In this post, we look at the risk decision models that underlie banking and insurance operations. Kailee Costello spoke to the Co-Founder and CEO of Taktile, Maik Taro Wehmeyer, about how Taktile has developed a low-code automated decisioning platform that enables companies to continuously iterate on their risk decision models and more easily collaborate across their organizations.
Risk pricing is core to banking and insurance operations. However, many financial institutions don’t have the right backend infrastructure, tools, and processes to optimize risk decisions.
In today’s financial climate, business performance for lenders and insurers is dependent not only on being able to price risk well, but also on being able to experiment, iterate, and refine decision models to deliver better, more accurate results.
For many companies, the process of building decision models is cumbersome; it requires input from data scientists and risk analysts to determine how credit assessments and decisions should be made (for example, who should be approved for a credit card, buy-now-pay-later service, or mortgage), and then engineering support to codify these models into technology systems.
Critically, these models are hard to update, leaving financial institutions slow to adjust their risk model to respond to changing macroeconomic factors.
Co-Founder and CEO of Taktile, Maik Taro Wehmeyer, shared his insights with us.
Can you tell us about Taktile’s solutions?
Maik: Taktile is a modern interactive decision design platform. We empower lenders and insurers around the world to simplify and enhance the way they make automated decisions. This is important because the world runs on automated decisions. Credit, risk, insurance–all of these decisions are automated. But many risk teams don’t have an easy way to build, run, and evaluate these decisions. Instead, they rely on guesswork and engineering teams to drive change.
Taktile changes that. Our low-code platform makes it possible for non-technical users, like risk analysts, to not only set up a new decision flow, such as a new credit policy, but also integrate new data sources, experiment, test, and refine that flow to deliver more accurate outcomes. This is important because, for the best results, optimizing your risk selection is not something you do once; you do it on a continuous basis.
For example, let’s assume you want to bring out a new credit card. You might start giving it out to a small sample size of the population to test “does it work well?” Based on the results of this test, you might decide to expand to a wider customer base. To assess that wider population accurately, you might need to bring in a new variable or bring in a new data source to accurately assess risk. If your decision logic is hard coded, it can be extremely time-consuming and painstaking to change your flows. Taktile makes it possible for a non-technical person to not only add logic to a decision flow — but to then also conduct tests to see if that change leads to better outcomes before setting it live. With these steps, you can improve your business outcomes, such as reducing default rates or improving conversion rates.
The other part of Taktile’s value proposition is tied to the data required to make these decisions. In the US, there are three credit bureaus that give quite a good indicator of if a person should be getting a financial product, but that’s not the only source you can use — there are many alternative data sources that can provide new insights into applicants. On Taktile, you can connect to the different data sources and use all these data sources in your decision flows. This is what makes it very powerful, because just having access to first-party data that the customer inputs into your website is normally not enough to make a detailed and segmented risk decision.
Why did you start Taktile? Is what the company looks like today what you originally envisioned as you started on that journey?
Maik: My co-founder Max and I previously worked together at a risk consultancy for large financial institutions. While there, we built bespoke machine learning models for banks and insurance companies. We saw that none of these companies had the infrastructure at hand to orchestrate and build these decision flows. The banks and insurance companies wanted to own their risk and lending models — after all, they lie at the heart of every insurance company and bank — but the infrastructure to orchestrate and design these decisions was something that nobody considered core and we had to rebuild every time.
In 2020, we initially started building a machine learning platform for advanced fintechs, banks, and insurance companies. In this original state, data scientists would use the platform to host machine learning models. However, our customers asked, “why can’t we deploy our business rules on Taktile?” So we made the decision to expand our scope to be a decisioning platform that could be used not only by machine learning engineers, but also by non-technical stakeholders that cannot code, such as risk analysts or credit analysts. We did that by creating a low-code environment where teams could collaborate on decision flows — and the impact has been incredible. Everyone from risk analysts to data scientists to engineers to compliance managers can collaborate to build the best decision flows for their company.
How did you approach developing Taktile’s solutions — did you focus on a particular vertical first, and if so, why?
Maik: We started with the credit underwriting vertical because there was huge customer demand and because credit underwriting involves complex decisioning. We wanted to tackle the hardest use case first. But we see incredible opportunities for Taktile beyond credit underwriting. We want to build software that can be used across verticals, such as underwriting, claims, and risk. And we’re already seeing proof that this works as we partner with insurance customers and see some of our customers using Taktile for fraud.
