Over the past few years, banking has far transcended from the typical brick-and-mortar system in more ways than one. With automated systems and digital processes embedded in almost every modern bank’s service offering, it is interesting to observe the many transformations that technologies like AI and Open banking have brought into the industry. Artificial Intelligence (AI) is a technology that encompasses the ability to automate human cognitive processes, including problem-solving, pattern recognition, and speech recognition, with the added benefit of eliminating the possibility of human errors. Open Banking offers the perfect platform for AI to manifest itself in the banking and lending industry.
Since its inception, the system has aimed to encourage competition and lower banking costs for customers. The scope of Open Banking includes the complete account details and transaction history, making it easier for lenders to assess the credibility and evaluate loan applications.
It arrived as the right for customers to manage their wealth better and for bankers to offer more transparency and convenience to their account holders. As of 2018, many popular UK banks such as Barclays, Lloyds, and HSBC gave customers control of their accounts and allowed data sharing with third-party applications. Companies, including lenders, brokers, and advisors, request customers to share this data by partnering with specially regulated technology providers called AISPs. Along with offering ease of banking, Open Banking granted lenders the ultimate platform that encompasses enough data to assess the creditworthiness of a potential borrower and monitor the financial health of a customer. Open Banking also made it easy for lenders to seamlessly reach out to new borrower segments. With Open Banking, it becomes easier for lenders to efficiently evaluate loan applications, use users’ banking history and data that can be used to complete the identity check directly from a user’s bank.
Before Open Banking was formalized, FinTech players such as Mint and Personal capital were trying to democratize the data by combining users' account information from all their financial institutions so they could see it in one place. Mint pioneered the concept of an independent app that would act as a centralized platform to access all the accounts and credit cards of an individual customer. This empowered the customers to manage and understand their finances better and essentially offered them a 360-degree of their finances. Many banks and FinTech companies across the globe have now created platforms of similar nature for bolstering transparency and higher customer satisfaction. Here are a few other exciting examples of players at the intersection of lending and Open Banking:
iwoca: In 2018, European SME lender iwoca released Open Banking for all new customers with a Lloyds Bank account, meaning that business owners can now provide iwoca up to five years of the transaction history.
Saltedge: The company aims to innovate the financial sector and create an open financial marketplace based on APIs. Salt Edge is connected to Open Banking channels, allowing lenders to initiate instant money transfers directly from borrowers’ bank account anywhere within the EU. The Salt Edge Partner Program enables companies to start using PSD2 channels of real-time data from across the EU within 15 minutes. Salt Edge serves by handling all the technical, security, and compliance matters.
Koyo: UK-based Koyo platform provides access to low-interest loans and credit cards for no-file/thin-file customers. It requires all customers to complete an application to offer competitive prices for loans without guarantors. In addition, data sourced through Open Banking allows Koyo to access current information about a potential borrower’s payment history. Koyo recently raised $4.9 million in funding.
Kontomatik: The company helps lenders connect with other banks’ data via Kontomatik API, enabling financial institutions to access customers' banking activity. The API allows companies to benefit from instant KYC, powerful financial data for credit scoring, and all possible sets of transactions to build a precise customer profile through the user’s consent.
This access to data and collaboration between FinTech and lenders is a win-win situation, and it would be myopic to say that incumbents are always at a loss. Some lending specialist FinTech players are helping traditional lenders to serve their customers with enriched data (alt data) and underwriting technology. AdviceRobo is one example where incumbent lenders can benefit from Open Banking. In 2019, AdviceRobo, a Netherlands-based FinTech specializing in psychographic & behavioral credit scoring and credit decision engines, launched an Open Banking capability for lenders. Its API aims to aid lenders in making better use of their data, competing with alt lenders and lending out more cash to underserved consumers. Another such example is the online small-business lender OnDeck offering its underwriting technology to JPMorgan Chase. The bank will use the capability to quickly approve and disburse loans to its own small-business customers.
While we talk about the democratized consumer data from banks that can be used for better lending mechanisms by new lenders, we should also consider the fact that banks are not very good with data around the underserved population. Here, alternative data and AI-powered automation can plug the gaps and make better evaluation engines.
When we talk about consumer lending or even corporate lending, large amounts of data are processed from the time the borrower fills out the application form until he gets access to funds. Many attributes are recorded and analyzed for each customer before a loan can be approved. In banks and financial companies that have not upped their ante in terms of technology, this data is still processed manually to a large extent and is very cumbersome.
Many FinTech companies leverage this data and analyze the borrower’s default probability using complex AI algorithms, which creates the individual’s risk profile, making it easier for lenders to arrive at a decision. A FinTech company making strides in developing its processes based on AI is ZestFinance. It’s one of the leading startups in the United States. The company developed the Zest Automated Machine Learning Platform (ZAML) in 2017, which is a fast and accurate way of identifying good borrowers by considering various traditional and non-traditional variables. Here are some other interesting players that use AI to improve their lending capabilities:
Kreditech: Kreditech, through its proprietary credit decision engine, helps the underbanked population to determine their creditworthiness, thereby enabling them to avail of loans. It provides access to credit for people without any credit history. It leverages artificial intelligence and machine learning to score a customer and determine credit risk by analyzing up to 20,000 data points per application.
Affirm: Affirm is a financial technology services company that offers installment loans to consumers at the point of sale.
Avant: Avant provides a B2C marketplace lending platform that leverages big data and machine-learning algorithms to offer a customized approach to streamlined credit options.
Social Finance (SoFi): SoFi helps graduates of top-tier universities refinance student loans. The company focuses on student loans, mortgages, and personal loans and uses AI-powered algorithms on alternative data to help lenders find patterns that would otherwise be overlooked.
Become: Become (formerly known as Lending Express) is an online marketplace that helps SMEs get the best loan deals through their lending partner's network. The platform uses algorithms to analyze the businesses and inspect data from various sources to calculate the LendingScore. This helps businesses learn the funding essentials to improve the step-by-step program outlined and get new funding opportunities.
To sum it up, we can say that as Open Banking expands, there'll be information sharing between banks and non-banks, which is poised to deliver a significant impact on lending. The key enablers will be open banking applications and companies that bring lenders and borrowers on the same platform. In addition, AI algorithms for evaluating borrower creditworthiness and managing risks reduce NPAs while making loans accessible for underserved segments. Apart from making the risk profiling process smoother and more accurate, some of the tangible benefits that lenders can leverage on by implementing AI include lower write-offs, lower underwriting & servicing costs, elimination of credit losses & fraudulent borrowers, and one of the most significant achievements for the service industry – higher customer satisfaction.
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