November 2022 Summaries

Plaid is announcing Plaid Signal, a machine learning risk engine that allows businesses to accelerate payments to near-instant experiences while reducing risk to their bottom line. This technology has been in use by several Plaid customers for over a year and currently protects nearly $1.5 billion in transactions every month. With Plaid Signal, businesses can enhance their risk program to deliver great customer experiences by analyzing over 1,000+ unique risk factors and returning risk scores, tiers, and attributes for improved automation and faster ACH transactions. By implementing Signal, companies have seen significant improvements in reducing return losses, increasing conversion rates, and enhancing user engagement. Plaid Signal is built on the company's leading consumer-permissioned Open Banking platform, enabling more precise and dynamic payment flows through predictive scores, tiers, and unique attributes that explain the 'why' behind each score.

The future of bank payments is rapidly evolving with a focus on making account-to-account money movement safer, smarter, and faster. Plaid is at the forefront of this transformation through its network of payment partners and innovative APIs that power nearly a billion ACH-based transfers every year. The company aims to accelerate the adoption of emerging bank payment rails such as RTP and FedNow, which will unlock broader innovation in the industry and provide consumers with more attractive options for merchants and customers. With major investments in safety and security technologies like Plaid Signal, Plaid is working to mitigate risk and fraud while improving the consumer experience through better user interfaces and seamless integration with multiple apps and services.

VRPs, or Variable Recurring Payments, are a type of payment mechanism that offers consumers more control and security compared to direct debits and card payments. They allow consumers to approve transactions that vary in amount month-to-month within specific parameters controlled by the consumer. VRPs have several benefits, including lower risk for consumers compared to direct debits and recurring card payments, which can be vulnerable to fraud, data breaches, and failed payments. The proposed principles for driving VRP adoption include capping CVRP issuer fees, creating a thin rulebook for VRPs that is enforced by an industry-agreed entity, and adopting a push payment framework rather than a pull payment mechanism, as direct debits and recurring card payments require consumers to hand over sensitive financial information. These principles aim to address outstanding questions around dispute resolution, payment security, and certainty, as well as the cost efficiency of VRPs relative to other payment methods.

Interoperability in API data connectivity is crucial for secure and reliable sharing of financial information among various partners, including large banks, regional banks, fintechs, and digital banking platforms. An interoperable API data standard allows data partners to build a single connection to all partner endpoints, resulting in faster implementation, fewer resources needed, and better user experience. This is particularly beneficial for smaller institutions with limited resources. Interoperability also benefits consumers by providing data transparency and control, instant access to financial tools, enhanced data security, privacy, and transparency. By delivering reliable API connectivity, data partners can build and retain customer trust, reducing customer support costs and improving the bottom line. The Financial Data Exchange (FDX) is working towards aligning the industry around a common interoperable API data standard, with Plaid contributing technical expertise to its development.

A changing economic landscape, marked by surging inflation and rising interest rates, is presenting opportunities for lenders to adapt and evolve. With historically high origination volumes in 2021 followed by a decline in mortgage demand, lenders are facing a more competitive market that requires them to focus on building compelling consumer experiences and improving backend processes. To navigate this environment, lenders need to effectively evaluate credit worthiness, expand credit to more customers, understand multiple income sources for single applicants, manage evolving risk, reduce fraud, and drive operational efficiency through automation. With the right tools, such as Plaid's Assets and Income solution, lenders can gain visibility into a borrower's entire credit portfolio, identify common types of primary and secondary outflows and inflows, and optimize repayment timing to minimize NSFs and delinquency risk profiles. By automating repetitive tasks and leveraging technology, lenders can save up to $70 billion by 2025 and implement time-saving and best-in-class operations.

Acre Homes, a new model of home ownership, uses Plaid's suite of credit products to unlock buyer insights and deliver a seamless customer approval application experience. Acre leverages Plaid's best-in-class conversion practices while gaining deeper insights into potential home buyers to make more informed decisions. With Plaid, Acre can build a streamlined process compared to traditional mortgage processes, which often have lengthy checklists of 80 items or more. This allows for faster completion rates and quicker approval times, with some approvals being completed within 24 hours. Acre's product is designed for individuals who want to own a home but may not qualify for a traditional mortgage due to income fluctuations or other factors. Plaid provides data that helps Acre make decisions in the context of home ownership fit, while also offering lenders more competitive offers and differentiating themselves through lower interest rates and larger loans. As Acre scales, they are adopting new Plaid products like Plaid Income and Credit Categories, which expands their core assets data set and streamlines insights for lenders. Ultimately, Plaid aims to be a one-stop shop for lenders, providing the data necessary to make informed decisions and supplement traditional credit models.