Smile API

How Smile API uses employment data to further financial inclusion efforts Created with financial inclusion in mind, how does Smile API's technology help with the overall cause for financial inclusion in the Philippines? As of July 2024, the Philippines' overall Credit Perception Index (CPI) score is at 69, improving by four points from last year. The latest CPI also shows that more Filipinos now hold credit cards and personal loans. This shows how much growth has happened when it comes to the accessibility of credit in the Philippines. With more financial and lending institutions tapping into the potential of alternative data sources, credit services has become more widespread in the country. Through the use of alternative data sources like employment data, credit risk managers are able to determine one's credibility despite not having a bank account. Financial institutions, lenders, and employers should consider integrating Smile API's technology into their systems to improve decision-making processes, reduce risks, and expand services to underserved populations. #SmileAPI #FinTech #FintechNews #latestFintech

We are stoked to be here at AsiaWorld-Expo in Hong Kong for Hong Kong Fintech Week! 🎉 Join us and don't forget to drop by and visit our booth! 🤩 #SmileAPI #FinTech #FintechNews #latestFintech

How Smile API Supports local BNPL providers BNPL is rapidly changing the way people shop and, and it's expected to grow as years pass by. How does employment data help these companies? In the Philippines, Buy Now Pay Later (BNPL) has been a popular option for shopping, expanding 9.6 times since 2018. In other Southeast Asian countries like SIngapore, the BNPL user base has increased by 7.1 times with an average monthly growth rate of 2.8%, reflecting a strong consumer shift towards flexible payment solutions. Due to easy access, seamless network coverage, consumer preferences, and cost-effectiveness compared to traditional credit options, BNPL has been a lucrative payment option for a lot of Filipinos. Its fast approvals, cost-effectiveness and coverage can also be alluded to the coverage brought not just by traditional credit models, but alternative data sources as well. This is why fintech companies should consider partnering with employment verification solutions to improve their services and user experience, similar to the partnership between Smile API and BillEase. With quicker approvals, there is a smoother financial journey for customers. #SmileAPI #FinTech #FintechNews #latestFintech

Real-time employment data and how it can supplement your current credit scoring system Alternative data sources are becoming increasingly important for making loan approvals, due to how it offers a more holistic view of an applicant and its ability to expand lending opportunities. How does employment data help supplement credit scoring systems as an alternative data source? In the Philippines, about 76% of the population is unbanked. Although that is the case, a lot of the population use credit services like Buy Now, Pay Later (BNPLs), which proves the capability of Filipinos to use and understand credit. This is also a huge challenge for banks and lending institutions to extend their services to an underserved population and make bank access easy for them. Because of this, alternative credit scoring has to be more resourceful in using other data points in order to determine one's creditworthiness. By adopting alternative data sources into the current credit scoring system, lenders can expand their customer base and borrower data point, and reduce the costs of issuing credit with bias and errors. Smile API, through automation and AI, gives companies access to employment data fast and easy, primed to be used as an alternative data source for loan applications. Learn more about Smile API 👉 https://zurl.co/4wpB #SmileAPI #FinTech #FintechNews #latestFintech

Attention! 📣 Smile API is heading to Hong Kong Fintech Week! Join us from October 28 to November 1 at the AsiaWorld-Expo in Hong Kong as we jump into everything fintech you can think of! This is your chance to discover how Smile is changing the way companies access real-time, user-consented employment data. Don’t miss out and see you there!🚀 #HKFTW2024 #SmileAPI #Fintech #FintechNews #latestFintech

Improving risk assessment for lending institutions Access to real-time employment information can improve credit risk assessment and business growth, especially for banks and lenders to minimize risks while maximizing profits and productivity. Starting from 2021, there has been a 34% increase in gross consumer lending, which is a testament to the demand for loans. Despite this, there are still numerous factors that could affect loan risk, which is why verification has to be faster and efficient. Real-time employment data provides a quick and accurate method of verifying an individual's income, potentially approving customers who might have been refused credit due to limited credit history or being unbanked. With the use of employment data, the unbanked population has a chance to have their loans approved due to the existence of employment data. Smile API provides its client with user-consented, up-to-date information on employment history that helps banks and lending institutions reach more people, thanks to the use of employment data for loan application approvals.

Using AI in Handling Personal Data: A Drawback? AI has been slowly integrated in numerous businesses due to how convenient it is for business operations, but when dealing with personal data, is it a wise choice to trust AI? Although frequently used in business operations, there are still some reservations on the use of AI. According to surveys, 29% are concerned with the ethical and legal concerns that come with AI, while 34% said security concerns are holding them back from using AI. When considering the use of AI to help automate your lending process, it's important to make sure that you protect and maintain a large user control on the data you have, These are just one of the few measures you can practice in order to mitigate security and privacy risks when it comes to AI. Smile API incorporates the use of automation and AI to verify the latest employment data easily, all while making sure they comply with local security and data regulations when it comes to data handling. Smile API also makes sure all the data they used is user-consented and secure. #SmileAPI #FinTech #FintechNews #latestFintech

Reducing Operational Cost and Manual Work in Lending The ever-growing lending industry has continued to flourish even during the pandemic. As more things go digital and automated, how should lending companies start automating their processes and avoid high operational costs from manual work? To start, businesses should learn to embrace technology, looking into areas in the loan approval process which can be easily automated to avoid long wait times and manual work. Another factor that can be considered is making remote work an option in order to avoid managing a physical office. As most verification processes will be done on computers, this can be considered as another way of reducing costs for upkeep that the company might be spending more on. Along with these, verifying an applicant's data can also be automated. By doing so, the other parts of the loan application process can also be streamlined to be automated. By going with a more digital approach, companies are able to take their data driven decision-making a bit further due to faster processes. Smile API verifies the recency and accuracy of one's employment data, which can be used by credit risk managers to determine their creditworthiness and approve loans faster than ever, thanks to the help of automation and AI. #SmileAPI #FinTech #FintechNews #latestFintech

Inconsistency and Inaccuracy in Data: How It Affects Lending Businesses In a data-driven industry, where data always has to be new and fresh, lending companies should be aware just how a simple mishap can affect their operations. Globally, around 3% of data decays each month. This means that any slight data changes can skew into other directions that you might not anticipate. In this case, a three-month old data regarding a person's government contributions may not be a reliable way to gauge someone's ability to pay their dues. The possibility of bad data affecting your decisions on loan approvals is not something that can be ignored, as the lack of proper screening can lead to company losses. Lending companies should aim to approve loan applicants who are guaranteed to have the ability to pay back their loans in a timely manner. Smile API is able to verify employment information, which can be used to determine one's creditworthiness due to their ability to earn money and pay for their applied loan. With Smile Checks, credit risk managers can decide which loan applications to approve in no time. #SmileAPI #FinTech #FintechNews #latestFintech

Reliance on Manual Loan Approval Processes Nowadays, manual loan processes are still prevalent to assure software errors do not affect business operations. However, technology has progressed far enough and overreliance on the manual process is no longer needed. Managing multiple loan applications is one of the bottlenecks of traditional loan approvals. As traditional loan processes are usually paper-based and labor-intensive, this entails the manual review and verification of documents, which makes it prone to human error. In order to reduce these errors, a streamlining tool that can quickly assess the validity and recency of data has to be used. By adding this tool to the usual work process, manual work is lessened and the company saves time and additional administrative costs. Smile API not only provides employment data for businesses to assess one' credibility, but it also makes sure to have access to the latest, user-consented data, helping streamline the manual loan processes in place. #SmileAPI #FinTech #FintechNews #latestFintech