancements and innovations that extend to every industry. Finance is no exception to shifting global undercurrents and the Reserve Bank of India (RBI) has been at the forefront of several future-first transitions in recent years.  One such move has been the RBI’s move pertaining to the extension of the wholesale CBDC (central bank digital currency) as tokens for the purpose of interbank borrowing or the call money market. The apex bank of the country is reportedly planning this new feature rollout for the RBI digital currency in the near future as per various reports. Here’s what we know so far.  RBI’s big wholesale CBDC initiative Here are some insights as to the RBI’s plans to boost money market efficiency:  PTP will take visitors through the entire framework, beginning from onboarding to the dairy and KCC loan sanction and disbursement processes within a few minutes. It may completely transform rural credit sectors in the future while being used for distributing loans of smaller ticket sizes in the future too (personal loans and MSME loans). The RBI has also worked to showcase its digital rupee and its evolution along with conducting live transactions with the same at the summit. UPI One World will help visitors complete onboarding without possessing an Indian bank account.  RuPay On-The-Go will enable contactless payments through accessories used or worn regularly. BBPS will facilitate cross-border bill payments, complete with easier fintech integration and support for regular financial entities to execute domestic and cross-border transactions alike. RBI’s Innovation Pavilion at the G20 Summit venue saw the announcement being made on the starting of the wholesale CBDC pilot for interbank borrowing either this month or early next month.  The RBI is betting big on this project, with an aim towards touching 1 million transactions each day by end-2023 as compared to 20-25,000 for July. On the other hand, Punjab National Bank (PNB) has also announced its CBDC (central bank digital currency) launch with UPI (unified payments interface) interoperability being a key feature for the digital rupee-based mobile application. As can be seen, there are exciting developments afoot in the Indian banking and financial services industry. The Reserve Bank of India is focusing on technology-backed innovation, an approach that will only enhance operational efficiencies and ecosystem-wide transparency in the near future.  FAQs The call money market (CMM) is the platform for short-term loans that are sometimes one-day loans, traded by financial institutions like banks. Lenders and borrowers in this market are majorly these banks or entities. CMM may be accessed by banks for meeting any reserve needs or for covering any sudden cash shortfalls on any specific date.  Wholesale CBDC will have a positive impact on the call money market. It will transform the interbank market by improving overall efficiency. The usage of central bank money for settlements will lower the costs of transactions greatly. This will be possible by pre-empting the requirement for any infrastructure for settlement guarantees or other collateral for the mitigation of settlement risks.  The RBI is already using e?-R as its retail version pilot for the CBDC while Digital Rupee – Wholesale (e?-W) has also been introduced. The former is similar to a digital token that is representative of legal tender. There are several blockchain technology components that are being used for these initiatives.  The RBI is expected to take several measures towards ensuring greater security for wholesale CBDC transactions. It has already proposed two CBDC structures, namely account and token-based. It has already aligned itself towards the latter for retail while the wholesale sector may get the former. Usage will be secured through tokenization at the retail level, ensuring security against fraudulent payments, duplicate payments, and other issues. There could be dedicated security protocols implemented by the RBI for these initiatives. 

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Financial Services with Blockchain Technology

Securing Sensitive Information: Empowering Financial Services with Blockchain Technology

