Adiante Recebíveis gains agility, flexibility and efficiency in risk decisioning with Provenir’s AI Solution
Adiante Recebíveis gains agility, flexibility and efficiency in risk decisioning with Provenir’s AI Solution
to loans.
How did Provenir begin, and what’s next for us? Our Chief Product Officer, Carol Hamilton, sat down with Qorus for a chat on what led to the creation of Provenir’s AI-powered risk decisioning platform, how we’ve evolved, and where we’re headed next. Read on for more info on how we’re expanding our capabilities in decision intelligence and how we’re helping financial services providers not only react to risks and opportunities, but better predict them.
Recent elections around the world have already triggered significant economic shifts, with far-reaching implications. In the UK General Elections in 2024, results have further shaped the ongoing Brexit process, influencing fiscal policies and regulatory frameworks that directly impact the financial industry. Uncertainty surrounding post-Brexit trade deals and regulatory realignment has already affected interest rates and inflation, creating tighter credit conditions for both consumers and businesses. And adjustments to the Bank of England’s interest rate policies or regulations governing financial institutions could further influence lending practices, with tighter borrowing conditions on the horizon for both individuals and small businesses.
In Argentina’s 2023 Presidential Election, a shift in leadership has brought about changes in economic strategy, particularly in the battle against soaring inflation. The new government’s attempts to control inflation and stabilize the economy are affecting the country’s monetary policy, leading to higher interest rates and tighter lending criteria. For financial institutions, this poses significant challenges, requiring lenders to quickly adjust their credit decisioning processes to accommodate economic instability. As inflation persists and the cost of borrowing rises, both consumer credit and business financing have become more difficult to secure, which further strains the economy.
The India General Elections earlier this year have also had effects on the fintech space. The results will influence regulatory policies surrounding fintech growth and digital finance, both of which are necessary for encouraging financial inclusion in underserved markets. Depending on the government’s support for these sectors, lending to traditionally underserved segments of the population could see either significant growth or stagnation. And changes in policy around digital finance could encourage new forms of lending, but they could also introduce more stringent regulations that will make access to credit much more challenging.
Of course top of mind these days, regardless of your location, is the upcoming US Presidential election. While it’s always something that has far-reaching effects, this year’s highly contentious ballot is poised to have sweeping global implications, on everything from global interest rates and inflation trends, to significant policy reforms on taxation, regulation, and lending practices. A key player in this process is the Federal Reserve, which closely monitors election outcomes and adjusts interest rates accordingly. If the newly-elected government pushes for changes in fiscal measures, the Federal Reserve’s response could shape borrowing costs, which in turn improves or challenges access to credit. For lenders and financial services providers, these shifts showcase how important it is to remain agile in the face of uncertain regulatory reforms and fluctuating market conditions. The global financial system will be watching closely as the election unfolds – because no matter who wins, there is bound to be significant changes that will reshape lending dynamics in the US and beyond.
Election outcomes can cause shifts in all sectors of the economy, but some areas in particular directly impact lending and risk decisioning. One of the most immediate effects is on interest rates, which are often adjusted based on fiscal policies introduced post-election. As interest rates fluctuate, lenders have to reassess risk profiles and adjust their credit and risk decisioning processes to account for any potential volatility in repayment abilities of their customers. Inflation control is also directly linked to post-election economic strategies. Any policies that either stimulate or dampen the economy can lead to varying levels of inflation – which affects everything from consumer purchasing power and household debt to business investments and the stock market. Inflation can also erode creditworthiness, with rising prices and an increased cost of living making it harder for both individuals and companies to manage their debt obligations. This means that lenders are then faced with the challenge of adjusting lending practices to maintain profitability while managing increasing risks in their customer base (which requires systems and solutions that enable flexibility in decisioning processes).
The outcome of any election also influences overall creditworthiness as economic conditions shift in response. Changes in the employment rate, business investments, interest rates, and fiscal stability all contribute to changes in credit and risk profiles. This is where a more dynamic approach to risk assessment is critical, with the ability to leverage intelligent, proactive risk decisioning solutions. Using advanced decisioning technology and data analytics allows financial services providers to adapt easily, identifying risks earlier and making more informed decisions. This proactive approach enables lenders to protect their profitability and lending portfolios while still serving the needs of customers effectively.
With elections comes uncertainty. And when there’s uncertainty, financial services providers need to proactively navigate shifting risk. Advanced risk decisioning solutions play a key role in helping you better predict (and respond to) risk, by leveraging real-time data and AI-driven analytics to identify emerging trends earlier and make smarter, faster risk decisions. Rather than simply reacting to sudden market fluctuations, proactive decisioning allows you to better predict future scenarios, preparing for possible fluctuations in interest rates, inflation, credit conditions, ability to repay, etc. Remaining agile and competitive is key to staying ahead of any uncertainty in the economy – election-driven or otherwise.
