Wednesday, June 22, 2011

My Favorite Two Tips for New Risk Teams

Every now and then I get to talk to companies either going into payments or having to deal with the effects of risk and fraud in payments. Usually that's a good sign - you need to be big enough to care, and that mostly means that you have good trajectory - but having to deal with risk and user behavior in payments without a manual (none exists) is difficult. To make matters worse, there aren't a lot of folks with this specific experience who are ready to hop on to a company looking to start a team from scratch.

Naturally every company is slightly different in the way its product utilizes payments. A marketplace for tangible items having to manage both merchant and consumer risk is different than a gaming platform with immediate delivery and high refund rates; business models also impact loss tolerance and use of various payment options. And so, providing one general advice constantly fails - well, other than "take it slow and iterate quickly", but you already knew that. There is, however, some advice I keep repeating at these very early stages.

  1. Hire the right person. As I describe in The Factory Approach, your first hires are crucial for the way your risk and decision team will grow. I've written multiple times in the past about the importance of hiring people who can articulate complex patterns. Find someone who combines a knack for patterns and data, can understand technology, but is able to deliver results in an operational environment. You may be looking for two different people (although my experience shows that these people exist - only outside of standard engineering practices)... hire the right person, and a huge number of the childhood illnesses of your department (over-reacting to losses, solving problems with low quality man power) will be spared. oh, and if you read this and feel like you're the right person for the job, I'm hiring!

  2. Instrument, instrument, instrument. No one has ever looked back at the first two years of his company running and said "I shouldn't have kept all that data". From the payments and risk perspective, this means a few things: decide on an entity-focused data structure and stick to it. When you add functionality, properly abstract rather than add flags and columns that are called "is_transaction_refunded_yes_no". Never delete rejected, refunded or cancelled orders. Properly document state changes. Instrument internal decisions and manual decision clicks. Finally, never build a complex ETL process to provide Risk folks with data; risk isn't business analytics - it is engineering with a sprinkle of manual review. Trust me, this will be one of your most precious assets even a few months down the road.
Are these enough for building a successful risk management team? No. But they are a good start and two things to keep in mind while you think about this complex task.

As always, I'm available for questions at @ohadsamet

Tuesday, June 7, 2011

Come Reinvent Payments with Us – Klarna is looking for Decision Analysts

Trying to purchase something is still far from a perfect experience, especially online. Not only are you taken through a tedious sign-up process, you’re also expected to trust the merchant and pay them before you even get to look at the merchandise. No wonder that only 9% of total commerce is done online: it’s just not easy enough. Klarna is looking to solve all that.

Klarna was founded 6 years ago by three Swedish entrepreneurs and has been growing rapidly ever since, thanks to its offering. It lets customers pay only after getting their product, while guarding merchants from risk – making purchases simpler and safer for everyone while growing sales for merchants. This also drew one of the best (maybe THE best) VCs in the world – Sequoia – to invest in the company.

We are Klarna’s Risk Management and Decision team; we deploy state of the art methodologies and tools (forensics, pattern recognition, network analysis, advanced statistics and even Theory of Constraints) to deliver the decisions that make Klarna’s business model possible. We’re looking for analysts to join the team.

This is where you come in.

Decision analysts in Klarna are motivated, strong achievers who specialize in using our methodology and tools to prevent payments fraud, predict credit worthiness and stop abusive customers. They work individually and in a group to identify patterns in user behavior data and turn these patterns into accept and reject decisions, delivered both manually and automatically. This is an entry level position with excellent prospects for getting into data analysis, risk management and automated decisions. If these areas sound interesting, you need to apply.

If you are our dream candidate, you probably:
·        Play to win. You know what we mean.
·        Can absorb vast quantities of information in short periods of time.
·        Have some proven ability to make quality decisions based on partial data and under time pressure.
·        Know or at least have a tendency to look at masses of data and identify patterns in it.
·        Are constantly encouraged by your friends to go on game shows because you always know the answers.
·        Lead an active life with multiple activities – because you can always rest later.

Some formalities:
  • This is a full time position in either Sweden (Stockholm) or Israel (Tel Aviv), with preference for Stockholm. Be local, or dazzle us completely and be ready to relocate ASAP. That said, if you feel like this is your dream job and you’re in the US, do drop me a line.
  • Fluent English is a must. Additional languages are a plus (in Israel, Hebrew is highly desired).
  • No relevant experience required. We prefer diverse backgrounds (I hold a B.Sc. in Biology and Philosophy). That said, if you’re experienced and looking for cool new challenges – we have multiple advanced challenges.
  • Bachelors’ graduates preferable, but all (= high school students to PhDs) may apply.
  • Some proof of excellence and analytic skills is highly desired (GMAT or Psychometric exam over 700, SAT > 1400, top programs, top schools)
  • Some technical skills or background (again, doesn't have to be formal) will push you to the front of the line. Please don’t refer to proficiency with Office as “technical skills”.

Interested? Contact me @ / @ohadsamet