After a somewhat shaky period following the Global Recession, the leasing and lending industry is once again showing sustained signs of recovery. Surveys from the ELFA (US Equipment Leasing and Finance Association) show that industry insiders are forecasting sustained growth in financing volume over the next few years as the effects of the economic recovery begin to take hold. Similar data from Leaseurope reveals that business volumes increased by 9.6% over 2017, continuing the sustained growth that has been visible across several local leasing markets for the past couple of years. Of course, Asia and in particular China remains a key driver for overall industry growth, the region already represents the third largest leasing market in the world at an estimated $200 billion, and leasing is only set to become more critical in these economies as more SMEs gain access to asset financing products.
These gains were largely attributed to the emergence of new operating models and technologies that have made leasing a far more attractive option for customers. The move towards digital transformation is long overdue. While stricter capital requirements and stringent credit assessment policies have made lenders far more risk-averse, their reluctance to innovate and expand their service offerings has proven to be a critical limiting factor in a rapidly evolving operating environment.
Factors Driving Disruption within the Asset Finance and Leasing Industry
Rising Customer Expectations
Disruptive new age technology companies, steered by millennials' in response to markedly evolved consumer expectations have managed to create personalized and intuitive user experiences that translate consistently across multiple digital channels. Today, both commercial and retail clients demand this same level of service from lending institutions. Unfortunately, few financial service providers are currently set up to provide a truly integrated customer journey. Most of these organizations lend through multiple specialized channels, each with their own systems and processes, therefore it is much harder to consolidate this disparate infrastructure into one platform.
Deutsch Bank is a prime example of this lack of agility. Back in 2015, incoming CEO John Cryan described the organization's IT infrastructure as really, really bad. At the time, the bank was operating upwards of 40 operating systems across different functions, each having its own unique functionalities. Some of these systems were running on legacy hardware that had not been updated in years, while others used platform-specific software that could not be implemented across other locations. The result was a disintegrated digital ecosystem with almost no reporting between teams. Since then, the bank has closed down operations in 10 locations, halved their client list and moved towards the wholesale consolidation of their technology.
Today, they have less than 30 different operating systems in place, and the number of shutdowns and critical failures across their IT environment has decreased significantly. This sort of top-down commitment is absolutely necessary if digital transformations are to be successful.
A number of lending institutions have turned to mergers and acquisitions as a key driver for business growth. Data from Deloitte's 2018 M&A report shows that 62% of business continuity managers in the financial services sector are pursuing these deals in an effort to transform their portfolios to handle emerging technologies. Specific target areas include payment platforms and consumer lending where customer acquisition costs have increased significantly over the past couple of years.
Although these moves might help to expand an organization's capability, they also introduce additional complexities to already laborious backend processes. A scattered digital infrastructure encourages functional managers to trust only their systems while ignoring the value that could be gained from other sources of data. The obvious result is inefficiency, inflexibility and an endemic lack of transparency within the business. While sales teams might rely solely on quarterly sales figures for their strategic planning, the manufacturing team may still be relying on last year's consolidated numbers for their own production forecasts. As a result, only 20% of modern asset financing providers exceed industry standards for productivity and cost-effectiveness.
Credit risk analysis is particularly prone to inefficiency. Although many lenders now employ software that can speed up statistical evaluations for credit assessments, many of these processes are still time-consuming and labor intensive. As this is a core function for any lending institution, the impact on profitability is significant. Data analytics platforms can be a key vector through which these inefficiencies can be resolved.
These widespread inefficiencies coincided with the arrival of FinTech startups in a variety of areas that were previously dominated by traditional lenders. Over the past few years we have seen a wide variety of operating models emerge in this space, including:
- Digital Lenders - Everything from the loan application to the credit assessment and final approval is handled through an online platform with no human intervention required. Certain companies have managed to empower millions of new businesses across the developing world with these capabilities.
- P2P Lending Platforms - These digital service providers design specific lending products and perform initial credit assessments for prospective borrowers. They then connect these businesses to lenders that are willing to finance capital acquisitions and other objectives. Traditional lenders also use these platforms to source and acquire new customers.