Holistic risk decisioning solutions also ensure a smoother onboarding process, with the ability to more accurately assess creditworthiness, even among rapidly changing market conditions. AI-powered decisioning software and solutions allows you to access and integrate vast amounts of data (everything from economic indicators and market trends to individual financial behavior), giving you a more accurate (and nuanced) view of a customer’s unique risk profile. Too often when economic conditions are volatile, the inclination is to be overly cautious. But that can stifle your business growth. With more proactive, agile decisioning, your lending portfolio remains stable (and profitable) even when external conditions aren’t.
Fraud prevention also becomes a key focus. During periods of political and economic uncertainty, fraud attempts often surge. With a holistic, data-driven approach to your risk decisioning, advanced algorithms and embedded intelligence can better detect unusual patterns and behaviors that signal fraudulent activity. Integrating fraud detection directly into the risk decisioning process allows you to greatly reduce losses, ensuring your operations remain secure, compliant, and resilient even among the unpredictability of major election upheaval.
Beyond onboarding, there is also the issue of managing ongoing customer relationships and maximizing value across the lifecycle. Ongoing account management is particularly important during periods of economic uncertainty. Advanced risk decisioning solutions empowers you to continuously, proactively monitor customer profiles and make adjustments easily. A flexible solution allows you to adjust credit limits and lending terms in real time as economic factors like inflation, interest rates, and consumer behavior evolve. Using AI-driven tools to track changes in individuals as well as broader market trends allows you to proactively mitigate risk, reducing the likelihood of defaults while maintaining a positive customer experience through personalized, flexible financial products and services.
Despite proactive, agile efforts to effectively manage your risk, post-election downturns are common, leading to increases in default rates and placing added pressure on collections and recovery strategies. Sophisticated (and more productive) collections treatment strategies are made possible with intelligent data and decisioning solutions. Leveraging advanced risk decisioning software allows you to segment delinquent accounts based on risk profiles, prioritize collections efforts, determine the best communications channels, and tailor recovery efforts to individual borrower profiles. Best of all, it allows you to anticipate defaults before they happen by closely analyzing customer behavior and economic trends to forecast likelihood of repayment, enabling you to approach debt recovery proactively and strategically. A more proactive approach not only helps to mitigate losses, but also supports a much more empathetic and effective recovery process, ensuring long-term management of your customer relationships.
Intelligent risk decisioning solutions are key to staying ahead of post-election shifts. By incorporating AI and advanced data analytics in one holistic platform, these decisioning solutions enable you to:
Financial services providers that adopt forward-looking, proactive strategies (and which are armed with the right technology) will prove more resilient, positioning themselves for sustainable growth even in the face of political and economic change. Are you ready?
Embedded finance has quickly emerged as a game-changer in the industry, with a predicted global market size of $348.8 billion by 2029, at a growth rate of 30% CAGR from 2023-2029. By seamlessly integrating financial services into non-financial platforms, companies are able to streamline operations and enhance the customer experience, creating frictionless journeys and improving customer loyalty and retention. Major players are on both sides of the fence – both those successfully weaving financial services directly into their core offerings, and those supporting this wave of tech innovation with cutting-edge solutions and APIs that empower embedded financial services. We’re looking at both – how these industry leaders are dominating the embedded finance area and the crucial role their tech partners play in making this integration happen.
Companies across the globe are leading the charge in embedding finance into their services, transforming customer experiences, and driving growth. These examples (among many!) demonstrate the immense potential of embedded finance to streamline operations, enhance customer satisfaction and loyalty, and open new revenue streams. For those looking to explore embedded financing options, Provenir’s AI-powered risk decisioning solutions can enable you to integrate financial services seamlessly, manage risk effectively across the lifecycle, and deliver exceptional value to your customers.
Embedded finance, referring to the integration of financial services into non-financial platforms, is enabling businesses to offer banking, lending, insurance, and payment services directly within their existing products, whether those are applications, websites or other platforms. The trend is gaining traction rapidly, in part due to its ability to create more cohesive, seamless user experiences and streamline financial transactions. The value of embedded finance in 2022 reached $66.8 billion, but estimates put that figure at $622.9 billion by 2032, highlighting how it’s poised to become a dominant force in the industry. This growth is driven by the increasing demand for convenience and the desire for businesses to differentiate themselves in a competitive market by integrating innovative financial solutions. Companies across various sectors, from travel to retail and everything in between, are recognizing the value of creating super-apps or platforms that incorporate a variety of types of services (including financial) to enhance customer loyalty and create new revenue streams.