July 18, 2023

Sensitive data protection has become a major buzzword in the financial series industry. Financial privacy and data security solutions are modern-day necessities for banks and other entities operating in the industry, considering disastrous data breaches and Cybersecurity threats that have rocked the segment in the last few years.  Blockchain technology has also become a major tool for empowering financial services players to safeguard sensitive information. It is a transparent, decentralised and secure framework which will ultimately transform the manner in which financial transactions are executed. It will lead to lower costs, higher security, and improved efficiency levels overall. Here are a few aspects that you should certainly take into account.  Blockchain for identity verification Blockchain technology has wide-ranging applications for identity verification purposes. Here are some points in this regard: Along with identity verification and management, blockchain technology also has huge potential in terms of cross-border payments. Here is a closer look at the same below. Blockchain for supply chain finance: Blockchain is also enhancing supply chain finance (SCF) methods. It is lowering the transaction times and streamlining the processes. Here are some other benefits that should be kept in mind: The trading and payments landscape may be considerably redefined by blockchain technology in the future. The best part is that it also enables sensitive data protection while streamlining operations alongside.  Blockchain for cross-border payments: Cross-border payments are vital for businesses, individuals, institutions, traders, and other global organisations. The usage of blockchain is what makes the entire procedure hassle-free. Hence, individuals and companies are leaning more towards blockchain for cross-border payments in recent times. This trend should only gain traction in the near future. Let us now look at the advantages of blockchain technology for supply chain finance. FAQs 1.What are the key advantages of using blockchain for securing sensitive data in financial services? Blockchain works on the premise of an immutable, decentralised, and shared ledger. It enhances security, trust, and transparency along with the traceability of all information and transactions throughout the network. Members can only access the ledger with permission, while nothing can be modified or altered. 2. Are there any specific use cases or success stories of blockchain securing sensitive financial data? There are several use cases that have been observed in recent times. Banks and other financial services players have been using blockchain technology to automatically time-stamp and store transaction records. It is also enabling easier tracking of data which is stored in immutable and unalterable ledgers. Hence, sensitive data is being stored and tracked in real-time without any hassles. 3. What measures are in place to protect sensitive financial information from insider threats in blockchain-based systems? Some of the key measures include cryptography, consensus, and decentralisation. Additionally, the blocks are linked and structured in a manner where tampering is near-impossible. The system uses the principle of trust that is consensus-based to prevent the insertion of changed/false records. Advanced encryption also enables enhanced data security in this case. 4. How does blockchain empower financial services to comply with data privacy regulations? Blockchain technology helps financial services players to adhere to data privacy regulations better. The immutable, consent-based, and decentralised ledger means that users are in control of their own data. They can only share it after providing consent. Participants collectively authenticate and maintain data with full access control via smart contracts. The whole system ensures higher transparency and authentication. Blockchain helps intellectual property owners to register trademarks, authenticate their ownership rights, combat counterfeiting, lease IPs with smart contracts, and also take care of their privacy. Blockchain can also facilitate autonomous and secure digital identities.

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Navigating Risk in Digital Lending

