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Authored by Vishal Gossain, Practice Leader, Risk Analytics and Strategy and Co-contributed by Divya Tulapurkar, Senior Manager, Financial Services Risk Management, Shelly Wu, Senior Manager, Financial Services Risk Management and Jessie Wang, Senior Manager, Financial Services Risk Management
Embracing the right analytical solution to reframe risk management can help financial institutions optimize profitability and build resilience.
In brief
- Banks and financial institutions are no longer limited to making either/or lending decisions based on risk or profitability.
- New technologies now empower institutions to embrace a more holistic, profit-based approach to lending decisions.
- Applying tech tools in this way helps institutions increase profitability on individual lending decisions and maintain greater balance portfolios.
Now is the time for profit-based risk management
Why rethink risk management frameworks now?
There are a lot of different ways for financial institutions to assess a customer. That said, the emergence of artificial intelligence (AI) and advanced machine learning (ML) means lending decisions no longer need to be based on either risk or profitability. Technology allows us to broaden those assessments and make holistic decisions that take both elements into consideration.
Historically, financial institutions determined risk appetite through a top-down approach, grounded in a static understanding of how “good” or “bad” a customer was (i.e., a customer’s risk to default on their loan obligations). For instance, do they make timely payments and meet certain thresholds?
Now, new modelling and strategy approaches allow us to create a much more comprehensive customer view using customer 360 data, one capable of redefining exactly what makes a good customer good by understanding the potential revenue, loss and expenses associated with each lending decision. These tools enable institutions to model individual borrower decisions and then layer that model against the wider portfolio to understand how the pieces — and profitability — fit together.
Case in point: a customer who might have traditionally been considered a higher-risk borrower (i.e., does not always make payments in a timely manner) could represent an opportunity as part of a broad-based portfolio with an optimized risk-reward approach and individualized customer products (e.g., customized lines, tenures, rewards and pricing).
And the tech solutions at our fingertips now empower us with a direct line of sight to gain that understanding and make decisions accordingly. In turn, banks can help customers across the credit spectrum, including underserved customers who have historically been unable to access banking services due to financial hardship.
The ability to reverse-engineer risk management decisions around optimized profitability within risk appetite can drive a far-reaching impact right across a financial institution. What’s more, because these tech solutions can generate even better access to customer data, deploying this approach can simultaneously open up additional opportunities to personalize customer experiences, offers, services and products. That can fuel a competitive advantage in the marketplace.
By employing technology in these new ways, financial institutions can foster profitability and dial down risk while addressing the ever-evolving need to personalize the customer experience in ways that deliver value. That’s huge.
What’s the cost of standing still?
Applying AI and ML as part of an integrated, profit-based risk management solution can help maximize your profitability on every lending decision made. While upsides abound, the risks of maintaining existing, risk-based approaches to decisions can significantly hamper future profitability and growth. Put simply, institutions that don’t embrace these new capabilities could ultimately price themselves out of the market. Add in the additional lost opportunity around customer personalization, and failure to adapt now could lead institutions to lose out on market share and income.
How can financial institutions deploy tech to fuel profit-based risk management?
We’re living in unprecedented times, when several shocks to the system are brought by rising interest rates, inflation and geopolitical instability, coupled with long-term disruptive effects of the pandemic. Banks globally need to work harder and take bold steps to futureproof themselves, improving short-term resilience and embracing long-term opportunities to become more profitable.
Embarking on a new, profit-based approach to managing risk doesn’t have to feel like boiling the ocean all at once. The important thing is to get the fundamentals right. If you’re considering the possibilities, keep these three guiding principles in mind to jumpstart your transition:
- Form the right partnership. Leaders in this space and trusted advisors should be genuinely invested in your long-term success. Settle for nothing less. Explore non-traditional pricing structures like revenue sharing or value-based pricing. Look for a partner who’s willing to carve the path to profit-based risk management together with you. Then measure the revenue together.
- Tighten up lead time. Applying a solution that’s readily available and deployable can save you time and money. In fact, some existing solutions are tech agnostic and show revenue returns within six months — much less than the two years it could take to develop something similar in house. Dig into what’s on offer and align your resources to a solution that can start delivering value here and now.
- Align tools and insight. It’s not enough to just deploy a tech solution. You’re going to need comprehensive support built on the right mix of technology and insight. Seek guidance from an integrated service provider that blends technical, consulting and industry expertise to make your rollout seamless and effective.
Summary
Embracing an integrated, profit-based risk management solution can have a transformational impact across banks and financial institutions. Applying AI and ML to adapt in this way can open up new routes to market share, income growth and sustainable growth — all while balancing risk effectively.