Uber and Shopify are just two big-name examples of organizations already leveraging embedded finance to enhance their services. Uber, the ride-sharing titan, offers instant payments to drivers, while Shopfiy allows for merchant cash advances and payment processing right in its proprietary platform. Likewise, retail giant Amazon offers its customers buy now, pay later (payment in installments) services right at checkout, and Tesla offers its car buyers insurance options, streamlining the process of getting coverage for their new vehicles. So why is embedded finance so popular?
There’s a ton of benefits that embedded finance can offer to enhance your business operations and the experiences of your customers. Let’s take a closer look.
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3. Enhanced Customer Experience |
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Step 1: Assess Your Business Needs |
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Step 2: Choose the Right Technology Partner(s) |
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Step 3: Implement Your Embedded Finance Plan |
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According to a 2023 survey by MuleSoft and Deloitte, large enterprises now use an average of more than a thousand applications across their organization.
So what exactly is tech bloat, and how can you slim down your stack? Read on to find out more.
Referring to the excessive accumulation of outdated, redundant, or highly complex tech systems that weigh down an organization, tech bloat in financial services is becoming increasingly common. This phenomenon stems from a variety of causes, but the biggest tends to be an abundance of legacy systems that have been patched and repurposed over the years. Of course many financial services providers require very specific needs to be addressed (including everything from core banking systems and risk assessment models, to cybersecurity software, workflow automation, customer relationship management, financial planning and forecasting, data sources, fraud and identity management, loan origination software, and payment processing). As the list of needs (and related tech) grows with your organization, so does the bloat.
But many of the software solutions you have will overlap in functionality, leading to inefficiencies in both operation and cost. A survey by Freshworks shared that “54% of IT professionals say their organization pays for software” that never gets used. And often these systems are not integrated with each other very well, creating numerous silos of information, complicating workflows, and making data access tricky. Not to mention the fact that extensive customizations and add-ons over the years, while useful at first, can quickly turn into burdens, limiting flexibility and making maintenance and updates difficult. And of course those updates are critical, because with constant regulatory shifts, financial institutions do regularly need to update their systems, which can result in a quickly tangled web of temporary fixes that, you guessed it, add more bloat (not to mention leave you more vulnerable to everything from data breaches to lapses in compliance).
According to Freshworks, “the cost of trying to use unhelpful technology amounts to more than $84B annually in wasted time in the US alone, or $10M every hour of every day.”
Any of these consequences should be enough to address your tech bloat problem, but put them all together and you can see it’s not just about security or reducing operational costs – it’s fundamental to unlocking your potential for sustained innovation and sustainable growth. Streamlining your tech infrastructure allows you to overcome these challenges and position yourself for future success and customer loyalty.
Consider the case of Provenir customer NewDay. Some of their existing systems were proving costly in terms of release times and updates, and were due for decommissioning. By implementing more holistic risk decisioning software, they were able to significantly reduce processing time and improve quote response times.
second decisioning processing time
SLA for availability
improvement in speed of change
faster quote response
1. Conduct a Technology Audit: |
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2. Streamline and Consolidate: |
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3. Invest in Modern, Integrated Solutions: |
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4. Enhance Data Management and Governance: |
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5. Foster a Culture of Continuous Improvement: |
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6. Partner with the Right Tech Providers: |
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Part of fighting the bloat battle is selecting the right technology partner – one that can enable flexibility, scalability, and an end-to-end decisioning platform that you can build and grow your business on. Provenir’s AI-Powered Decisioning Platform brings together the key capabilities you need to turn decisioning into a differentiator, allowing you to deploy accurate, fully automated risk decisioning across the lifecycle, while also gaining actionable insights to optimize strategies and enhance performance across the entire organization. Featuring solutions for data, decisioning, case management, and decision intelligence, across onboarding, fraud & identity management, customer management and collections, Provenir’s platform is a one-stop solution that eliminates silos, brings teams together, and enables sustainable, customer-centric growth.
The connected vehicle payments market could reach $600 billion by 2030.
As we’re already witnessing, Generative AI will continue to have a massive impact. It is certainly making life easier in many ways (chat bots, personalized email and marketing campaigns, dynamic customer management, etc.), but it will also mean greater ease in testing products and models as new data sets are generated (which used to take an incredible amount of time when done manually). Generative AI could also help test different use cases for products and UAT testing (which is traditionally very difficult and time consuming). We can also use Generative AI to translate videos and documents in real-time, or even do live translations in meetings, increasing the serviceable markets of financial services providers who may have previously been limited by language or region.
