Use Cases, Best Practices For Working With Fintechs

Bank leadership teams often come under pressure to quickly establish new fintech relationships in response to current market and competitive trends.

The rewards of these increasingly popular collaborations can be substantial, but so can the associated risks. To balance these risks and rewards, bank boards and senior executives should understand the typical use-case scenarios that make such collaborations appealing, as well as the critical success factors that make them work.

Like any partnership, a successful bank-fintech collaboration begins with recognizing that each partner has something the other needs. For fintechs, that “something” is generally access to payment rails and the broader financial system — and in some cases, direct funding and access to a bank’s customer base. For banks, such partnerships can make it possible to implement advanced technological capabilities that would be impractical or cost-prohibitive to develop internally.

At a high level, bank-fintech partnerships generally fall into two broad categories:

1. Customer-facing collaborations. Among the more common use cases in this category are new digital interfaces, such as banking-as-a-service platforms and targeted online offerings such as deposit services, lending or credit products, and personal and commercial financial management tools.

In some collaborations, banks install software developed by fintech to automate or otherwise enhance their interactions with customers. In others, banks allow fintech partners to interact directly with bank customers using their own brand to provide specialized services such as payment processing or peer-to-peer transactions. In all such relationships, banks must be alert to the heightened third-party risks — including reputational risk — that result when a fintech partner is perceived as an extension of the bank. The bank also maintains ultimate accountability for consumer protection, financial crimes compliance and other similar issues that could expose it to significant harm.

2. Infrastructure and operational collaborations. In these partnerships, banks work with fintechs to streamline internal processes, enhance regulatory monitoring or compliance systems, or develop other technical infrastructure to upgrade core platforms or support systems such as customer onboarding tools. In addition to improving operational efficiency and accuracy, such partnerships also can enable banks to expand their product offerings and improve the customer experience.

Although each situation is unique, successful bank-fintech partnerships generally share some important attributes, including:

  • Strategic and cultural alignment. Each organization enters the collaboration for its own reasons, but the partnership’s business plan must support both parties’ strategic objectives. It’s necessary that both parties have a compatible cultural fit and complementary views of how the collaboration will create value and produce positive customer outcomes. They must clearly define the roles and contributions and be willing to engage in significant transparency and data sharing on compatible technology platforms.
  • Operational capacity, resilience and compatibility. Both parties’ back-office systems must have sufficient capacity to handle the increased data capture and data processing demands they will face. Bank systems typically incorporate strict controls; fintech processes often are more flexible. This disparity can present additional risks to the bank, particularly in high-volume transactions. Common shortcomings include inadequate capacity to handle customer inquiries, disputes, error resolution and complaints. As a leading bank’s chief operating officer noted at a recent Bank Director FinXTech event, improper handling of Regulation E errors in a banking-as-a-service relationship is one of the quickest ways to put a bank’s charter at risk.
  • Integrated risk management and compliance. Although the chartered bank in a bank-fintech partnership inevitably carries the larger share of the regulatory compliance risk, both organizations should be deliberate in embedding risk management and compliance considerations into their new workflows and processes. A centralized governance, risk, and compliance platform can be of immense value in this effort. Banks should be particularly vigilant regarding information security, data privacy, consumer protection, financial crimes compliance and dispute or complaints management.

Proceed Cautiously
Banks should guard against rushing into bank-fintech relationships merely to pursue the newest trend or product offering. Rather, boards and senior executives should require that any relationship begins with a clear definition of the specific issues the partnership will address or the strategic objective it will achieve. In addition, as regulators outlined in recent guidance regarding bank and fintech partnerships, the proposed collaboration should be subject to the full range of due diligence controls that would apply to any third-party relationship.

Successful fintech collaborations can help banks expand their product offerings in support of long-term growth objectives and meet customers’ growing expectations for innovative and responsive new services.

Data Considerations for Successful Deal Integration

Bank M&A activity is heating up in 2021; already, a number of banks have announced deals this year. Is your bank considering a combination with another institution?

Banks initiate mergers because of synergies between institutions, and to achieve economies of scale along with anticipated cost savings. Acquiring institutions typically intend to leverage the newly acquired customer base, but this can be difficult to execute upon without a data strategy.

Whether your bank is considering are buying or selling, it has never been more important to evaluate whether your data house is in order. Unresolved acquisition data challenges can result in poor customer experiences, inaccurate reporting and significant inefficiency after the merger closes. What causes these types of data challenges?

  • Both institutions possess massive volumes of data and multiple systems, while disparate systems prevent a holistic view of the combined entity. In a merger, the acquirer does not have access to the target’s data until legal close, and data is not consolidated until the core conversion is completed.
  • Systems are often antiquated, and it is difficult to access high-value customer data. Data integrity is often an issue that impedes anticipated synergies that could promote revenue generation.
  • Absence of enterprise knowledge or insight into target’s customer portfolio. This makes it difficult to identify growth opportunities and plan the strategy for the combined institution. It also creates a barrier to pivoting in the event a key relationship manager leaves the institution.

Baltimore-based Howard Bancorp has conducted five successful acquisitions in the last eight years. Steven Poynot, Howard’s CIO, recommends looking internally first and getting your house in order prior to any merger. “If you don’t understand all of the pieces of your bank’s data and portfolio well, how are you going to overlay your information in combination with the other bank’s data for reporting?”

Five solutions to merger data challenges include:

  • Create a data governance strategy before a deal is in the works. Identify the source and location of all pertinent data. Evaluate whether customer data is clean and up to date. Stale customer information such as old land line phone numbers and inaccurate email addresses yield roadblocks for relationship managers attempting to use data effectively. If your bank does identify data issues, implement a clean-up project based on a data governance policy framework. This initiative will benefit all banks, not just those looking to merge.
  • Develop an M&A integration plan that sets expectations and goals. Involve the CIO quickly and identify tools needed for the integration. Make a strategic determination of what data fields need to be integrated for reporting purposes. Acquire tools to allow for enterprise reporting and to highlight sales opportunities. Partner with vendors who understand the specific challenges of the banking industry.
  • Unify Disparate Systems. Prioritize data integration with a seamless transition for customers as the top priority. Plan for mapping and consolidating data along with reporting for the combined institution. Take product and data mapping beyond what is needed for the system mapping required for core integration. Use the information gleaned from the data to support product analytics, risk assessment, business development and cross selling strategies. The goal is to combine and integrate systems quickly to leverage the data as an asset.
  • Discourage Data Silos. Make data available and easily accessible to all who need it to do their jobs. Banking is a relationship business, and relationship managers need current customer relationship information readily available to them.
  • Analyze. Once the data has been consolidated, analyze and leverage it to identify opportunities that will drive revenue.

In a merger, the sooner that data is combined, the earlier decisions can be made from the information. As data silos are removed and data becomes easily accessible across the organization, data becomes an enterprise-wide asset that can be used effectively in the bank’s strategy.