Navigating Risk in Digital Lending

May 30, 2023

Digital lending risks abound in the current scenario, which require careful navigation. The need for suitable risk management in lending is increasing by the day. Here is a snapshot of the biggest online lending risks and how financial institutions can navigate the same. 1. Higher consumer risks in digital lending– Banks are facing higher operational risks in online lending. They are streamlining the process through the adoption of paperless loan approvals, while using automation to enhance overall quality and time alike. There is a concern regarding risks of customer data safety, since they share account and personal details, credit history and a lot more on applications. Banks and financial institutions are now looking at increasing cyber security in lending and measures to implement mechanisms for data privacy in lending. Dedicated security prevention is possible with the right technological framework and solutions which BFS players are steadily opting for.  2. Credit risks– There is a need for proper credit risk assessment in digital lending, considering how customers with poor or low credit may lead to growing NPAs and hassles for BFS players At the same time, there is always a risk of defaults in the future. Hence, these companies need to use data analytics and advanced credit evaluation systems for ascertaining the creditworthiness of borrowers. There is also a need for swift assessment and proper credit evaluation models can help address the same digitally. 3. Compliance and regulatory risks- BFS players have to increasingly factor in compliance risks in fintech lending. The RBI and other authorities are coming up with evolving guidelines and regulatory mechanisms that have to be adhered to in a strict manner without lapses. Usage of artificial intelligence, insights, and regulatory mechanisms is the solution to navigate these challenges. 4. Market risks in digital lending– There are always risks of market changes, volatility, and fluctuations that may turn out to be problematic for digital lenders. Hence, using advanced AI-based forecasting models and analytics could help gauge market patterns, trends, and consumer preferences. This will aid the creation of products and services, while boosting strategic decision-making simultaneously. 5.Operational risks- Digital lending often works through a transaction process that has multiple layers. Many services are often outsourced to several entities. It sometimes becomes complicated, in terms of redressing grievances, taking care of customer complaints, and ensure effective and prompt service. This can be navigated with the use of advanced AI-based Chatbots for resolving most customer queries and prompt engagement with customers. From algorithms that personalise customer journeys and recommend products to those that quickly resolve issues or take care of complaints, automation can work wonders in this case. 6.Fraud risks– There are always risks pertaining to fraudulent applications, transactions, and breach of trust within the ecosystem. BFS players can ensure better fraud prevention in digital lending with advanced automation. Historical data analytics can help gauge patterns of a fraudulent nature. This can help detect and combat frauds in a better manner. NBFCs and banks should endeavour to periodically get security audits done, while implementing robust Cyber security measures at the same time. From firewalls and advanced encryption protocols to multi-factor authentication, there are several options available. Identity verification can be scaled up with biometric authentication, digital KYC, and quick credit bureau checks. Data analytics can be used to analyse credit histories and verify income and debt-to-income ratios. Diversifying lending portfolios is also recommended for combating market risks more effectively. FAQs 1.What are the different risk associated with lending? There are several risks associated with lending. These include data privacy, operational, credit, regulatory, market and fraud risks. 2.What are the risks associated with digital finance? Digital finance faces risks linked to the privacy of consumer data, breaches in security frameworks, preventing frauds, credit risks, and compliance/regulatory risks. 3.How do market and economic factors impact digital lending risks? Fluctuations in the market on account of geopolitical and economic factors can impact consumer behaviour and also lending rates. The effect on these variables may lead to business risks for the institution. 4.What measures can be taken to address the risk of borrower default in digital lending? Borrower default risks can be minimised with proper data analytics for evaluating historical borrower data, credit histories, debt-to-income ratios, track records, and other vital information. This helps establish the creditworthiness of individual buyers, while flagging risky customers in advance.

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How the Large Language Models like GPT are revolutionising the AI space in all domains (BFSI, Pharma, and HealthCare)

How the Large Language Models like GPT are revolutionising the AI space in all domains (BFSI, Pharma, and HealthCare)

April 6, 2023

Large language models or LLMs are ushering in a widespread AI revolution throughout multiple business and industry domains. DALL-E-2 set the cat amongst the pigeons in the AI segment in July 2022, developed by OpenAI, before ChatGPT came into the picture. This has put the spotlight firmly on the invaluable role increasingly played by LLMs (large language models) across diverse sectors. Here’s examining the phenomenon in greater detail.  LLMs make a sizeable impact worldwide With natural language processing, machine learning, deep learning, and predictive analytics among other advanced tools, LLM neural networks are steadily widening the scope of impact of AI across the BFSI (banking, financial services, and insurance), pharma, healthcare, robotics, and gaming sectors among others.  Large language models are learning-based algorithms which can identify, summarise, predict, translate, and generate languages with the help of massive text-based datasets with negligible supervision and training. They are also taking care of varied tasks including answering queries, identifying and generating images, sounds, and text with accuracy, and also taking care of things like text-to-text, text-to-video, text-to-3D, and digital biology. LLMs are highly flexible while being able to successfully provide deep domain queries along with translating languages, understanding and summarising documents, writing text, and also computing various programs as per experts.  ChatGPT heralded a major shift in LLM usage since it works as a foundation of transformer neural networks and generative AI. It is now disrupting several enterprise applications simultaneously. These models are now combining scalable and easy architectures with AI hardware, customisable systems, frameworks, and automation with AI-based specialised infrastructure, making it possible to deploy and scale up the usage of LLMs throughout several mainstream enterprise and commercial applications via private and public clouds, and also through APIs.  How LLMs are disrupting sectors like healthcare, pharma, BFSI, and more Large language models are increasingly being hailed as massive disruptors throughout multiple sectors. Here are some aspects worth noting in this regard:  Pharma and Life Sciences:  Healthcare:  The impact of ChatGPT and other tools in healthcare becomes even more important when you consider how close to 1/3rd of adults in the U.S. alone, looking for medical advice online for self-diagnosis, with just 50% of them subsequently taking advice from physicians.  BFS:  Insurance:  The future should witness higher LLM adoption throughout varied business sectors. AI will be a never-ending blank canvas on which businesses will function more efficiently and smartly towards future growth and customer satisfaction alike. The practical value and potential of LLMs go far beyond image and text generation. They can be major new-gen disruptors in almost every space.  FAQs What are large language models? Large language models or LLMs are specialised language frameworks that have neural networks with multiple parameters that are trained on vast amounts of unlabelled text with the usage of self-supervised learning.  How are they limited and what are the challenges they encounter? LLMs have to be contextual and relevant to various industries, which necessitates better training. Personal data security risks, inconsistencies in accuracy, limited levels of controllability, and lack of proper training data are limitations and challenges that need to be overcome.  How cost-effective are the Large Language Models? While building an LLM does require sizeable costs, the end-savings for the organisation are considerable, right from saving costs on human resources and functions to automating diverse tasks.  What are some potential ethical concerns surrounding the use of large language models in various industries? Some concerns include data privacy, security, consent management, and so on. At the same time, there are concerns regarding these models replicating several stereotypes and biases since they are trained using vast datasets. This may lead to discriminatory or inaccurate results at times in their language. 