AI in Banking market was worth $6794.27 million USD in 2023, and is expected to reach $36765.29 million USD by 2023 (CAGR of 32.5%)
Quantum computing promises to fundamentally change the capacity to process information by performing calculations at speeds unattainable by traditional computers, enabling the ability to execute complex risk simulations and fraud decisioning and detection algorithms. This speed enables quicker, and more informed risk decisoning for financial services providers. Quantum algorithms could simulate market reactions to economic events or stress test financial portfolios under a variety of conditions, providing insights at a speed and scale that just isn’t possible with today’s computation methods.
Globally, the financial services industry’s spending on quantum computing capabilities is expected to grow 233x from just US$80 million in 2022 to US$19 billion in 2032, growing at a 10-year CAGR of 72%
Offering a decentralized and secure platform that can transform traditional banking infrastructure, credit approvals, and monitoring systems, blockchain technology can make big waves in risk decisioning, with advancements in peer-to-peer lending, smart contracts, and fraud screening measures. With transparent and fixed record-keeping, the technology can streamline processes and reduce operational costs, automating credit decisioning and other transactional processes. And with blockhain’s inherent transparency, the reliability of financial data is improved, greatly enhancing fraud and identity management. When it comes to the increasingly important aspect of identity verification, blockchain can also be useful – enabling Self-Soverign Identity (SSI) and Decentralized Identifiers (DIDs). SSIs allow individuals to own and control their own digital identities, stored on a blockchain for maximum privacy and security, while DIDs use unique, blockchain-based identifiers that can be verified across different platforms without exposing personal data.
There is around $52 billion of value locked in DeFI, and global blockchain spending is expected to hit $19 billion this year
134 countries and currency unions, representing 98% of global GDP, are exploring a CBDC
The integration of the Internet of Things (IoT) in banking could provide continuous data streams to credit risk models, offering real-time insights into a potential borrower’s financial activities and habits, and ensuring more dynamic (and accurate) credit risk decisioning and lower default rates. For instance, data from smart home devices could inform lenders about a customer’s energy consumption patterns, which might correlate with financial stability or risk levels. This level of integration can lead to even more personalized risk assessments, potentially improving credit access and inclusion while mitigating risks for lenders.
IoT In Banking And Financial Services Market size is projected to reach USD $30925 Million by 2030, growing at a CAGR of 50.10% from 2023 to 2030.
Financial institutions are the second most impacted sector based on the number of reported data breaches; ransomware attacks on financial services increased from 55% in 2022 to 64% in 2023.
Global sustainable finance product issuance totalled $717 billion in the first half of 2023.
By the end of 2024, Gartner predicts 75% of the global population will have its personal data protected by modern privacy regulations.
Western Europe and Asia Pacific will potentially account for 50% of digital ID verification spend by 2028.
Technology has always had the power to drive significant change in all aspects of society, and future tech advancements will continue to alter how financial institutions operate and interact with their customers. A common theme running through all of these innovations is the ability to personalize products and offerings, highlighting the extreme importance of the customer experience. A prime example of this is dynamic, responsive onboarding – where financial services providers are tailoring the onboarding experience to individual customers by matching data checks (including identity verification, AML, KYC, and more) to the event risk and the responses of the customer. Depending on the consumer’s answers in an application, the actual application itself will change dynamically – populating additional responses required or minimizing friction with fewer questions if lower risk is determined.
Today’s consumers will no longer stand for long wait times, inadequate customer service, and mass-marketed products. Instead, a competitive edge requires rapid response times, omnichannel offerings, customized products, and frictionless experiences – all enabled by automated, real-time decisioning.
But the concept of ‘decisioning’ itself will also evolve. Currently financial services providers utilize specific triggers that result in a decision being made, whether that’s from the end-consumer applying for a product, or from a provider proactively analyzing data and making a decision to offer a new product. But with the increased availability of data, extremely fast processing speeds, and the enhanced use of AI to analyze data and behaviors, decisioning will become much more fluid. Rather than trigger points causing a decision, are we in for a future where decisions around customers and products/services are just continuous? Seamless? Always happening? This too will result in more hyper-personalization and a customer-centric approach in all aspects of financial services.
Done well, personalization at scale for banking customers can lead to annual revenue uplifts of 10%
As these technologies develop, Provenir continues to lead the charge, offering an advanced decision intelligence platform that is adaptable, efficient, and strategically forward-thinking. Discover why choosing Provenir is the best decision for managing risk in a technologically evolving landscape.