Is there anything you learned from developing the first iteration of your underwriting product that influenced how you built out your product suite?
Maik: One of the main learnings was that having all necessary data integrations in place is a game changer for customers. Before we had this ability, customers would say, “I would love to use FICO scores in my decision flows”, and we would tell them, “that’s great, you should build an integration.” Then they wanted to use banking data, accounting data, and so on. These questions came up over and over again and, as the software provider, we started to think, “maybe we should build that?”
We built these data integrations, and now, when we come to a new customer, everything they need is already in place on the platform. It was a big investment for us as a company to build these out, but it empowers us to deliver the best possible solution for our customers so they can onboard quickly, launch new products, and refine their flows.
What’s your vision for Taktile’s impact on the fintech and financial services sectors?
Maik: I see Taktile as the missing piece of the fintech stack. We will serve as the connective tissue that empowers fintechs and legacy banks to get the full picture of the risk associated with each customer and make better decisions.
More than that, we will help a lot of fintechs become profitable. There was a huge wave of neobanks and fintechs after 2010. This initial wave focused on delivering a better customer experience and grew incredibly quickly. In the low-interest rate environment of past years, they were rewarded by investors who said that growth is the most important metric. But now we’re in 2023; interest rates are rising, and venture money is drying up, particularly for growth-stage companies without a clear road to profitability. This is where Taktile comes in — to make sure that they’re not only growing, but that they’re growing profitably and are getting customers on board that are repaying their loans and not defaulting on their credit card. To do this, every fintech needs a decision engine. We have one ready to go and will help them become profitable.
Do you think the opportunity for Taktile is primarily supporting emerging fintechs, or is there also an opportunity to improve decision flows for legacy financial institutions?
Maik: We currently sell to a lot of advanced fintechs, but I certainly see opportunities with legacy providers–everyone wants to become more profitable, especially as a lot of them are undergoing digital transformation and moving to the cloud. We are already starting to move up-market. If you look at the future of Taktile, we want to be the leading decisioning platform in financial services around the globe.
What’s your perspective on the FinTech market for 2023 and beyond?
Maik: We wrote a fantastic blog article on that. Some trends I’m excited about are:
- FinTech growth in emerging markets: In countries like Nigeria, Kenya, and India, there is a completely unserved population — they don’t have credit scores, but they need access to financial products. Fintechs are doing great things in this space. For example, one of our customers is offering BNPL for healthcare in India at point-of-sale.
- Embedded lending: More marketplaces are directly offering point-of-sale solutions. For example, Shopify knows a lot about its store owners, and I personally think they are in a unique position to offer them working capital financing.
- BNPL shifting from B2C to B2B: SMBs have such a great need to make sure their working capital is secured, and having access to direct financing options at the point-of-sale is so valuable for B2B. It’s a very complex market — B2B is much more heterogeneous than B2C, so it’s a much harder problem to solve.
About Maik Taro Wehmeyer
Maik Taro Wehmeyer is the CEO and Co-Founder of Taktile, a modern automated decisioning platform that has offices in New York, London and Berlin. In a world increasingly run on automated decisions, Taktile’s low-code platform makes it easy for credit and data teams to build more accurate decision flows, adapt to change quickly, and, ultimately, improve outcomes. Prior to joining Taktile, Maik worked at QuantCo, McKinsey, and SAP. He has significant experience in the machine learning and financial services spaces, serving as a member of EU Commission’s AI Alliance and the German AI Alliance.
To learn more about Taktile, visit their website.
Follow Maik Taro Wehmeyer or Taktile on LinkedIn.
Interested in joining Taktile? We’re hiring! Check out open roles.
About the Author
Kailee Costello is a first-year MBA Candidate at The Wharton School, where she is part of the Wharton FinTech Podcast team. She’s most passionate about how FinTech is breaking down barriers to make financial products and services more accessible — particularly in the personal finance space. Don’t hesitate to reach out with questions, comments, feedback, and opportunities at [email protected].
As always, for more FinTech insights and opportunities to collaborate, please find us below:
Medium Blog | Twitter | Our Website | LinkedIn
Suggest a Podcast Guest: https://airtable.com/shrdbokQPxAJzgVh7
Hire Wharton FinTech MBAs: https://www.whartonfintech.org/recruiting