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Embedded Finance

All You Need To Know About Embedded Finance

December 30, 2022

Embedded finance is one of the biggest trends today, indicating a seamless integration of the non-financial and financial services spectrum. It will help in streamlining financial systems and procedures for consumers while enabling superior user experiences simultaneously.  For example, embedded finance may help customers make their purchases and receive credit at one point rather than visiting a banking branch for applying for the credit in question and then make the purchase.  Customer-facing platforms digitally tap into these technologies for integrating financial solutions into their own spectrum of services. What is embedded finance?  Consider a scenario where an e-commerce platform integrates a checkout option for financing purchases or any e-wallet helps people to directly exchange money.  It can even be any other product platform offering insurance services for buyers. There are basically limitless possibilities ahead for embedded finance technology.  What about regulatory aspects?  These are no stumbling block at least for now. The entity which is regulated, i.e. the fintech player or banking institution, will be taking care of these aspects, including licenses, compliance, safety of consumer operations, deposits, and so on.  When financial services are embedded into various transactional platforms, it translates into a win-win for consumers. Embedding adheres to regular operational protocols for working with the help of APIs.  Upon a clear blueprint from product managers, developers solely have to deliver code as per the vision of the UX designer.  This trend will certainly become one of the biggest across the global economy and financial services sector over the next years, particularly for its potential to maximize revenues from every individual customer.  Delving Deeper Into Embedded Finance Here are some operational mechanisms for embedded finance that are worth noting:  Embedded Payments These enable consumers to make their payments with a one-touch mechanism, and also minus any need to shift between apps, enabling faster settlement and checkouts.  Embedded Cards These can temporarily replace debit/credit cards for regular transactions between vendors and users. It enables fund transfers to these cards digitally for purchases, restricted to the value of the funds transferred and this can be activated. These are more secure for consumers and include expense cards, smart cards, corporate cards, and other digital/virtual cards.  Embedded Credit Several platforms can allow consumers to get credit instantly while buying any item, thereby doing away with the need for huge paperwork, applications, separate procedures, and so on.  Embedded Investment Options Platforms may offer a one-stop solution for investing in various avenues and managing the same easily. Multiple financial instruments may be accessed without leaving the one-stop platform in question.  Embedded Insurance Solutions Embedded insurance solutions refer to better integration across platforms, enabling companies to approach and get insurance customers through multifarious trusted platforms.  Embedded Banking Services This refers to the integration of financial solutions with any other brand app or platform via APIs. This may include contactless payment, bank transfers, lending, and more.  Naturally, embedded finance has its fair share of advantages including enhancing the average order value, customer count, lifetime value of a customer, and customer retention figures for digital and other brand platforms, while helping them earn some alternative income via revenue-sharing as well.  These platforms will also get a chance to gather invaluable customer information for insights on buying patterns. Financial institutions benefit from tapping the distribution abilities of these platforms/apps, while gaining access to vital data on borrowers, useful for enabling customized financial offerings for them.  They also benefit from a higher pool of customers while improving lifecycle management of credit and underwriting in turn. This will ultimately enhance their revenues/profit margins as well.  Consumers benefit from more convenience, easier access to almost all major financial solutions, and customized financial offerings, along with better user experience across multiple trusted platforms. Embedded finance thus translates into a viable and beneficial solution for all stakeholders in the process, i.e. the financial institution, the platform, and the end-consumer. It could well become one of the defining trends of not just 2023, but for the coming decade too!  