- Supply Chain Lenders - These companies will provide short-term financing for inventory or asset purchases from specific distributors.
FinTechs have helped to reshape the financing and leasing landscape through their focus on data analytics, customer engagement and convenient services. Currently, online lenders enjoy a relatively benign regulatory environment with minimal barriers to entry in place. This means that they can employ more relaxed credit assessment systems while offering a wider array of financing products. While new compliance measures are being brought into place to account for the inherent risks of online lending, these policies will take some time to implement. Meanwhile the added competition has compelled traditional lenders to tighten operating margins and introduce more innovation to their operating models.
The Growth of Commercial Lending
Commercial lending products have overtaken residential mortgages as the biggest source of revenue for financial service providers. In total, these products represent 21% of bank distributed financing. While lenders are keen to take advantage of this opportunity, there are a number of challenges present.
- A large portion of commercial borrowers are SMEs that are attempting to grow their technical capabilities and logistics systems to maintain their global competitiveness. According to a Siemens report, more than 60% of these companies are either currently availing or seeking financing through alternative funding options such as asset financing.
- It is often difficult to analyze the creditworthiness of SMEs due to the lack of relevant documentation and the sheer diversity of their operating models and products. As a result, assessments generally require direct intervention from subject matter experts and risk assessment teams at various stages in the approvals process.
- Commercial lending products can quickly become complex. Sophisticated technology is generally required to administer and manage these financing arrangements.,
- Business customers are seeking the same flexibility, simplicity and mobility as retail customers. They are not prepared to navigate through complex software to get the services they need.
In order to address these concerns, lenders must implement loan administration and management solutions that allow better oversight and risk assessment across complex commercial portfolios. An effective implementation should offer end-to-end visibility of multiple business lines and lending structures from loan origination to periodic reporting.
In terms of frontend systems, the focus should be on developing a streamlined digital lending experience that allows for online applications, quick credit assessments and efficient processing at each stage of the lending process. These steps towards automation should reduce the cost of lower value SME leases, and help make these financing arrangements profitable for lessors.
Key Technologies in Digital Transformation
While many lessors have taken ambitious steps to automate their backend accounting and administration, their loan origination (credit assessment, documentation, underwriting and payments) is often still conducted through less-than efficient legacy architecture. The lack of a consistent frontend system can lead to inaccuracies, fraud, oversights and inefficiencies across the loan origination process. Cloud technology can be a critical enabler in this regard.
Finance and leasing providers that have shied away from automating their frontend due to the scale of investment required can benefit from the ease and cost-efficiency of cloud migration. These lending solutions are housed in off-site data centers that are maintained by dedicated service providers. In most cases, implementation simply means synching your existing systems to remotely hosted platforms through a web interface.
In a cloud implementation, disparate functional systems are broken down and consolidated into a unified platform. This integrated architecture should give key decision-makers in every area a true end-to-end perspective on their processes, which in turn helps to align functional objectives with overall corporate objectives, and introduce more effective collaboration between different departments. Lending institutions should also become far more flexible, as disruptions in one area will be visible to every manager.
Once loan origination has been moved to the cloud, lenders can benefit from a variety of built-in features that help to streamline costs, improve end-to-end process visibility and provide more operational flexibility.
- Automated credit scorecards based on the type of financing product sought, the collateral offered, and corroborating information provided. Based on these metrics, each prospective lessee can be sorted into a suitable category.
- Automated systems also provide inbuilt tools that help users to analyze the lessee's financial statements for potential vulnerability.
- Leasing solutions can also be adjusted to reflect the accounting conventions of different countries, so multinational companies can be evaluated according to their specific operating environment.
- Further functionalities may include asset tracking, debt schedules, weekly/monthly reporting, contract restructuring options, and debt schedules.
Cloud technology can help companies consolidate and organize their data, but in order to extract real value from this information further technical capabilities are required. For years, the banking industry has relied on data analytics to drive their customer engagement and risk assessment strategies, this technology can bring similar advantages to the leasing sector.