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How Regtech is beneficial for financial services

How Regtech Can Be Beneficial For Financial Services

November 28, 2022

The Regtech solutions trend has caught on throughout the financial services sector and how! Here’s understanding this phenomenon and what it can do for any financial institution.  What Is Regtech And Why Is It Important?  What is Regtech? If you dig deeper, then you will find how companies are not just emphasizing consumer-facing operational aspects, but also back-end elements. With regulatory pressures on governance and data compliance, Regtech is steadily building a strong use case for itself. More fintech and financial institution partnerships could happen in the near future for leveraging the same.  Regtech compliance tools are the need of the hour for most financial institutions. Regulatory technology has built a firm base in the fintech space for overcoming several hurdles including litigation, regulations, regulatory remediation, and more. A majority of Regtech tools make use of SaaS and open APIs for helping financial institutions solve a multitude of issues, helping manage governance and compliance, while lowering regulatory risks at the same time.  Challenges Faced By Financial Institutions Before venturing into Regtech requirements and other Regtech certification needs at an implementation-level, challenges faced by several financial institutions should be addressed. They face problems like the following:  Issues in risk management.  Consistent addition of new Government regulations.  Modifications and circulars related to existing rules/regulations.  Higher overheads for solution production and deployment with regard to compliance.  Higher penalties for non-compliance.  Legacy system issues and insufficient levels of digitization or automation for tackling these aspects.  Incompatibility or integration issues of systems.  This is where Regtech comes into play as a viable solution for the future.  Advantages – How Regtech Is Helping FIs To Manage Risks Regtech solutions are ensuring the following benefits for financial institutions:  Internal accountability and control for compliance assessments, risk-based data, effective policies, analysis, and management of procedures.  Compliance with regulations- Financial institutions can easily adhere to regulatory needs in a more efficient manner. They cover periodic regulations while ensuring solutions for the same.  Lowering the time required for onboarding customers.  Better fraud identification and adjusting swiftly to newer regulations.  Enhancing data analytics and collection.  Simplification of data management, complying with safety and privacy regulations.  Ensuring suitable access, storage, and processing of data for financial institutions.  More transparent and effective regulatory filings.  Reporting in real-time along with improving decision-making.  New governance implementation and reframing regulations.  Enhanced risk and fraud management- Solutions for risk management ensure automated assessment of credit for understanding optimal limits and also exposure aspects. Collaboration with Regtech solutions will help in generating higher savings on costs and also higher investment returns, in addition to taking care of compliance and regulatory requirements.  Support for risk-data aggregation, taking care of reporting liquidity, data modeling, analyzing scenarios, and stress test forecasting.  Real-time ML/AI based prevention of frauds, real-time tracking of compliance, AML screening in real-time, and more for KYC procedures.  Data standardization with cloud computing, predictive analytics, governance at the board level, provenance audit, and end-to-end regulatory reporting via automation.  These are some segments where Regtech solutions can play a vital role in helping financial institutions shift towards a new era of better governance and regulatory compliance.

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