Analytics platforms go through a vast volume of current, historical, and real-time data drawn from a variety of sources across the enterprise. These data points are processed through tailored algorithms that are used to identify relevant patterns in these inputs. Identified patterns can help to drive a more in-depth understanding of lending processes, markets, customer channels, and specific financing products.
Predictive analytics takes these insights and runs them through simulated models that can be used to determine how a particular pattern will affect future operating conditions, or how changes to key factors will impact current figures (i.e changes in GDP versus lease volume). The right insights will augment strategic decision making, by helping lessors to target and leverage future opportunities while mitigating developing risks to their business.
Analytics can be deployed in some key areas including:
- Fraud Detection-Analytics platforms can be used to examine a wide variety of incongruent data from both internal (claims processing and policy databases) and external (social media, financial reports, trade publications, police reports) sources to identify potential inaccuracies or outright fabrications during the application stage.
- Credit Scoring-Predictive analytics can be used to extrapolate the default risk of advancing financing to a particular client. This determination is made on the basis of a comprehensive assessment that covers millions of relevant data points derived from internal and external sources.
- Personalization-Analytics allows lessors to draw user-specific data from across the customer journey. This information can provide an understanding of the customer's financing requirements and spending patterns. With the right insights, sales teams can proactively deliver tailored product recommendations and cross-sell relevant services that match up to the customer's needs.
- Internal Auditing - When applied to internal records and documentation, Analytics can help to ensure compliance with industry regulations. This will help to reduce the risk of fines and penalties, and the related cost savings can be passed down to the customer.
Digital Transaction Management
Once a company decides to expand its digital footprint, it can begin to free itself from the constraints of its physical location and connect with customers across the world with ease. Until recently, one of the biggest physical constraints for financing and leasing providers was the use of manual documentation and signatures. In this case, ensuring the accurate completion of paperwork meant either: visiting a customer in-person, or engaging in a time-consuming back and forth over fax and email.
A digital transaction management system (DTM) based on e-signature technology can help to reduce these obstacles and create a far more convenient lease processing system. E-signatures allow people to sign important documents from anywhere in the world.This not only increases the consumer base of a company, but also helps accelerate its development. As a result of the increased scale of customers, a company now sees results much faster.
DTM systems add additional process controls to the leasing process. For example, lessors can ensure that lessees are unable to move to the next page of a contract before completing all previous signatures. If the contract needs to be passed down to other stakeholders, then specific privileges can be implemented which restrict the sharing, viewing or duplication of documents.
Artificial Intelligence (AI) and Robotic Process Automation (RPA)
AI, in particular UI based Machine Learning (ML) is being broadly and increasingly employed in the finance domain as it lends itself well for lower value, repetitive tasks such as responding to non-critical data queries. This also makes for significantly improved accuracy as the machine learns and automates responses. Additionally, invaluable human intellect is better utilized due to the advent of these tools as it is freed up to be engage with more critical and impactful decision making which AI can't imitate yet. Lenders can use AI ML and RPA to sift through credit applications at unprecedented speeds to weed out unfavorable applications and forward promising ones to senior analysts for approvals. This man and machine grouping can increase productivity and the quality of decision making exponentially, giving finance companies a competitive advantage.
The Future of Asset Finance and Leasing
The disruptions that are shaping the financial services sector today show no signs of abating. If lenders are to remain competitive amidst this period of restructuring then they must be able to identify the emerging technologies and market trends that will be in use a decade from now. This sort of visionary focus requires more than just digital adoption; it means a fundamental transformation of your core business.
Operating models must be redesigned to ensure that the right capabilities are in place and they are properly aligned to deliver optimal outcomes across the enterprise. At the same time, C-suite leaders must work to foster a culture of innovation and continuous improvement amongst their workforces, because a true digital transformation will need to be supported by talented individuals who can properly leverage the new technologies at their disposal. By working to create these changes today, you can ensure that your organization is equipped to deal with the disruptions of the future.
Written by Fawad Ghauri, Head of Digital Transformation
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